E
Emmanuel J. Candès
Researcher at Stanford University
Publications - 280
Citations - 148481
Emmanuel J. Candès is an academic researcher from Stanford University. The author has contributed to research in topics: Convex optimization & Compressed sensing. The author has an hindex of 102, co-authored 262 publications receiving 135077 citations. Previous affiliations of Emmanuel J. Candès include Samsung & École Normale Supérieure.
Papers
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Proceedings Article
Conformalized Quantile Regression
TL;DR: In this article, the authors combine conformal prediction with classical quantile regression, inheriting the advantages of both, and show that their method tends to produce shorter intervals than other conformal methods.
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Ridgelets and the Representation of Mutilated Sobolev Functions
TL;DR: Ridgelets are shown to be optimal to represent smooth multivariate functions that may exhibit linear singularities, allowing optimal partial reconstructions and unlike all systems currently in use, especially Fourier or wavelet representations.
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Conformal prediction beyond exchangeability
TL;DR: These algorithms are provably robust, with substantially less loss of coverage when exchangeability is violated due to distribution drift or other challenging features of real data, while also achieving the same coverage guarantees as existing conformal prediction methods if the data points are in fact exchangeable.
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Multi-resolution localization of causal variants across the genome.
TL;DR: This work proposes KnockoffZoom, a non-parametric statistical method for the simultaneous discovery and fine-mapping of causal variants, assuming only that LD is described by hidden Markov models (HMMs).
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Metropolized Knockoff Sampling
TL;DR: Techniques for knockoff generation in great generality are introduced, providing a sequential characterization of all possible knockoff distributions, which leads to a Metropolis-Hastingsformulation of an exact knockoff sampler and how to use conditional independence structure to speed up computations.