• 2024

    • Z. He
    • B. Chu
    • J. Yang
    • J. Gu
    • Z. Chen
    • L. Liu
    • T. Morrison
    • M. E. Belloy
    • X. Qi
    • N. Hejazi
    • M. Mathur
    • Y. L. Guen
    • H. Tang
    • T. Hastie
    • I. Ionita-laza
    • C. Sabatti
    • E. Candès
    In silico identification of putative causal genetic variants. bioRxiv. Pre-published. 2024.
    @article{He2024.02.28.582621,
      author = {He, Zihuai and Chu, Benjamin and Yang, James and Gu, Jiaqi and Chen, Zhaomeng and Liu, Linxi and Morrison, Tim and Belloy, Michael E. and Qi, Xinran and Hejazi, Nima and Mathur, Maya and Guen, Yann Le and Tang, Hua and Hastie, Trevor and Ionita-laza, Iuliana and Sabatti, Chiara and Candès, Emmanuel},
      title = {In silico identification of putative causal genetic variants},
      journaltitle = {bioRxiv},
      publisher = {Cold Spring Harbor Laboratory},
      date = {2024},
      annotation = {2024e},
      doi = {10.1101/2024.02.28.582621},
      eprint = {https://www.biorxiv.org/content/early/2024/03/03/2024.02.28.582621.full.pdf},
      pubstate = {Pre-published},
      url = {https://www.biorxiv.org/content/early/2024/03/03/2024.02.28.582621},
    }
    • T. Zrnic
    • E. J. Candès
    Active statistical inference. Pre-published. 2024.
    @article{zrnic2024active,
      author = {Zrnic, Tijana and Candès, Emmanuel J.},
      title = {Active Statistical Inference},
      date = {2024},
      annotation = {2024d},
      eprint = {2403.03208},
      eprintclass = {stat.ML},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • E. Zeger
    • Y. Wang
    • A. Mishkin
    • T. Ergen
    • E. Candès
    • M. Pilanci
    A library of mirrors: Deep neural nets in low dimensions are convex lasso models with reflection features. Pre-published. 2024.
    @article{zeger2024library,
      author = {Zeger, Emi and Wang, Yifei and Mishkin, Aaron and Ergen, Tolga and Candès, Emmanuel and Pilanci, Mert},
      title = {A Library of Mirrors: Deep Neural Nets in Low Dimensions are Convex Lasso Models with Reflection Features},
      date = {2024},
      annotation = {2024c},
      eprint = {2403.01046},
      eprintclass = {cs.LG},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • Z. Chen
    • Z. He
    • B. B. Chu
    • J. Gu
    • T. Morrison
    • C. Sabatti
    • E. Candès
    Controlled variable selection from summary statistics only? A solution via GhostKnockoffs and penalized regression. Pre-published. 2024.
    @article{chen2024controlled,
      author = {Chen, Zhaomeng and He, Zihuai and Chu, Benjamin B. and Gu, Jiaqi and Morrison, Tim and Sabatti, Chiara and Candès, Emmanuel},
      title = {Controlled Variable Selection from Summary Statistics Only? A Solution via GhostKnockoffs and Penalized Regression},
      date = {2024},
      annotation = {2024b},
      eprint = {2402.12724},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • Z. Yang
    • E. Candès
    • L. Lei
    Bellman conformal inference: Calibrating prediction intervals for time series. Pre-published. 2024.
    @article{yang2024bellman,
      author = {Yang, Zitong and Candès, Emmanuel and Lei, Lihua},
      title = {Bellman Conformal Inference: Calibrating Prediction Intervals For Time Series},
      date = {2024},
      annotation = {2024a},
      eprint = {2402.05203},
      eprintclass = {cs.LG},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
  • 2023

    • T. Zrnic
    • E. J. Candès
    Cross-prediction-powered inference. Pre-published. 2023.
    @article{zrnic2023crosspredictionpowered,
      author = {Zrnic, Tijana and Candès, Emmanuel J.},
      title = {Cross-Prediction-Powered Inference},
      date = {2023},
      annotation = {2023i},
      eprint = {2309.16598},
      eprintclass = {stat.ML},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • A. N. Angelopoulos
    • E. J. Candès
    • R. J. Tibshirani
    Conformal PID control for time series prediction. NeurIPS 2023. Forthcoming. 2023.
    @inproceedings{angelopoulos2023conformal,
      author = {Angelopoulos, Anastasios N. and Candès, Emmanuel J. and Tibshirani, Ryan J.},
      title = {Conformal {PID} Control for Time Series Prediction},
      booktitle = {NeurIPS 2023},
      date = {2023},
      annotation = {2023h},
      eprint = {2307.16895},
      eprintclass = {cs.LG},
      eprinttype = {arXiv},
      pubstate = {Forthcoming},
    }
    • Y. Jin
    • E. J. Candès
    Model-free selective inference under covariate shift via weighted conformal p-values. Pre-published. 2023.
    @article{jin2023modelfree,
      author = {Jin, Ying and Candès, Emmanuel J.},
      title = {Model-free selective inference under covariate shift via weighted conformal p-values},
      date = {2023},
      annotation = {2023g},
      eprint = {2307.09291},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • J. Jang
    • E. Candès
    Tight distribution-free confidence intervals for local quantile regression. Pre-published. 2023.
    @article{jang2023tight,
      author = {Jang, Jayoon and Candès, Emmanuel},
      title = {Tight Distribution-Free Confidence Intervals for Local Quantile Regression},
      date = {2023},
      annotation = {2023f},
      eprint = {2307.08594},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • K. Huang
    • Y. Jin
    • E. Candès
    • J. Leskovec
    Uncertainty quantification over graph with conformalized graph neural networks. NeurIPS 2023. Forthcoming. 2023.
    @inproceedings{huang2023uncertainty,
      author = {Huang, Kexin and Jin, Ying and Candès, Emmanuel and Leskovec, Jure},
      title = {Uncertainty Quantification over Graph with Conformalized Graph Neural Networks},
      booktitle = {NeurIPS 2023},
      date = {2023},
      annotation = {2023e},
      eprint = {2305.14535},
      eprintclass = {cs.LG},
      eprinttype = {arXiv},
      pubstate = {Forthcoming},
    }
    • I. Gibbs
    • J. J. Cherian
    • E. J. Candès
    Conformal prediction with conditional guarantees. Pre-published. 2023.
    @article{gibbs2023conformal,
      author = {Gibbs, Isaac and Cherian, John J. and Candès, Emmanuel J.},
      title = {Conformal Prediction With Conditional Guarantees},
      date = {2023},
      annotation = {2023d},
      eprint = {2305.12616},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • J. J. Cherian
    • E. J. Candès
    Statistical inference for fairness auditing. Pre-published. 2023.
    @article{cherian2023statistical,
      author = {Cherian, John J. and Candès, Emmanuel J.},
      title = {Statistical Inference for Fairness Auditing},
      date = {2023},
      annotation = {2023c},
      eprint = {2305.03712},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
      pubstate = {Pre-published},
    }
    • A. Spector
    • E. Candès
    • L. Lei
    A discussion of “A note on universal inference” by Tse and Davison. Stat. Early access. 2023.
    @article{spector2023discussion,
      author = {Spector, Asher and Candès, Emmanuel and Lei, Lihua},
      title = {A Discussion of “{A} Note on Universal Inference” by {T}se and {D}avison},
      journaltitle = {Stat},
      volume = {12},
      number = {1},
      pages = {e570},
      date = {2023},
      annotation = {2023b},
      doi = {10.1002/sta4.570},
      pubstate = {Early access},
    }
    • R. F. Barber
    • E. J. Candes
    • A. Ramdas
    • R. J. Tibshirani
    De Finetti’s theorem and related results for infinite weighted exchangeable sequences. Sankhya. Forthcoming. 2023.
    @article{barber2023finettis,
      author = {Barber, Rina Foygel and Candes, Emmanuel J. and Ramdas, Aaditya and Tibshirani, Ryan J.},
      title = {De {F}inetti's Theorem and Related Results for Infinite Weighted Exchangeable Sequences},
      journaltitle = {Sankhya},
      date = {2023},
      annotation = {2023a},
      eprint = {2304.03927},
      eprintclass = {math.ST},
      eprinttype = {arXiv},
      pubstate = {Forthcoming},
    }
  • 2022

    • P. Nobel
    • E. Candès
    • S. Boyd
    Tractable evaluation of Stein’s unbiased risk estimator with convex regularizers. IEEE Transactions on Signal Processing. 2023.
    @article{nobel2022tractable,
      author = {Nobel, Parth and Candès, Emmanuel and Boyd, Stephen},
      title = {Tractable Evaluation of {S}tein's Unbiased Risk Estimator with Convex Regularizers},
      journaltitle = {IEEE Transactions on Signal Processing},
      volume = {71},
      pages = {4330--4341},
      date = {2023},
      annotation = {2022g},
      doi = {10.1109/TSP.2023.3323046},
    }
    • Y. Jin
    • E. J. Candès
    Selection by prediction with conformal p-values. Journal of Machine Learning Research. 2023.
    @article{jin2022selection,
      author = {Jin, Ying and Candès, Emmanuel J.},
      title = {Selection by Prediction with Conformal p-values},
      journaltitle = {Journal of Machine Learning Research},
      volume = {24},
      number = {244},
      pages = {1--41},
      date = {2023},
      annotation = {2022f},
      url = {https://jmlr.org/papers/v24/22-1176.html},
    }
    • Q. Zhao
    • E. J. Candès
    An adaptively resized parametric bootstrap for inference in high-dimensional generalized linear models. Statistica Sinica. Forthcoming. 2022.
    @article{zhao2022adaptively,
      author = {Zhao, Qian and Cand{ès}, Emmanuel J.},
      title = {An Adaptively Resized Parametric Bootstrap for Inference in High-dimensional Generalized Linear Models},
      journaltitle = {Statistica Sinica},
      date = {2022},
      annotation = {2022e},
      eprint = {2208.08944},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
      pubstate = {Forthcoming},
    }
    • I. Gibbs
    • E. Candès
    Conformal inference for online prediction with arbitrary distribution shifts. 2022.
    @article{gibbs2022conformal,
      author = {Gibbs, Isaac and Cand{è}s, Emmanuel},
      title = {Conformal Inference for Online Prediction with Arbitrary Distribution Shifts},
      date = {2022},
      annotation = {2022d},
      eprint = {2208.08401},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
    }
    • R. Foygel Barber
    • E. J. Candès
    • A. Ramdas
    • R. J. Tibshirani
    Permutation tests using arbitrary permutation distributions. Sankhya A. 2023.
    @article{barber2022permutation,
      author = {{Foygel Barber}, Rina and Cand{è}s, Emmanuel J. and Ramdas, Aaditya and Tibshirani, Ryan J.},
      title = {Permutation tests using arbitrary permutation distributions},
      journaltitle = {Sankhya A},
      volume = {85},
      number = {2},
      pages = {1156--1177},
      date = {2023},
      annotation = {2022c},
      doi = {10.1007/s13171-023-00308-8},
    }
    • C. Chia
    • M. Sesia
    • C. Ho
    • S. S. Jeffrey
    • J. Dionne
    • E. J. Candès
    • R. T. Howe
    Interpretable classification of bacterial raman spectra with knockoff wavelets. IEEE Journal of Biomedical and Health Informatics. 2022.
    @article{chia2022raman,
      author = {Chia, Charmaine and Sesia, Matteo and Ho, Chi-Sing and Jeffrey, Stefanie S. and Dionne, Jennifer and Candès, Emmanuel J. and Howe, Roger T.},
      title = {Interpretable classification of bacterial Raman spectra with knockoff wavelets},
      journaltitle = {IEEE Journal of Biomedical and Health Informatics},
      volume = {26},
      number = {2},
      pages = {740--748},
      date = {2022},
      annotation = {2022b},
      doi = {10.1109/JBHI.2021.3094873},
    }
    • R. F. Barber
    • E. J. Candès
    • A. Ramdas
    • R. J. Tibshirani
    Conformal prediction beyond exchangeability. Annals of Statistics. 2023.
    @article{barber2022conformal,
      author = {Barber, Rina Foygel and Candès, Emmanuel J. and Ramdas, Aaditya and Tibshirani, Ryan J.},
      title = {Conformal prediction beyond exchangeability},
      journaltitle = {Annals of Statistics},
      volume = {51},
      number = {2},
      pages = {816--845},
      date = {2023},
      annotation = {2022a},
      doi = {10.1214/23-AOS2276},
    }
  • 2021

    • Z. He
    • L. Liu
    • M. E. Belloy
    • Y. Le Guen
    • A. Sossin
    • X. Liu
    • X. Qi
    • S. Ma
    • T. Wyss-Coray
    • H. Tang
    • C. Sabatti
    • E. Candes
    • M. D. Greicius
    • I. Ionita-Laza
    GhostKnockoff inference empowers identification of putative causal variants in genome-wide association studies. Nature Communications. 2022.
    @article{He2021.12.06.471440,
      author = {He, Zihuai and Liu, Linxi and Belloy, Michael E. and Le Guen, Yann and Sossin, Aaron and Liu, Xiaoxia and Qi, Xinran and Ma, Shiyang and Wyss-Coray, Tony and Tang, Hua and Sabatti, Chiara and Candes, Emmanuel and Greicius, Michael D. and Ionita-Laza, Iuliana},
      title = {GhostKnockoff inference empowers identification of putative causal variants in genome-wide association studies},
      journaltitle = {Nature Communications},
      volume = {13},
      pages = {7209},
      date = {2022},
      annotation = {2021i},
      doi = {10.1038/s41467-022-34932-z},
      issue = {1},
    }
    • Y. Jin
    • Z. Ren
    • E. J. Candès
    Sensitivity analysis of individual treatment effects: A robust conformal inference approach. Proceedings of the National Academy of Sciences. 2023.
    @article{jin2021sensitivity,
      author = {Jin, Ying and Ren, Zhimei and Candès, Emmanuel J.},
      title = {Sensitivity Analysis of Individual Treatment Effects: A Robust Conformal Inference Approach},
      journaltitle = {Proceedings of the National Academy of Sciences},
      volume = {120},
      number = {6},
      pages = {e2214889120},
      date = {2023},
      annotation = {2021h},
      doi = {10.1073/pnas.2214889120},
    }
    • A. N. Angelopoulos
    • S. Bates
    • E. J. Candès
    • M. I. Jordan
    • L. Lei
    Learn then test: Calibrating predictive algorithms to achieve risk control. Annals of Applied Statistics. Submitted. 2021.
    @article{angelopoulos2021learn,
      author = {Angelopoulos, Anastasios N. and Bates, Stephen and Candès, Emmanuel J. and Jordan, Michael I. and Lei, Lihua},
      title = {Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control},
      journaltitle = {Annals of Applied Statistics},
      date = {2021},
      annotation = {2021g},
      eprint = {2110.01052},
      eprintclass = {cs.LG},
      eprinttype = {arXiv},
      pubstate = {Submitted},
    }
    • S. Li
    • E. J. Candès
    Deploying the conditional randomization test in high multiplicity problems. 2021.
    @article{li2021deploying,
      author = {Li, Shuangning and Candès, Emmanuel J.},
      title = {Deploying the Conditional Randomization Test in High Multiplicity Problems},
      date = {2021},
      annotation = {2021f},
      eprint = {2110.02422},
      eprintclass = {stat.ME},
      eprinttype = {arXiv},
    }
    • S. Li
    • M. Sesia
    • Y. Romano
    • E. Candès
    • C. Sabatti
    Searching for robust associations with a multi-environment knockoff filter. Biometrika. 2022.
    @article{li2021searching,
      author = {Li, S and Sesia, M and Romano, Y and Candès, E and Sabatti, C},
      title = {Searching for robust associations with a multi-environment knockoff filter},
      journaltitle = {Biometrika},
      volume = {109},
      number = {3},
      pages = {611--629},
      date = {2022},
      annotation = {2021e},
      doi = {10.1093/biomet/asab055},
    }
    • I. Gibbs
    • E. Candès
    Adaptive conformal inference under distribution shift. Advances in neural information processing systems 34 (NeurIPS 2021). 2021.
    @inproceedings{gibbs2021adaptive,
      author = {Gibbs, Isaac and Candès, Emmanuel},
      title = {Adaptive Conformal Inference Under Distribution Shift},
      booktitle = {Advances in Neural Information Processing Systems 34 (NeurIPS 2021)},
      publisher = {Curran Associates, Inc.},
      pages = {1660--1672},
      date = {2021},
      annotation = {2021d},
      editor = {Ranzato, M. and Beygelzimer, A. and Dauphin, Y. and Liang, P.S. and Vaughan, J. Wortman},
      url = {proceedings.neurips.cc/paper/2021/file/0d441de75945e5acbc865406fc9a2559-Paper.pdf},
    }
    • S. Bates
    • E. Candès
    • L. Lei
    • Y. Romano
    • M. Sesia
    Testing for outliers with conformal p-values. Annals of Statistics. 2023.
    @article{bates2021multiple,
      author = {Bates, Stephen and Candès, Emmanuel and Lei, Lihua and Romano, Yaniv and Sesia, Matteo},
      title = {Testing for outliers with conformal p-values},
      journaltitle = {Annals of Statistics},
      volume = {51},
      number = {1},
      pages = {149--178},
      date = {2023},
      annotation = {2021c},
      doi = {10.1214/22-AOS2244},
    }
    • E. Candès
    • L. Lei
    • Z. Ren
    Conformalized survival analysis. Journal of the Royal Statistical Society Series B. 2023. (Website & code)
    @article{ConformalSurvivalAnalysis,
      author = {Candès, Emmanuel and Lei, Lihua and Ren, Zhimei},
      title = {Conformalized Survival Analysis},
      journaltitle = {Journal of the Royal Statistical Society Series B},
      volume = {85},
      number = {1},
      pages = {24--45},
      date = {2023},
      annotation = {2021b},
      doi = {10.1093/jrsssb/qkac004},
    }
    • D. Medarametla
    • E. Candès
    Distribution-free conditional median inference. Electronic Journal of Statistics. 2021.
    @article{MedianInference,
      author = {Medarametla, Dhruv and Candès, Emmanuel},
      title = {Distribution-Free Conditional Median Inference},
      journaltitle = {Electronic Journal of Statistics},
      volume = {15},
      number = {2},
      pages = {4625--4658},
      date = {2021},
      annotation = {2021a},
      doi = {10.1214/21-EJS1910},
    }
  • 2020

    • Z. Ren
    • Y. Wei
    • E. Candès
    Derandomizing knockoffs. Journal of the American Statistical Association. 2023. (Website & code)
    @article{derandomizingKnockoffs,
      author = {Ren, Zhimei and Wei, Yuting and Candès, Emmanuel},
      title = {Derandomizing Knockoffs},
      journaltitle = {Journal of the American Statistical Association},
      volume = {118},
      number = {542},
      pages = {948--958},
      date = {2023},
      annotation = {2020i},
      doi = {10.1080/01621459.2021.1962720},
    }
    • M. Sesia
    • S. Bates
    • E. Candès
    • J. Marchini
    • C. Sabatti
    False discovery rate control in genome-wide association studies with population structure. Proceedings of the National Academy of Sciences. 2021. (Website & code)
    @article{sesia2020controlling,
      author = {Sesia, Matteo and Bates, Stephen and Cand{è}s, Emmanuel and Marchini, Jonathan and Sabatti, Chiara},
      title = {False discovery rate control in genome-wide association studies with population structure},
      journaltitle = {Proceedings of the National Academy of Sciences},
      volume = {118},
      number = {40},
      pages = {e2105841118},
      date = {2021},
      annotation = {2020h},
      doi = {10.1073/pnas.2105841118},
    }
    • A. Weinstein
    • W. J. Su
    • M. Bogdan
    • R. F. Barber
    • E. J. Candès
    [A power analysis for model-X knockoffs with $\ell _{p}$-regularized statistics]. Annals of Statistics. 2023.
    @article{weinstein2020power,
      author = {Weinstein, Asaf and Su, Weijie J. and Bogdan, Ma{ł}gorzata and Barber, Rina Foygel and Candès, Emmanuel J.},
      title = {{A power analysis for model-X knockoffs with $\ell _{p}$-regularized statistics}},
      journaltitle = {Annals of Statistics},
      volume = {51},
      number = {3},
      pages = {1005--1029},
      date = {2023},
      annotation = {2020g},
      doi = {10.1214/23-AOS2274},
    }
    • L. Lei
    • E. J. Candès
    Conformal inference of counterfactuals and individual treatment effects. Journal of the Royal Statistical Society Series B. 2021. (Website & code)
    @article{lei2020conformal,
      author = {Lei, Lihua and Candès, Emmanuel J.},
      title = {Conformal inference of counterfactuals and individual treatment effects},
      journaltitle = {Journal of the Royal Statistical Society Series B},
      volume = {83},
      number = {5},
      pages = {911--938},
      date = {2021},
      annotation = {2020f},
      doi = {10.1111/rssb.12445},
    }
    • Y. Romano
    • S. Bates
    • E. J. Candès
    Achieving equalized odds by resampling sensitive attributes. Advances in neural information processing systems 33 (NeurIPS 2020). 2020.
    @inproceedings{romano2020achieving,
      author = {Romano, Yaniv and Bates, Stephen and Candès, Emmanuel J.},
      title = {Achieving equalized odds by resampling sensitive attributes},
      booktitle = {Advances in Neural Information Processing Systems 33 (NeurIPS 2020)},
      publisher = {Curran Associates, Inc.},
      pages = {361--371},
      date = {2020},
      annotation = {2020e},
      editor = {Larochelle, H. and Ranzato, M. and Hadsell, R. and Balcan, M. F. and Lin, H.},
      url = {proceedings.neurips.cc/paper/2020/file/03593ce517feac573fdaafa6dcedef61-Paper.pdf},
    }
    • Y. Romano
    • M. Sesia
    • E. J. Candès
    Classification with valid and adaptive coverage. Advances in neural information processing systems 33 (NeurIPS 2020). 2020. (Website & code)
    @inproceedings{romano2020classification,
      author = {Romano, Yaniv and Sesia, Matteo and Candès, Emmanuel J.},
      title = {Classification with valid and adaptive coverage},
      booktitle = {Advances in Neural Information Processing Systems 33 (NeurIPS 2020)},
      publisher = {Curran Associates, Inc.},
      pages = {3581--3591},
      date = {2020},
      annotation = {2020d},
      editor = {Larochelle, H. and Ranzato, M. and Hadsell, R. and Balcan, M. F. and Lin, H.},
      url = {proceedings.neurips.cc/paper/2020/file/244edd7e85dc81602b7615cd705545f5-Paper.pdf},
    }
    • S. Bates
    • M. Sesia
    • C. Sabatti
    • E. Candès
    Causal inference in genetic trio studies. Proceedings of the National Academy of Sciences. 2020. (Website & code)
    @article{DTT,
      author = {Bates, Stephen and Sesia, Matteo and Sabatti, Chiara and Candès, Emmanuel},
      title = {Causal inference in genetic trio studies},
      journaltitle = {Proceedings of the National Academy of Sciences},
      volume = {117},
      number = {39},
      pages = {24117--24126},
      date = {2020},
      annotation = {2020c},
      doi = {10.1073/pnas.2007743117},
    }
    • Q. Zhao
    • P. Sur
    • E. J. Candès
    The asymptotic distribution of the MLE in high-dimensional logistic models: Arbitrary covariance. Bernoulli. 2022.
    @article{LogisticCov,
      author = {Zhao, Qian and Sur, Pragya and Candès, Emmanuel J.},
      title = {The asymptotic distribution of the {MLE} in high-dimensional logistic models: Arbitrary covariance},
      journaltitle = {Bernoulli},
      volume = {28},
      number = {3},
      pages = {1835--1861},
      date = {2022},
      annotation = {2020b},
      doi = {10.3150/21-BEJ1401},
    }
    • Z. Ren
    • E. J. Candès
    Knockoffs with side information. Annals of Applied Statistics. 2023.
    @article{AdaptiveKnockoffs,
      author = {Ren, Zhimei and Candès, Emmanuel J.},
      title = {Knockoffs with side information},
      journaltitle = {Annals of Applied Statistics},
      volume = {17},
      number = {2},
      pages = {1152--1174},
      date = {2023},
      annotation = {2020a},
      doi = {10.1214/22-AOAS1663},
    }
  • 2019

    • E. J. Candès
    • J. Duchi
    • C. Sabatti
    Comments on [Michael Jordan’s essay ‘The AI Revolution Hasn’t Happened Yet’]. Harvard Data Science Review. 2019. (Website & code)
    @article{Candes2019Comments,
      author = {Candès, Emmanuel J. and Duchi, John and Sabatti, Chiara},
      title = {Comments on {Michael Jordan's essay `The AI Revolution Hasn't Happened Yet'}},
      journaltitle = {Harvard Data Science Review},
      volume = {1},
      number = {1},
      date = {2019-06-23},
    }
    • M. Sesia
    • E. J. Candès
    A comparison of some conformal quantile regression methods. Stat. 2020.
    @article{CQRComparison,
      author = {Sesia, Matteo and Candès, Emmanuel J.},
      title = {A comparison of some conformal quantile regression methods},
      journaltitle = {Stat},
      volume = {9},
      number = {1},
      pages = {e261},
      date = {2020},
      annotation = {2019i},
      doi = {10.1002/sta4.261},
    }
    • Y. Romano
    • R. Foygel Barber
    • C. Sabatti
    • E. J. Candès
    With malice toward none: Assessing uncertainty via equalized coverage. Harvard Data Science Review. 2020. (Website & code)
    @article{EqualizedCoverage,
      author = {Romano, Yaniv and Foygel Barber, Rina and Sabatti, Chiara and Candès, Emmanuel J.},
      title = {With malice toward none: Assessing uncertainty via equalized coverage},
      journaltitle = {Harvard Data Science Review},
      volume = {2},
      number = {2},
      date = {2020-04-30},
      annotation = {2019h},
      doi = {10.1162/99608f92.03f00592},
    }
    • M. Sesia
    • E. Katsevich
    • S. Bates
    • E. J. Candès
    • C. Sabatti
    Multi-resolution localization of causal variants across the genome. Nature Communications. 2020. (Website & code)
    @article{UKBio,
      author = {Sesia, Matteo and Katsevich, Eugene and Bates, Stephen and Candès, Emmanuel J. and Sabatti, Chiara},
      title = {Multi-resolution localization of causal variants across the genome},
      journaltitle = {Nature Communications},
      volume = {11},
      number = {1},
      pages = {1093},
      date = {2020},
      annotation = {2019g},
    }
    • R. F. Barber
    • E. J. Candès
    • A. Ramdas
    • R. J. Tibshirani
    Predictive inference with the jackknife+. Annals of Statistics. 2021.
    @article{BaCaRaTi2021,
      author = {Barber, Rina Foygel and Candès, Emmanuel J. and Ramdas, Aaditya and Tibshirani, Ryan J.},
      title = {Predictive inference with the jackknife+},
      journaltitle = {Annals of Statistics},
      volume = {49},
      number = {1},
      pages = {486--507},
      date = {2021},
      annotation = {2019f},
      doi = {10.1214/20-AOS1965},
    }
    • Y. Romano
    • E. Patterson
    • E. J. Candès
    Conformalized quantile regression. Advances in neural information processing systems 32 (NIPS 2019). 2019. (Website & code)
    @inproceedings{CQR,
      author = {Romano, Yaniv and Patterson, Evan and Candès, Emmanuel J.},
      title = {Conformalized Quantile Regression},
      booktitle = {Advances in Neural Information Processing Systems 32 (NIPS 2019)},
      publisher = {Curran Associates},
      pages = {3538--3548},
      date = {2019},
      editor = {Wallach, H. and Larochelle, H. and Beygelzimer, A. and d'Alché-Buc, F. and Fox, E. and Garnett, R.},
      url = {papers.nips.cc/paper/8613-conformalized-quantile-regression},
    }
    • R. J. Tibshirani
    • R. Foygel Barber
    • E. J. Candès
    • A. Ramdas
    Conformal prediction under covariate shift. Advances in neural information processing systems 32 (NIPS 2019). 2019.
    @inproceedings{WeightedCP,
      author = {Tibshirani, Ryan J. and Foygel Barber, Rina and Candès, Emmanuel J. and Ramdas, Aaditya},
      title = {Conformal Prediction Under Covariate Shift},
      booktitle = {Advances in Neural Information Processing Systems 32 (NIPS 2019)},
      publisher = {Curran Associates},
      pages = {2526--2536},
      date = {2019},
      editor = {Wallach, H. and Larochelle, H. and Beygelzimer, A. and d'Alché-Buc, F. and Fox, E. and Garnett, R.},
      url = {papers.nips.cc/paper/8522-conformal-prediction-under-covariate-shift},
    }
    • R. Foygel Barber
    • E. J. Candès
    • A. Ramdas
    • R. J. Tibshirani
    The limits of distribution-free conditional predictive inference. Information and Inference. 2021.
    @article{ConditionalConformal,
      author = {Foygel Barber, Rina and Candès, Emmanuel J and Ramdas, Aaditya and Tibshirani, Ryan J},
      title = {The limits of distribution-free conditional predictive inference},
      journaltitle = {Information and Inference},
      volume = {10},
      number = {2},
      pages = {455--482},
      date = {2021},
      annotation = {2019c},
      doi = {10.1093/imaiai/iaaa017},
    }
    • S. Bates
    • E. J. Candès
    • L. Janson
    • W. Wang
    Metropolized knockoff sampling. Journal of the A`\-`{=latex}mer`\-`{=latex}i`\-`{=latex}can Statistical Association. 2021. (Website & code)
    @article{Metro,
      author = {Bates, Stephen and Candès, Emmanuel J. and Janson, Lucas and Wang, Wenshuo},
      title = {Metropolized knockoff sampling},
      journaltitle = {Journal of the A\-mer\-i\-can Statistical Association},
      volume = {116},
      number = {535},
      pages = {1413--1427},
      date = {2021},
      annotation = {2019b},
      doi = {10.1080/01621459.2020.1729163},
    }
    • D. A. Barmherzig
    • J. Sun
    • E. J. Candès
    • T. J. Lane
    • P. Li
    Dual-reference design for holographic phase retrieval. 2019 13th International Conference on Sampling Theory and Applications (SAMPTA). 2019.
    @inproceedings{HolographicPR-ISI,
      author = {Barmherzig, David A. and Sun, Ju and Candès, Emmanuel J. and Lane, T. J. and Li, Po-Nan},
      title = {Dual-Reference Design for Holographic Phase Retrieval},
      booktitle = {2019 13th {I}nternational {C}onference on {S}ampling {T}heory and {A}pplications ({SAMPTA})},
      publisher = {IEEE},
      date = {2019},
      isbn = {978-1-7281-3741-4},
    }
    • D. A. Barmherzig
    • J. Sun
    • E. J. Candès
    • T. J. Lane
    • P. Li
    Holographic phase retrieval and optimal reference design. Inverse Problems. 2019.
    @article{HolographicPR,
      author = {Barmherzig, D. A. and Sun, J. and Candès, E. J. and Lane, T. J. and Li, P-N.},
      title = {Holographic phase retrieval and optimal reference design},
      journaltitle = {Inverse Problems},
      volume = {35},
      number = {9},
      pages = {094001},
      date = {2019},
      sortyear = {2019a},
    }
  • 2018

    • R. Foygel Barber
    • E. J. Candès
    On the construction of knockoffs in case-control studies. Stat. 2019.
    @article{Case-Control,
      author = {Foygel Barber, Rina and Candès, Emmanuel J.},
      title = {On the construction of knockoffs in case-control studies},
      journaltitle = {Stat},
      volume = {8},
      number = {1},
      pages = {e225},
      date = {2019},
      annotation = {2018e},
    }
    • Y. Romano
    • M. Sesia
    • E. J. Candès
    Deep knockoffs. Journal of the American Statistical Association. 2020. (Website & code)
    @article{DeepKnockoffs,
      author = {Romano, Yaniv and Sesia, Matteo and Candès, Emmanuel J.},
      title = {Deep knockoffs},
      journaltitle = {Journal of the American Statistical Association},
      publisher = {Taylor & Francis},
      volume = {115},
      number = {532},
      pages = {1861--1872},
      date = {2020},
      annotation = {2018d},
      doi = {10.1080/01621459.2019.1660174},
    }
    • E. J. Candès
    • P. Sur
    The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression. Annals of Statistics. 2020.
    @article{LogisticMLE,
      author = {Candès, Emmanuel J. and Sur, Pragya},
      title = {The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression},
      journaltitle = {Annals of Statistics},
      volume = {48},
      number = {1},
      pages = {27--42},
      date = {2020},
    }
    • P. Sur
    • E. J. Candès
    A modern maximum-likelihood theory for high-dimensional logistic regression. Proceedings of the National Academy of Sciences. 2019.
    @article{LogisticAMP,
      author = {Sur, Pragya and Candès, Emmanuel J.},
      title = {A modern maximum-likelihood theory for high-dimensional logistic regression},
      journaltitle = {Proceedings of the National Academy of Sciences},
      volume = {116},
      number = {29},
      pages = {14516--14525},
      date = {2019},
      sortyear = {2018b},
    }
    • R. Foygel Barber
    • E. J. Candès
    • R. Samworth
    Robust inference with knockoffs. Annals of Statistics. 2020.
    @article{RobustKnockoffs,
      author = {Foygel Barber, Rina and Candès, Emmanuel J. and Samworth, R.},
      title = {Robust inference with knockoffs},
      journaltitle = {Annals of Statistics},
      volume = {48},
      number = {3},
      pages = {1409--1431},
      date = {2020},
      sortyear = {2018a},
    }
  • 2017

    • A. Weinstein
    • R. Foygel Barber
    • E. J. Candès
    A power analysis for knockoffs under gaussian designs. IEEE Transactions on Information Theory. In revision. 2017.
    @article{AMPKnockoffs,
      author = {Weinstein, Asaf and Foygel Barber, Rina and Candès, Emmanuel J.},
      title = {A power analysis for knockoffs under Gaussian designs},
      journaltitle = {IEEE Transactions on Information Theory},
      date = {2017},
      pubstate = {In revision},
      sortyear = {2017d},
    }
    • M. Sesia
    • C. Sabatti
    • E. J. Candès
    Rejoinder: “Gene hunting with knockoffs for hidden markov models”. Biometrika. 2019.
    @article{Rejoinder_HMM_Knockoffs,
      author = {Sesia, Matteo and Sabatti, Chiara and Candès, Emmanuel J.},
      title = {Rejoinder: ``Gene hunting with knockoffs for hidden Markov models''},
      journaltitle = {Biometrika},
      volume = {106},
      number = {1},
      pages = {35--45},
      date = {2019},
      sortyear = {2017c},
    }
    • M. Sesia
    • C. Sabatti
    • E. J. Candès
    Gene hunting with knockoffs for hidden markov models (with discussion). Biometrika. 2019. (Website & code)
    @article{HMM_Knockoffs,
      author = {Sesia, Matteo and Sabatti, Chiara and Candès, Emmanuel J.},
      title = {Gene hunting with knockoffs for hidden Markov models (with discussion)},
      journaltitle = {Biometrika},
      volume = {106},
      number = {1},
      pages = {1--18},
      date = {2019},
      sortyear = {2017b},
    }
    • P. Sur
    • Y. Chen
    • E. J. Candès
    The likelihood ratio test in high-dimensional logistic regression is asymptotically a rescaled chi-square. Probability Theory and Related Fields. 2019.
    @article{LRT_HighDim,
      author = {Sur, Pragya and Chen, Yuxin and Candès, Emmanuel J.},
      title = {The likelihood ratio test in high-dimensional logistic regression is asymptotically a {\em rescaled} chi-square},
      journaltitle = {Probability Theory and Related Fields},
      volume = {175},
      number = {1-2},
      pages = {487--558},
      date = {2019},
      sortyear = {2017a},
    }
    • E. J. Candès
    • Y. Fan
    • L. Janson
    • J. Lv
    Panning for gold: ‘Model-x’ knockoffs for high-dimensional controlled variable selection. Journal of the Royal Statistical Society Series B. 2018. (Website & code)
    @article{MX_Knockoffs,
      author = {Candès, Emmanuel J. and Fan, Yingying and Janson, Lucas and Lv, Jinchi},
      title = {Panning for gold: `Model-X' knockoffs for high-dimensional controlled variable selection},
      journaltitle = {Journal of the Royal Statistical Society Series B},
      volume = {80},
      number = {13},
      pages = {551--577},
      date = {2018},
      sortyear = {2016d},
    }
    • Y. Chen
    • E. J. Candès
    The projected power method: An efficient algorithm for joint alignment from pairwise differences. Communications on Pure and Applied Mathematics. 2018.
    @article{JointAlign,
      author = {Chen, Yuxin and Candès, Emmanuel J},
      title = {The projected power method: An efficient algorithm for joint alignment from pairwise differences},
      journaltitle = {Communications on Pure and Applied Mathematics},
      volume = {71},
      number = {8},
      pages = {1648--1714},
      date = {2018},
      sortyear = {2016c},
    }
    • D. Brzyski
    • C. B. Peterson
    • P. Sobczyk
    • E. J. Candès
    • M. Bogdan
    • C. Sabatti
    Controlling the rate of GWAS false discoveries. Genetics. 2017.
    @article{GWAS_FDR,
      author = {Brzyski, Damian and Peterson, Christine B. and Sobczyk, Piotr and Candès, Emmanuel J. and Bogdan, Malgorzata and Sabatti, Chiara},
      title = {Controlling the rate of GWAS false discoveries},
      journaltitle = {Genetics},
      volume = {205},
      number = {1},
      pages = {61--75},
      date = {2017},
      sortyear = {2016b},
    }
    • R. Foygel Barber
    • E. J. Candès
    A knockoff filter for high-dimensional selective inference. Annals of Statistics. 2019.
    @article{HD_Knockoffs,
      author = {Foygel Barber, Rina and Candès, Emmanuel J},
      title = {A knockoff filter for high-dimensional selective inference},
      journaltitle = {Annals of Statistics},
      volume = {47},
      number = {5},
      pages = {2504--2537},
      date = {2019},
      sortyear = {2016a},
    }
    • W. Su
    • M. Bogdan
    • E. J. Candès
    False discoveries occur early on the lasso path. Annals of Statistics. 2017.
    @article{LassoFDR,
      author = {Su, Weijie and Bogdan, Malgorzata and Candès, Emmanuel J},
      title = {False discoveries occur early on the lasso path},
      journaltitle = {Annals of Statistics},
      volume = {45},
      number = {5},
      pages = {2133--2150},
      date = {2017},
      sortyear = {2015f},
    }
    • Y. Chen
    • E. J. Candès
    Solving random quadratic systems of equations is nearly as easy as solving linear systems. Communications on Pure and Applied Mathematics. 2017. (Website & code)
    @article{TruncatedWF,
      author = {Chen, Yuxin and Candès, Emmanuel J},
      title = {Solving random quadratic systems of equations is nearly as easy as solving linear systems},
      journaltitle = {Communications on Pure and Applied Mathematics},
      volume = {70},
      number = {5},
      pages = {2133--2150},
      date = {2017},
      sortyear = {2015e},
    }
    • L. Janson
    • R. Foygel Barber
    • E. J. Candès
    EigenPrism: Inference for high-dimensional signal-to-noise ratios. Journal of the Royal Statistical Society Series B. 2017.
    @article{EigenPrism,
      author = {Janson, Lucas and Foygel Barber, Rina and Candès, Emmanuel J},
      title = {EigenPrism: Inference for high-dimensional signal-to-noise ratios},
      journaltitle = {Journal of the Royal Statistical Society Series B},
      volume = {79},
      number = {4},
      pages = {1037--1065},
      date = {2017},
      sortyear = {2015d},
    }
  • 2016

    • V. Morgenshtern
    • E. J. Candès
    Super-resolution of positive sources: The discrete setup. SIAM Journal on Imaging Sciences. 2016.
    @article{SuperResPositive,
      author = {Morgenshtern, Veniamin and Candès, Emmanuel J},
      title = {Super-resolution of positive sources: The discrete setup},
      journaltitle = {SIAM Journal on Imaging Sciences},
      publisher = {SIAM},
      volume = {9},
      number = {1},
      pages = {412--444},
      date = {2016},
      sortyear = {2015c},
    }
    • E. J. Candès
    • W. Su
    SLOPE is adaptive to unknown sparsity and asymptotically minimax. Annals of Statistics. 2016.
    @article{SLOPE_minimax,
      author = {Candès, Emmanuel J and Su, Weijie},
      title = {SLOPE is adaptive to unknown sparsity and asymptotically minimax},
      journaltitle = {Annals of Statistics},
      volume = {44},
      number = {3},
      pages = {1038--1068},
      date = {2016},
      sortyear = {2015b},
    }
    • W. Su
    • S. Boyd
    • E. J. Candès
    A differential equation for modeling nesterov’s accelerated gradient method: Theory and insights. Journal of Machine Learning Research. 2016.
    @article{NesterovODE,
      author = {Su, Weijie and Boyd, Stephen and Candès, Emmanuel J},
      title = {A differential equation for modeling Nesterov's accelerated gradient method: Theory and insights},
      journaltitle = {Journal of Machine Learning Research},
      volume = {17},
      number = {153},
      pages = {1--43},
      date = {2016},
      sortyear = {2015a},
    }
  • 2014

    • W. Su
    • S. Boyd
    • E. J. Candès
    A differential equation for modeling nesterov’s accelerated gradient method: Theory and insights. Advances in neural information processing systems 27 (NIPS 2014). 2014.
    @inproceedings{NIPS2014,
      author = {Su, Weijie and Boyd, Stephen and Candès, Emmanuel J},
      title = {A differential equation for modeling Nesterov's accelerated gradient method: Theory and insights},
      booktitle = {Advances in Neural Information Processing Systems 27 (NIPS 2014)},
      pages = {2510--2518},
      date = {2014},
      sortyear = {2014e},
    }
    • E. J. Candès
    Mathematics of sparsity (and a few other things). Proceedings of the international congress of mathematicians. 2014.
    @inproceedings{ICM2014,
      author = {Candès, Emmanuel J},
      title = {Mathematics of sparsity (and a few other things)},
      booktitle = {Proceedings of the International Congress of Mathematicians},
      date = {2014},
      location = {Seoul, South Korea},
      sortyear = {2014d},
    }
    • E. J. Candès
    • X. Li
    • M. Soltanolkotabi
    Phase retrieval via wirtinger flow: Theory and algorithms. IEEE Transactions on Information Theory. 2015. (Website & code)
    @article{WirtingerFlow,
      author = {Candès, Emmanuel J and Li, Xiaodong and Soltanolkotabi, Mahdi},
      title = {Phase retrieval via Wirtinger flow: Theory and algorithms},
      journaltitle = {IEEE Transactions on Information Theory},
      publisher = {IEEE},
      volume = {61},
      number = {4},
      pages = {1985--2007},
      date = {2015},
      sortyear = {2014c},
    }
    • M. Bogdan
    • E. Berg
    • C. Sabatti
    • W. Su
    • E. J. Candès
    SLOPE – adaptive variable selection via convex optimization. Annals of Applied Statistics. 2015. (Website & code)
    @article{SLOPE,
      author = {Bogdan, Malgorzata and van den Berg, Ewout and Sabatti, Chiara and Su, Weijie and Candès, Emmanuel J},
      title = {SLOPE -- Adaptive variable selection via convex optimization},
      journaltitle = {Annals of Applied Statistics},
      publisher = {Institute of Mathematical Statistics},
      volume = {9},
      number = {3},
      pages = {1103--1140},
      date = {2015},
      sortyear = {2014b},
    }
    • R. Foygel Barber
    • E. J. Candès
    Controlling the false discovery rate via knockoffs. Annals of Statistics. 2015. (Website & code)
    @article{FDR_regression,
      author = {Foygel Barber, Rina and Candès, Emmanuel J},
      title = {Controlling the false discovery rate via knockoffs},
      journaltitle = {Annals of Statistics},
      publisher = {Institute of Mathematical Statistics},
      volume = {43},
      number = {5},
      pages = {2055--2085},
      date = {2015},
      sortyear = {2014a},
    }
  • 2013

    • C. Fernandez-Granda
    • E. J. Candès
    Super-resolution via transform-invariant group-sparse regularization. Proceedings of the IEEE international conference on computer vision (ICCV). 2013.
    @inproceedings{TI_DTV_superres,
      author = {Fernandez-Granda, Carlos and Candès, Emmanuel J},
      title = {Super-resolution via transform-invariant group-sparse regularization},
      booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
      organization = {IEEE},
      date = {2013},
      sortyear = {2013f},
    }
    • E. J. Candès
    • X. Li
    • M. Soltanolkotabi
    Phase retrieval from coded diffraction patterns. Applied and Computational Harmonic Analysis. 2014.
    @article{PhaseLift_CDP,
      author = {Candès, Emmanuel J and Li, Xiaodong and Soltanolkotabi, Mahdi},
      title = {Phase retrieval from coded diffraction patterns},
      journaltitle = {Applied and Computational Harmonic Analysis},
      publisher = {Elsevier},
      volume = {39},
      number = {2},
      pages = {277--299},
      date = {2014},
      sortyear = {2013e},
    }
    • M. Bogdan
    • E. v. d. Berg
    • W. Su
    • E. J. Candès
    Statistical estimation and testing via the sorted L1 norm. 2013.
    @article{SortedL1,
      author = {Bogdan, Malgorzata and Berg, Ewout van den and Su, Weijie and Candès, Emmanuel J},
      title = {Statistical estimation and testing via the sorted L1 norm},
      date = {2013},
      eprint = {1310.1969},
      eprinttype = {arXiv},
      sortyear = {2013d},
    }
    • R. Witten
    • E. Candès
    Randomized algorithms for low-rank matrix factorizations: Sharp performance bounds. Algorithmica. 2013.
    @article{RandomizedNLA,
      author = {Witten, Rafi and Candès, Emmanuel},
      title = {Randomized algorithms for low-rank matrix factorizations: Sharp performance bounds},
      journaltitle = {Algorithmica},
      publisher = {Springer},
      volume = {72},
      number = {1},
      pages = {264--281},
      date = {2013},
      sortyear = {2013c},
    }
    • R. Otazo
    • E. Candès
    • D. Sodickson
    Low-rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components. Magnetic Resonance in Medicine. 2015.
    @article{L+S-MRI,
      author = {Otazo, Ricardo and Candès, Emmanuel and Sodickson, Daniel},
      title = {Low-rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components},
      journaltitle = {Magnetic Resonance in Medicine},
      volume = {73},
      number = {3},
      pages = {1125--1136},
      date = {2015},
      sortyear = {2013b},
    }
    • M. Soltanolkotabi
    • E. Elhamifar
    • E. J. Candès
    Robust subspace clustering. Annals of Statistics. 2014.
    @article{RobustSubspaceClustering,
      author = {Soltanolkotabi, Mahdi and Elhamifar, Ehsan and Candès, Emmanuel J},
      title = {Robust subspace clustering},
      journaltitle = {Annals of Statistics},
      publisher = {Institute of Mathematical Statistics},
      volume = {42},
      number = {2},
      pages = {669--699},
      date = {2014},
      sortyear = {2013a},
    }
    • E. J. Candès
    • C. Fernandez-Granda
    Super-resolution from noisy data. Journal of Fourier Analysis and Applications. 2013.
    @article{robust_SR,
      author = {Candès, Emmanuel J and Fernandez-Granda, Carlos},
      title = {Super-resolution from noisy data},
      journaltitle = {Journal of Fourier Analysis and Applications},
      publisher = {Springer},
      volume = {19},
      number = {6},
      pages = {1229--1254},
      date = {2013},
      sortyear = {2012i},
    }
    • E. J. Candès
    • C. Sing-Long
    • J. D. Trzasko
    • et al
    Unbiased risk estimates for singular value thresholding and spectral estimators. IEEE Transactions on Signal Processing. 2013. (Website & code)
    @article{SURE_SVT,
      author = {Candès, Emmanuel J and Sing-Long, Carlos and Trzasko, Joshua D and others},
      title = {Unbiased risk estimates for singular value thresholding and spectral estimators},
      journaltitle = {IEEE Transactions on Signal Processing},
      publisher = {IEEE},
      volume = {61},
      number = {19},
      pages = {4643--4657},
      date = {2013},
      sortyear = {2012h},
    }
    • E. Van Den Berg
    • E. Candès
    • G. Chinn
    • C. Levin
    • P. D. Olcott
    • C. Sing-Long
    Single-photon sampling architecture for solid-state imaging sensors. Proceedings of the National Academy of Sciences. 2013.
    @article{GroupTesting,
      author = {Van Den Berg, Ewout and Candès, Emmanuel and Chinn, Garry and Levin, Craig and Olcott, Peter Demetri and Sing-Long, Carlos},
      title = {Single-photon sampling architecture for solid-state imaging sensors},
      journaltitle = {Proceedings of the National Academy of Sciences},
      publisher = {National Acad Sciences},
      volume = {110},
      number = {30},
      pages = {E2752--E2761},
      date = {2013},
      sortyear = {2012g},
    }
    • E. J. Candès
    • X. Li
    Solving quadratic equations via PhaseLift when there are about as many equations as unknowns. Foundations of Computational Mathematics. 2014.
    @article{ImprovedPL,
      author = {Candès, Emmanuel J and Li, Xiaodong},
      title = {Solving quadratic equations via PhaseLift when there are about as many equations as unknowns},
      journaltitle = {Foundations of Computational Mathematics},
      publisher = {Springer},
      volume = {14},
      number = {5},
      pages = {1017--1026},
      date = {2014},
      sortyear = {2012f},
    }
  • 2012

    • E. J. Candès
    • M. Soltanolkotabi
    Discussion of ’latent variable graphical model selection via convex optimization'. Annals of Statistics. 2012.
    @article{LatentVariables,
      author = {Candès, Emmanuel J and Soltanolkotabi, Mahdi},
      title = {Discussion of `Latent variable graphical model selection via convex optimization'},
      journaltitle = {Annals of Statistics},
      publisher = {Institute of Mathematical Statistics},
      volume = {40},
      number = {4},
      pages = {1997--2004},
      date = {2012},
      sortyear = {2012e},
    }
    • B. O'Donoghue
    • E. Candès
    Adaptive restart for accelerated gradient schemes. Foundations of Computational Mathematics. 2013.
    @article{adap_restart_paper,
      author = {O’Donoghue, Brendan and Candès, Emmanuel},
      title = {Adaptive restart for accelerated gradient schemes},
      journaltitle = {Foundations of Computational Mathematics},
      publisher = {Springer},
      volume = {15},
      number = {3},
      pages = {715--732},
      date = {2013},
      sortyear = {2012d},
    }
    • E. J. Candès
    • C. Fernandez-Granda
    Towards a mathematical theory of super-resolution. Communications on Pure and Applied Mathematics. 2014.
    @article{super-res,
      author = {Candès, Emmanuel J and Fernandez-Granda, Carlos},
      title = {Towards a mathematical theory of super-resolution},
      journaltitle = {Communications on Pure and Applied Mathematics},
      volume = {67},
      number = {6},
      pages = {906--956},
      date = {2014},
      sortyear = {2012c},
    }
    • J. Yoo
    • C. Turnes
    • E. Nakamura
    • C. Le
    • S. Becker
    • E. Sovero
    • M. Wakin
    • M. Grant
    • J. Romberg
    • A. Emami-Neyestanak
    • E. J. Candès
    A compressed sensing parameter extraction platform for radar pulse signal acquisition. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2012.
    @article{RMPI_20120630,
      author = {Yoo, Juhwan and Turnes, Christopher and Nakamura, Eric and Le, Chi and Becker, Stephen and Sovero, Emilio and Wakin, Michael and Grant, Michael and Romberg, Justin and Emami-Neyestanak, Azita and Candès, Emmanuel J},
      title = {A compressed sensing parameter extraction platform for radar pulse signal acquisition},
      journaltitle = {IEEE Journal on Emerging and Selected Topics in Circuits and Systems},
      publisher = {IEEE},
      volume = {2},
      number = {3},
      pages = {626--638},
      date = {2012},
      sortyear = {2012b},
    }
    • M. Wakin
    • S. Becker
    • E. Nakamura
    • M. Grant
    • E. Sovero
    • D. Ching
    • J. Yoo
    • J. Romberg
    • A. Emami-Neyestanak
    • E. Candès
    A nonuniform sampler for wideband spectrally-sparse environments. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2012.
    @article{NUS_20120628,
      author = {Wakin, Michael and Becker, Stephen and Nakamura, Eric and Grant, Michael and Sovero, Emilio and Ching, Daniel and Yoo, Juhwan and Romberg, Justin and Emami-Neyestanak, Azita and Candès, Emmanuel},
      title = {A nonuniform sampler for wideband spectrally-sparse environments},
      journaltitle = {IEEE Journal on Emerging and Selected Topics in Circuits and Systems},
      publisher = {IEEE},
      volume = {2},
      number = {3},
      pages = {516--529},
      date = {2012},
      sortyear = {2012a},
    }
    • M. Soltanolkotabi
    • E. J. Candès
    A geometric analysis of subspace clustering with outliers. Annals of Statistics. 2012.
    @article{SubspaceClustering,
      author = {Soltanolkotabi, Mahdi and Candès, Emmanuel J},
      title = {A geometric analysis of subspace clustering with outliers},
      journaltitle = {Annals of Statistics},
      publisher = {Institute of Mathematical Statistics},
      volume = {40},
      number = {4},
      pages = {2195--2238},
      date = {2012},
      sortyear = {2011g},
    }
    • V. Studer
    • J. Bobin
    • M. Chahid
    • H. S. Mousavi
    • E. Candès
    • M. Dahan
    Compressive fluorescence microscopy for biological and hyperspectral imaging. Proceedings of the National Academy of Sciences. 2012.
    @article{CFM,
      author = {Studer, Vincent and Bobin, Jérome and Chahid, Makhlad and Mousavi, Hamed Shams and Candès, Emmanuel and Dahan, Maxime},
      title = {Compressive fluorescence microscopy for biological and hyperspectral imaging},
      journaltitle = {Proceedings of the National Academy of Sciences},
      publisher = {National Acad Sciences},
      volume = {109},
      number = {26},
      pages = {E1679--E1687},
      date = {2012},
      sortyear = {2011f},
    }
    • E. Arias-Castro
    • E. J. Candès
    • M. Davenport
    • et al
    On the fundamental limits of adaptive sensing. IEEE Transactions on Information Theory. 2013.
    @article{adaptive,
      author = {Arias-Castro, Ery and Candès, Emmanuel J and Davenport, Mark and others},
      title = {On the fundamental limits of adaptive sensing},
      journaltitle = {IEEE Transactions on Information Theory},
      publisher = {IEEE},
      volume = {59},
      number = {1},
      pages = {472--481},
      date = {2013},
      sortyear = {2011e},
    }
    • E. J. Candès
    • T. Strohmer
    • V. Voroninski
    PhaseLift: Exact and stable signal recovery from magnitude measurements via convex programming. Communications on Pure and Applied Mathematics. 2013.
    @article{ExactPR,
      author = {Candès, Emmanuel J and Strohmer, Thomas and Voroninski, Vladislav},
      title = {PhaseLift: Exact and stable signal recovery from magnitude measurements via convex programming},
      journaltitle = {Communications on Pure and Applied Mathematics},
      volume = {66},
      number = {8},
      pages = {1241--1274},
      date = {2013},
      sortyear = {2011d},
    }
    • E. J. Candès
    • Y. C. Eldar
    • T. Strohmer
    • V. Voroninski
    Phase retrieval via matrix completion. SIAM Journal on Imaging Sciences. 2013.
    @article{PhaseRetrieval,
      author = {Candès, Emmanuel J and Eldar, Yonina C and Strohmer, Thomas and Voroninski, Vladislav},
      title = {Phase retrieval via matrix completion},
      journaltitle = {SIAM Journal on Imaging Sciences},
      publisher = {SIAM},
      volume = {6},
      number = {1},
      pages = {199--225},
      date = {2013},
      sortyear = {2011c},
    }
    • E. Candès
    • B. Recht
    Simple bounds for recovering low-complexity models. Mathematical Programming. 2013.
    @article{dual_multiplier,
      author = {Candès, Emmanuel and Recht, Benjamin},
      title = {Simple bounds for recovering low-complexity models},
      journaltitle = {Mathematical Programming},
      publisher = {Springer},
      volume = {141},
      number = {1-2},
      pages = {577--589},
      date = {2013},
      sortyear = {2011b},
    }
    • E. J. Candès
    • M. A. Davenport
    How well can we estimate a sparse vector?. Applied and Computational Harmonic Analysis. 2013.
    @article{HowWell,
      author = {Candès, Emmanuel J and Davenport, Mark A},
      title = {How well can we estimate a sparse vector?},
      journaltitle = {Applied and Computational Harmonic Analysis},
      publisher = {Elsevier},
      volume = {34},
      number = {2},
      pages = {317--323},
      date = {2013},
      sortyear = {2011a},
    }
  • 2011

    • E. J. Candès
    • Y. Plan
    A probabilistic and RIPless theory of compressed sensing. IEEE Transactions on Information Theory. 2011.
    @article{IncoherenceCS,
      author = {Candès, Emmanuel J and Plan, Yaniv},
      title = {A probabilistic and RIPless theory of compressed sensing},
      journaltitle = {IEEE Transactions on Information Theory},
      publisher = {IEEE},
      volume = {57},
      number = {11},
      pages = {7235--7254},
      date = {2011},
      sortyear = {2010g},
    }
    • S. Becker
    • E. J. Candès
    • M. Grant
    Templates for convex cone problems with applications to sparse signal recovery. Mathematical Programming Computation. 2011. (Website & code)
    @article{TFOCS,
      author = {Becker, Stephen and Candès, Emmanuel J and Grant, Michael},
      title = {Templates for convex cone problems with applications to sparse signal recovery},
      journaltitle = {Mathematical Programming Computation},
      publisher = {Springer},
      volume = {3},
      number = {3},
      pages = {165--218},
      date = {2011},
      sortyear = {2010f},
    }
    • E. Arias-Castro
    • E. J. Candès
    • Y. Plan
    Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism. Annals of Statistics. 2011.
    @article{GlobalTesting,
      author = {Arias-Castro, Ery and Candès, Emmanuel J and Plan, Yaniv},
      title = {Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism},
      journaltitle = {Annals of Statistics},
      volume = {39},
      number = {5},
      pages = {2533--2556},
      date = {2011},
      sortyear = {2010e},
    }
    • E. J. Candès
    • Y. C. Eldar
    • D. Needell
    • P. Randall
    Compressed sensing with coherent and redundant dictionaries. Applied and Computational Harmonic Analysis. 2011.
    @article{CoherentCS,
      author = {Candès, Emmanuel J and Eldar, Yonina C and Needell, Deanna and Randall, Paige},
      title = {Compressed sensing with coherent and redundant dictionaries},
      journaltitle = {Applied and Computational Harmonic Analysis},
      publisher = {Elsevier},
      volume = {31},
      number = {1},
      pages = {59--73},
      date = {2011},
      sortyear = {2010d},
    }
  • 2010

    • Z. Zhou
    • X. Li
    • J. Wright
    • E. Candès
    • Y. Ma
    Stable principal component pursuit. Proceedings of international symposium on information theory. 2010.
    @inproceedings{StableRPCA,
      author = {Zhou, Zihan and Li, Xiaodong and Wright, John and Candès, Emmanuel and Ma, Yi},
      title = {Stable principal component pursuit},
      booktitle = {Proceedings of International Symposium on Information Theory},
      organization = {IEEE},
      pages = {1518--1522},
      date = {2010},
      sortyear = {2010c},
    }
    • A. Ganesh
    • J. Wright
    • X. Li
    • E. J. Candès
    • Y. Ma
    Dense error correction for low-rank matrices via principal component pursuit. Proceedings of international symposium on information theory. 2010.
    @inproceedings{DenseRPCA,
      author = {Ganesh, Arvind and Wright, John and Li, Xiaodong and Candès, Emmanuel J and Ma, Yi},
      title = {Dense error correction for low-rank matrices via principal component pursuit},
      booktitle = {Proceedings of International Symposium on Information Theory},
      organization = {IEEE},
      pages = {1513--1517},
      date = {2010},
      sortyear = {2010b},
    }
    • E. Arias-Castro
    • E. J. Candès
    • A. Durand
    Detection of an anomalous cluster in a network. Annals of Statistics. 2011.
    @article{ClusterDetect,
      author = {Arias-Castro, Ery and Candès, Emmanuel J and Durand, Arnaud},
      title = {Detection of an anomalous cluster in a network},
      journaltitle = {Annals of Statistics},
      volume = {39},
      number = {1},
      pages = {278--304},
      date = {2011},
      sortyear = {2010a},
    }
    • E. J. Candès
    • X. Li
    • Y. Ma
    • J. Wright
    Robust principal component analysis?. Journal of the ACM. 2011.
    @article{RobustPCA,
      author = {Candès, Emmanuel J and Li, Xiaodong and Ma, Yi and Wright, John},
      title = {Robust principal component analysis?},
      journaltitle = {Journal of the ACM},
      publisher = {ACM},
      volume = {58},
      number = {3},
      pages = {11},
      date = {2011},
      sortyear = {2009f},
    }
    • E. J. Candès
    • Y. Plan
    Tight oracle inequalities for low-rank matrix recovery from a minimal number of noisy random measurements. IEEE Transactions on Information Theory. 2011.
    @article{MatrixOracle,
      author = {Candès, Emmanuel J and Plan, Yaniv},
      title = {Tight oracle inequalities for low-rank matrix recovery from a minimal number of noisy random measurements},
      journaltitle = {IEEE Transactions on Information Theory},
      publisher = {IEEE},
      volume = {57},
      number = {4},
      pages = {2342--2359},
      date = {2011},
      sortyear = {2009e},
    }
    • A. Zymnis
    • S. Boyd
    • E. Candès
    Compressed sensing with quantized measurements. Signal Processing Letters. 2010.
    @article{quant_compr_sens,
      author = {Zymnis, Argyrios and Boyd, Stephen and Candès, Emmanuel},
      title = {Compressed sensing with quantized measurements},
      journaltitle = {Signal Processing Letters},
      publisher = {IEEE},
      volume = {17},
      number = {2},
      pages = {149--152},
      date = {2010},
      sortyear = {2009d},
    }
    • S. Becker
    • J. Bobin
    • E. J. Candès
    NESTA: A fast and accurate first-order method for sparse recovery. SIAM Journal on Imaging Sciences. 2011. (Website & code)
    @article{NESTA,
      author = {Becker, Stephen and Bobin, Jérôme and Candès, Emmanuel J},
      title = {NESTA: A fast and accurate first-order method for sparse recovery},
      journaltitle = {SIAM Journal on Imaging Sciences},
      publisher = {SIAM},
      volume = {4},
      number = {1},
      pages = {1--39},
      date = {2011},
      sortyear = {2009c},
    }
    • E. J. Candès
    • Y. Plan
    Matrix completion with noise. Proceedings of the IEEE. 2010.
    @article{NoisyCompletion,
      author = {Candès, Emmanuel J and Plan, Yaniv},
      title = {Matrix completion with noise},
      journaltitle = {Proceedings of the IEEE},
      publisher = {IEEE},
      volume = {98},
      number = {6},
      pages = {925--936},
      date = {2010},
      sortyear = {2009b},
    }
    • E. J. Candès
    • T. Tao
    The power of convex relaxation: Near-optimal matrix completion. IEEE Transactions on Information Theory. 2010.
    @article{OptimalCompletion,
      author = {Candès, Emmanuel J and Tao, Terence},
      title = {The power of convex relaxation: Near-optimal matrix completion},
      journaltitle = {IEEE Transactions on Information Theory},
      publisher = {IEEE},
      volume = {56},
      number = {5},
      pages = {2053--2080},
      date = {2010},
      sortyear = {2009a},
    }
  • 2008

    • E. J. Candès
    • T. Tao
    Reflections on compressed sensing. IEEE Information Theory Society Newsletter. 2008.
    @article{itNL1208,
      author = {Candès, Emmanuel J and Tao, Terence},
      title = {Reflections on compressed sensing},
      journaltitle = {IEEE Information Theory Society Newsletter},
      volume = {58},
      number = {4},
      pages = {14--17},
      date = {2008},
      sortyear = {2008e},
    }
    • J. Cai
    • E. J. Candès
    • Z. Shen
    A singular value thresholding algorithm for matrix completion. SIAM Journal on Optimization. 2010. (Website & code)
    @article{SVT,
      author = {Cai, Jian-Feng and Candès, Emmanuel J and Shen, Zuowei},
      title = {A singular value thresholding algorithm for matrix completion},
      journaltitle = {SIAM Journal on Optimization},
      publisher = {SIAM},
      volume = {20},
      number = {4},
      pages = {1956--1982},
      date = {2010},
      sortyear = {2008d},
    }
    • E. Candès
    • L. Demanet
    • L. Ying
    A fast butterfly algorithm for the computation of fourier integral operators. Multiscale Modeling & Simulation. 2009.
    @article{ButterflyFIO,
      author = {Candès, Emmanuel and Demanet, Laurent and Ying, Lexing},
      title = {A fast butterfly algorithm for the computation of Fourier integral operators},
      journaltitle = {Multiscale Modeling \& Simulation},
      publisher = {SIAM},
      volume = {7},
      number = {4},
      pages = {1727--1750},
      date = {2009},
      sortyear = {2008c},
    }
    • E. J. Candès
    • B. Recht
    Exact matrix completion via convex optimization. Foundations of Computational Mathematics. 2009.
    @article{MatrixCompletion,
      author = {Candès, Emmanuel J and Recht, Benjamin},
      title = {Exact matrix completion via convex optimization},
      journaltitle = {Foundations of Computational Mathematics},
      publisher = {Springer},
      volume = {9},
      number = {6},
      pages = {717--772},
      date = {2009},
      sortyear = {2008b},
    }
    • E. J. Candès
    The restricted isometry property and its implications for compressed sensing. Comptes Rendus Mathematique. 2008.
    @article{RIP,
      author = {Candès, Emmanuel J},
      title = {The restricted isometry property and its implications for compressed sensing},
      journaltitle = {Comptes Rendus Mathematique},
      publisher = {Elsevier},
      volume = {346},
      number = {9},
      pages = {589--592},
      date = {2008},
      sortyear = {2008a},
    }
    • E. J. Candès
    • Y. Plan
    Near-ideal model selection by $\ell_1$ minimization. Annals of Statistics. 2009.
    @article{LassoPredict,
      author = {Candès, Emmanuel J and Plan, Yaniv},
      title = {Near-ideal model selection by $\ell_1$ minimization},
      journaltitle = {Annals of Statistics},
      publisher = {Institute of Mathematical Statistics},
      volume = {37},
      number = {5A},
      pages = {2145--2177},
      date = {2009},
      sortyear = {2007e},
    }
    • E. J. Candès
    • M. B. Wakin
    • S. P. Boyd
    Enhancing sparsity by reweighted $\ell_1$ minimization. Journal of Fourier Analysis and Applications. 2008.
    @article{rwl1,
      author = {Candès, Emmanuel J and Wakin, Michael B and Boyd, Stephen P},
      title = {Enhancing sparsity by reweighted $\ell_1$ minimization},
      journaltitle = {Journal of Fourier Analysis and Applications},
      publisher = {Springer},
      volume = {14},
      number = {5-6},
      pages = {877--905},
      date = {2008},
      sortyear = {2007d},
    }
    • E. J. Candès
    • M. B. Wakin
    An introduction to compressive sampling. Signal Processing Magazine. 2008.
    @article{spm-robustcs-v05,
      author = {Candès, Emmanuel J and Wakin, Michael B},
      title = {An introduction to compressive sampling},
      journaltitle = {Signal Processing Magazine},
      publisher = {IEEE},
      volume = {25},
      number = {2},
      pages = {21--30},
      date = {2008},
      sortyear = {2007c},
    }
  • 2007

    • E. J. Candès
    • T. Tao
    Rejoinder: ‘The dantzig selector: Statistical estimation when $p$ is much larger than $n$’. Annals of Statistics. 2007.
    @article{rejoinder,
      author = {Candès, Emmanuel J and Tao, Terence},
      title = {Rejoinder: `The Dantzig selector: Statistical estimation when $p$ is much larger than $n$'},
      journaltitle = {Annals of Statistics},
      volume = {35},
      number = {6},
      pages = {2392--2404},
      date = {2007},
      sortyear = {2007b},
    }
    • E. Arias-Castro
    • E. J. Candès
    • H. Helgason
    • O. Zeitouni
    Searching for a trail of evidence in a maze. Annals of Statistics. 2008.
    @article{PathDetect,
      author = {Arias-Castro, Ery and Candès, Emmanuel J and Helgason, Hannes and Zeitouni, Ofer},
      title = {Searching for a trail of evidence in a maze},
      journaltitle = {Annals of Statistics},
      volume = {36},
      number = {4},
      pages = {1726--1757},
      date = {2008},
      sortyear = {2007a},
    }
    • E. J. Candès
    • P. Randall
    Highly robust error correction by convex programming. IEEE Trans`\-`{=latex}ac`\-`{=latex}tions on Information Theory. 2008.
    @article{GrossErrorsSmallErrors,
      author = {Candès, Emmanuel J and Randall, Paige},
      title = {Highly robust error correction by convex programming},
      journaltitle = {IEEE Trans\-ac\-tions on Information Theory},
      publisher = {IEEE},
      volume = {54},
      number = {7},
      pages = {2829--2840},
      date = {2008},
      sortyear = {2006f},
    }
    • E. J. Candès
    • J. Romberg
    Sparsity and incoherence in compressive sampling. Inverse Problems. 2007.
    @article{PartialMeasurements,
      author = {Candès, Emmanuel J and Romberg, Justin},
      title = {Sparsity and incoherence in compressive sampling},
      journaltitle = {Inverse Problems},
      publisher = {IOP Publishing},
      volume = {23},
      number = {3},
      pages = {969},
      date = {2007},
      sortyear = {2006e},
    }
    • E. J. Candès
    • L. Demanet
    • L. Ying
    Fast computation of fourier integral operators. SIAM Journal on Scientific Computing. 2007.
    @article{FastFIO,
      author = {Candès, Emmanuel J and Demanet, Laurent and Ying, Lexing},
      title = {Fast computation of Fourier integral operators},
      journaltitle = {SIAM Journal on Scientific Computing},
      publisher = {SIAM},
      volume = {29},
      number = {6},
      pages = {2464--2493},
      date = {2007},
      sortyear = {2006d},
    }
  • 2006

    • E. J. Candès
    Compressive sampling. Proceedings of the international congress of mathematicians. 2006.
    @inproceedings{CompressiveSampling,
      author = {Candès, Emmanuel J},
      title = {Compressive sampling},
      booktitle = {Proceedings of the International Congress of Mathematicians},
      volume = {3},
      pages = {1433--1452},
      date = {2006},
      location = {Madrid, Spain},
      sortyear = {2006c},
    }
    • E. J. Candès
    • P. R. Charlton
    • H. Helgason
    Detecting highly oscillatory signals by chirplet path pursuit. Applied and Computational Harmonic Analysis. 2008.
    @article{ChirpDetection,
      author = {Candès, Emmanuel J and Charlton, Philip R and Helgason, Hannes},
      title = {Detecting highly oscillatory signals by chirplet path pursuit},
      journaltitle = {Applied and Computational Harmonic Analysis},
      publisher = {Elsevier},
      volume = {24},
      number = {1},
      pages = {14--40},
      date = {2008},
      sortyear = {2006b},
    }
    • E. J. Candès
    • L. Ying
    Fast geodesics computation with the phase flow method. Journal of Computational Physics. 2006.
    @article{GeodesicFlow,
      author = {Candès, Emmanuel J and Ying, Lexing},
      title = {Fast geodesics computation with the phase flow method},
      journaltitle = {Journal of Computational Physics},
      publisher = {Elsevier},
      volume = {220},
      number = {1},
      pages = {6--18},
      date = {2006},
      sortyear = {2006a},
    }
    • E. J. Candès
    Modern statistical estimation via oracle inequalities. Acta Numerica. 2006.
    @article{NonlinearEstimation,
      author = {Candès, Emmanuel J},
      title = {Modern statistical estimation via oracle inequalities},
      journaltitle = {Acta Numerica},
      publisher = {Cambridge University Press},
      volume = {15},
      pages = {257--325},
      date = {2006},
      sortyear = {2005f},
    }
    • E. J. Candès
    • L. Ying
    The phase flow method. Journal of Computational Physics. 2006.
    @article{PhaseFlow,
      author = {Candès, Emmanuel J and Ying, Lexing},
      title = {The phase flow method},
      journaltitle = {Journal of Computational Physics},
      publisher = {Elsevier},
      volume = {220},
      number = {1},
      pages = {184--215},
      date = {2006},
      sortyear = {2005e},
    }
    • E. J. Candès
    • L. Demanet
    • D. Donoho
    • L. Ying
    Fast discrete curvelet transforms. Multiscale Modeling & Simulation. 2006. (Website & code)
    @article{FDCT,
      author = {Candès, Emmanuel J and Demanet, Laurent and Donoho, David and Ying, Lexing},
      title = {Fast discrete curvelet transforms},
      journaltitle = {Multiscale Modeling \& Simulation},
      publisher = {SIAM},
      volume = {5},
      number = {3},
      pages = {861--899},
      date = {2006},
      sortyear = {2005d},
    }
    • E. J. Candès
    • T. Tao
    The dantzig selector: Statistical estimation when $p$ is much larger than $n$. Annals of Statistics. 2007.
    @article{DantzigSelector,
      author = {Candès, Emmanuel J and Tao, Terence},
      title = {The Dantzig selector: Statistical estimation when $p$ is much larger than $n$},
      journaltitle = {Annals of Statistics},
      volume = {35},
      number = {6},
      pages = {2313--2351},
      date = {2007},
      sortyear = {2005c},
    }
  • 2005

    • E. J. Candès
    • M. Rudelson
    • T. Tao
    • R. Vershynin
    Error correction via linear programming. Proceedings of the 46th annual IEEE symposium on foundations of computer science (FOCS). 2005.
    @inproceedings{FOCS05,
      author = {Candès, Emmanuel J and Rudelson, Mark and Tao, Terence and Vershynin, Roman},
      title = {Error correction via linear programming},
      booktitle = {Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS)},
      organization = {IEEE},
      pages = {295--308},
      date = {2005},
      sortyear = {2005b},
    }
    • E. J. Candès
    • J. Romberg
    • T. Tao
    Stable signal recovery from incomplete and inaccurate meas\-{=latex}ure\-{=latex}ments. Communications on Pure and Applied Mathematics. 2006.
    @article{StableRecovery,
      author = {Candès, Emmanuel J and Romberg, Justin and Tao, Terence},
      title = {Stable signal recovery from incomplete and inaccurate meas\-ure\-ments},
      journaltitle = {Communications on Pure and Applied Mathematics},
      volume = {59},
      number = {8},
      pages = {1207--1223},
      date = {2006},
      sortyear = {2005a},
    }
    • E. J. Candès
    • T. Tao
    Decoding by linear programming. IEEE Transactions on Information Theory. 2005.
    @article{DecodingLP,
      author = {Candès, Emmanuel J and Tao, Terence},
      title = {Decoding by linear programming},
      journaltitle = {IEEE Transactions on Information Theory},
      volume = {51},
      number = {12},
      pages = {4203--4215},
      date = {2005},
      sortyear = {2004f},
    }
    • E. J. Candès
    • J. Romberg
    Practical signal recovery from random projections. Wavelet applications in signal and image processing XI. 2005.
    @inproceedings{PracticalRecovery,
      author = {Candès, Emmanuel J and Romberg, Justin},
      title = {Practical signal recovery from random projections},
      booktitle = {Wavelet Applications in Signal and Image Processing XI},
      volume = {5914},
      date = {2005},
      series = {Proc. SPIE},
      sortyear = {2004e},
    }
    • E. J. Candès
    • T. Tao
    Near-optimal signal recovery from random projections: Universal encoding strategies?. IEEE Transactions on Information Theory. 2006.
    @article{OptimalRecovery,
      author = {Candès, Emmanuel J and Tao, Terence},
      title = {Near-optimal signal recovery from random projections: Universal encoding strategies?},
      journaltitle = {IEEE Transactions on Information Theory},
      volume = {52},
      number = {12},
      pages = {5406--5425},
      date = {2006},
      sortyear = {2004d},
    }
    • E. J. Candès
    • J. Romberg
    Quantitative robust uncertainty principles and optimally sparse decompositions. Foundations of Computational Mathematics. 2006.
    @article{RandomBasisPursuit,
      author = {Candès, Emmanuel J and Romberg, Justin},
      title = {Quantitative robust uncertainty principles and optimally sparse decompositions},
      journaltitle = {Foundations of Computational Mathematics},
      publisher = {Springer},
      volume = {6},
      number = {2},
      pages = {227--254},
      date = {2006},
      sortyear = {2004c},
    }
    • E. J. Candès
    • J. Romberg
    • T. Tao
    Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory. 2006. (Website & code)
    @article{ExactRecovery,
      author = {Candès, Emmanuel J and Romberg, Justin and Tao, Terence},
      title = {Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information},
      journaltitle = {IEEE Transactions on Information Theory},
      volume = {52},
      number = {2},
      pages = {489--509},
      date = {2006},
      sortyear = {2004b},
    }
    • E. J. Candès
    • L. Demanet
    The curvelet representation of wave propagators is optimally sparse. Communications on Pure and Applied Mathematics. 2005.
    @article{CurveletsWaves,
      author = {Candès, Emmanuel J and Demanet, Laurent},
      title = {The curvelet representation of wave propagators is optimally sparse},
      journaltitle = {Communications on Pure and Applied Mathematics},
      volume = {58},
      number = {11},
      pages = {1472--1528},
      date = {2005},
      sortyear = {2004a},
    }
    • E. J. Candès
    • D. L. Donoho
    Continuous curvelet transform: I. Resolution of the wavefront set. Applied and Computational Harmonic Analysis. 2005.
    @article{ContCurveletTransform-I,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Continuous curvelet transform: I.\ Resolution of the wavefront set},
      journaltitle = {Applied and Computational Harmonic Analysis},
      publisher = {Elsevier},
      volume = {19},
      number = {2},
      pages = {162--197},
      date = {2005},
      sortyear = {2003a},
    }
    • E. J. Candès
    • D. L. Donoho
    Continuous curvelet transform: II. Discretization and frames. Applied and Computational Harmonic Analysis. 2005.
    @article{ContCurveletTransform-II,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Continuous curvelet transform: II.\ Discretization and frames},
      journaltitle = {Applied and Computational Harmonic Analysis},
      publisher = {Elsevier},
      volume = {19},
      number = {2},
      pages = {198--222},
      date = {2005},
      sortyear = {2003b},
    }
  • 2002

    • E. J. Candès
    Multiscale chirplets and near-optimal recovery of chirps. Technical Report, Department of Statistics, Stanford University. 2002.
    @report{Chirplets,
      author = {Candès, Emmanuel J},
      title = {Multiscale chirplets and near-optimal recovery of chirps},
      date = {2002},
      institution = {Department of Statistics, Stanford University},
      sortyear = {2002g},
      type = {techreport},
    }
    • E. J. Candès
    • D. L. Donoho
    New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities. Communications on Pure and Applied Mathematics. 2004.
    @article{CurveEdges,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities},
      journaltitle = {Communications on Pure and Applied Mathematics},
      publisher = {Wiley Online Library},
      volume = {57},
      number = {2},
      pages = {219--266},
      date = {2004},
      sortyear = {2002f},
    }
    • E. J. Candès
    • L. Demanet
    Curvelets and fourier integral operators. Comptes Rendus Mathematique. 2003.
    @article{CurveletsFIO,
      author = {Candès, Emmanuel J and Demanet, Laurent},
      title = {Curvelets and Fourier integral operators},
      journaltitle = {Comptes Rendus Mathematique},
      publisher = {Elsevier},
      volume = {336},
      number = {5},
      pages = {395--398},
      date = {2003},
      sortyear = {2002e},
    }
    • J. Starck
    • D. L. Donoho
    • E. J. Candès
    Astronomical image representation by the curvelet transform. Astronomy & Astrophysics. 2003.
    @article{Astro,
      author = {Starck, Jean-Luc and Donoho, David L and Candès, Emmanuel J},
      title = {Astronomical image representation by the curvelet transform},
      journaltitle = {Astronomy \& Astrophysics},
      publisher = {EDP Sciences},
      volume = {398},
      number = {2},
      pages = {785--800},
      date = {2003},
      sortyear = {2002d},
    }
    • A. G. Flesia
    • H. Hel-Or
    • A. Averbuch
    • E. J. Candès
    • R. R. Coifman
    • D. L. Donoho
    Digital implementation of ridgelet packets. Studies in Computational Mathematics. 2003.
    @article{DIoRP,
      author = {Flesia, A G and Hel-Or, H and Averbuch, A and Candès, Emmanuel J and Coifman, R R and Donoho, David L},
      title = {Digital implementation of ridgelet packets},
      journaltitle = {Studies in Computational Mathematics},
      publisher = {Elsevier},
      volume = {10},
      pages = {31--60},
      date = {2003},
      sortyear = {2002c},
    }
    • E. J. Candès
    • F. Guo
    New multiscale transforms, minimum total variation synthesis: Applications to edge-preserving image reconstruction. Signal Processing. 2002.
    @article{TV_synthesis,
      author = {Candès, Emmanuel J and Guo, Franck},
      title = {New multiscale transforms, minimum total variation synthesis: Applications to edge-preserving image reconstruction},
      journaltitle = {Signal Processing},
      publisher = {Elsevier},
      volume = {82},
      number = {11},
      pages = {1519--1543},
      date = {2002},
      sortyear = {2002b},
    }
    • E. J. Candès
    New ties between computational harmonic analysis and approximation theory. Approximation theory x. 2002.
    @inproceedings{at_popov,
      author = {Candès, Emmanuel J},
      title = {New ties between computational harmonic analysis and approximation theory},
      booktitle = {Approximation Theory X},
      publisher = {Vanderbilt University Press},
      pages = {87--153},
      date = {2002},
      sortyear = {2002a},
    }
    • J. Starck
    • F. Murtagh
    • E. J. Candès
    • D. L. Donoho
    Gray and color image contrast enhancement by the curvelet transform. IEEE Transactions on Image Processing. 2003.
    @article{Cont_Enhance,
      author = {Starck, Jean-Luc and Murtagh, Fionn and Candès, Emmanuel J and Donoho, David L},
      title = {Gray and color image contrast enhancement by the curvelet transform},
      journaltitle = {IEEE Transactions on Image Processing},
      publisher = {IEEE},
      volume = {12},
      number = {6},
      pages = {706--717},
      date = {2003},
      sortyear = {2001b},
    }
  • 2001

    • J. Starck
    • E. J. Candès
    • D. L. Donoho
    Very high quality image restoration by combining wavelets and curvelets. Wavelet applications in signal and image processing IX. 2001.
    @inproceedings{SPIE01,
      author = {Starck, Jean-Luc and Candès, Emmanuel J and Donoho, David L},
      title = {Very high quality image restoration by combining wavelets and curvelets},
      booktitle = {Wavelet Applications in Signal and Image Processing IX},
      volume = {4478},
      date = {2001},
      editor = {Aldroubi, A and Laine, A F and Unser, M A},
      series = {Proc. SPIE},
      sortyear = {2001a},
    }
    • J. Starck
    • E. J. Candès
    • D. L. Donoho
    The curvelet transform for image denoising. IEEE Trans`\-`{=latex}ac`\-`{=latex}tions on Image Processing. 2002.
    @article{CurveDenoise,
      author = {Starck, Jean-Luc and Candès, Emmanuel J and Donoho, David L},
      title = {The curvelet transform for image denoising},
      journaltitle = {IEEE Trans\-ac\-tions on Image Processing},
      publisher = {IEEE},
      volume = {11},
      number = {6},
      pages = {670--684},
      date = {2002},
      sortyear = {2000e},
    }
  • 2000

    • E. J. Candès
    • D. L. Donoho
    Curvelets, multiresolution representation, and scaling laws. Wavelet applications in signal and image processing VIII. 2000.
    @inproceedings{SPIE_Curvelets,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Curvelets, multiresolution representation, and scaling laws},
      booktitle = {Wavelet Applications in Signal and Image Processing VIII},
      volume = {4119},
      date = {2000},
      editor = {Aldroubi, A and Laine, A F and Unser, M A},
      series = {Proc. SPIE},
      sortyear = {2000d},
    }
    • E. J. Candès
    • D. L. Donoho
    Curvelets and reconstruction of images from noisy radon data. Wavelet applications in signal and image processing VIII. 2000.
    @inproceedings{SPIE_Radon,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Curvelets and reconstruction of images from noisy radon data},
      booktitle = {Wavelet Applications in Signal and Image Processing VIII},
      volume = {4119},
      date = {2000},
      editor = {Aldroubi, A and Laine, A F and Unser, M A},
      series = {Proc. SPIE},
      sortyear = {2000c},
    }
    • E. J. Candès
    • D. L. Donoho
    Recovering edges in ill-posed inverse problems: Optimality of curvelet frames. Annals of Statistics. 2002.
    @article{CurveInverse,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Recovering edges in ill-posed inverse problems: Optimality of curvelet frames},
      journaltitle = {Annals of Statistics},
      publisher = {JSTOR},
      pages = {784--842},
      date = {2002},
      sortyear = {2000b},
    }
    • E. J. Candès
    • D. L. Donoho
    Curvelets and curvilinear integrals. Journal of Approximation Theory. 2001.
    @article{Curves_and_Curvelets,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Curvelets and curvilinear integrals},
      journaltitle = {Journal of Approximation Theory},
      publisher = {Elsevier},
      volume = {113},
      number = {1},
      pages = {59--90},
      date = {2001},
      sortyear = {2000a},
    }
  • 1999

    • E. J. Candès
    Ridgelets and their derivatives: Representation of images with edges. Curves and surfaces.
    • L. L. Schumaker
    • et al
    (eds.), Vanderbilt University Press. 1999.
    @incollection{StMalo,
      author = {Candès, Emmanuel J},
      title = {Ridgelets and their derivatives: Representation of images with edges},
      booktitle = {Curves and Surfaces},
      publisher = {Vanderbilt University Press},
      date = {1999},
      editor = {Schumaker, Larry L and others},
      sortyear = {1999g},
    }
    • E. J. Candès
    • D. L. Donoho
    Curvelets: A surprisingly effective nonadaptive representation for objects with edges. Curves and surfaces.
    • L. L. Schumaker
    • et al
    (eds.), Vanderbilt University Press. 1999.
    @incollection{Curvelet-SMStyle,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Curvelets: A surprisingly effective nonadaptive representation for objects with edges},
      booktitle = {Curves and Surfaces},
      publisher = {Vanderbilt University Press},
      date = {1999},
      editor = {Schumaker, Larry L and others},
      sortyear = {1999f},
    }
    • E. J. Candès
    Ridgelets: Estimating with ridge functions. Annals of Statistics. 2003.
    @article{Ridgelet_Stat,
      author = {Candès, Emmanuel J},
      title = {Ridgelets: Estimating with ridge functions},
      journaltitle = {Annals of Statistics},
      publisher = {JSTOR},
      pages = {1561--1599},
      date = {2003},
      sortyear = {1999e},
    }
    • E. J. Candès
    Ridgelets and the representation of mutilated sobolev functions. SIAM Journal on Math`\-`{=latex}e`\-`{=latex}ma`\-`{=latex}ti`\-`{=latex}cal Analysis. 2001.
    @article{Mutilated,
      author = {Candès, Emmanuel J},
      title = {Ridgelets and the representation of mutilated Sobolev functions},
      journaltitle = {SIAM Journal on Math\-e\-ma\-ti\-cal Analysis},
      publisher = {SIAM},
      volume = {33},
      number = {2},
      pages = {347--368},
      date = {2001},
      sortyear = {1999d},
    }
    • E. J. Candès
    Monoscale ridgelets for the representation of images with edges. Technical Report, Department of Statistics, Stanford University. 1999.
    @report{Monoscale,
      author = {Candès, Emmanuel J},
      title = {Monoscale ridgelets for the representation of images with edges},
      date = {1999},
      institution = {Department of Statistics, Stanford University},
      sortyear = {1999c},
      type = {techreport},
    }
    • E. J. Candès
    • D. L. Donoho
    Ridgelets: A key to higher-dimensional intermittency?. Philosophical Transactions of the Royal Society of London A. 1999.
    @article{RoySoc,
      author = {Candès, Emmanuel J and Donoho, David L},
      title = {Ridgelets: A key to higher-dimensional intermittency?},
      journaltitle = {Philosophical Transactions of the Royal Society of London A},
      publisher = {The Royal Society},
      volume = {357},
      number = {1760},
      pages = {2495--2509},
      date = {1999},
      sortyear = {1999b},
    }
    • E. J. Candès
    Harmonic analysis of neural networks. Applied and Computational Harmonic Analysis. 1999.
    @article{Harm_Net,
      author = {Candès, Emmanuel J},
      title = {Harmonic analysis of neural networks},
      journaltitle = {Applied and Computational Harmonic Analysis},
      publisher = {Elsevier},
      volume = {6},
      number = {2},
      pages = {197--218},
      date = {1999},
      sortyear = {1999a},
    }
  • 1998

    • E. J. Candès
    Ridgelets: Theory and applications. PhD Thesis, Department of Statistics, Stanford University. 1998.
    @thesis{Thesis,
      author = {Candès, Emmanuel J},
      title = {Ridgelets: Theory and applications},
      date = {1998},
      institution = {Department of Statistics, Stanford University},
      sortyear = {1998},
      type = {phdthesis},
    }