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467 papers

Rényi Divergence and Kullback-Leibler Divergence

Tim van Erven, Peter Harremoës

1206.2459

Faster and Sample Near-Optimal Algorithms for Proper Learning Mixtures of Gaussians

Constantinos Daskalakis, Gautam Kamath

1312.1054

Sub-Gaussian estimators of the mean of a random vector

Gábor Lugosi, Shahar Mendelson

1702.00482

Learning from Untrusted Data

Moses Charikar, Jacob Steinhardt, Gregory Valiant

1611.02315

The dynamics of message passing on dense graphs, with applications to compressed sensing

Mohsen Bayati, Andrea Montanari

1001.3448

Learning Poisson Binomial Distributions

Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio

1107.2702

Nonparametric regression using deep neural networks with ReLU activation function

Johannes Schmidt-Hieber

1708.06633

Learning mixtures of structured distributions over discrete domains

Siu-on Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun

1210.0864

A typical reconstruction limit of compressed sensing based on Lp-norm minimization

Y. Kabashima, T. Wadayama, T. Tanaka

0907.0914

Risk minimization by median-of-means tournaments

Gabor Lugosi, Shahar Mendelson

1608.00757

Geometric median and robust estimation in Banach spaces

Stanislav Minsker

1308.1334

Robust Estimators in High Dimensions without the Computational Intractability

Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Ankur Moitra, Alistair Stewart

1604.06443

Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising

David Donoho, Iain Johnstone, Andrea Montanari

1111.1041

Breaking the Curse of Dimensionality with Convex Neural Networks

Francis Bach

1412.8690

Testing $k$-Modal Distributions: Optimal Algorithms via Reductions

Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio, Gregory Valiant, Paul Valiant

1112.5659

Concentration and regularization of random graphs

Can M. Le, Elizaveta Levina, Roman Vershynin

1506.00669

Optimal Phase Transitions in Compressed Sensing

Yihong Wu, Sergio Verdú

1111.6822

The LASSO risk for gaussian matrices

Mohsen Bayati, Andrea Montanari

1008.2581

Algorithms of Robust Stochastic Optimization Based on Mirror Descent Method

Anatoli Juditsky, Alexander Nazin, Arkadi Nemirovsky, Alexandre Tsybakov

1907.02707

Sparse recovery under weak moment assumptions

Guillaume Lecué, Shahar Mendelson

1401.2188

Performance of empirical risk minimization in linear aggregation

Guillaume Lecué, Shahar Mendelson

1402.5763

Optimal Rates for Random Fourier Features

Bharath K. Sriperumbudur, Zoltan Szabo

1506.02155

Deep ReLU Networks Have Surprisingly Few Activation Patterns

Boris Hanin, David Rolnick

1906.00904

Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients?

Boris Hanin

1801.03744

The Noise-Sensitivity Phase Transition in Compressed Sensing

David L. Donoho, Arian Maleki, Andrea Montanari

1004.1218

Achieving Optimal Misclassification Proportion in Stochastic Block Model

Chao Gao, Zongming Ma, Anderson Y. Zhang, Harrison H. Zhou

1505.03772

From f-divergence to quantum quasi-entropies and their use

Denes Petz

0909.3647

Density Estimation in Infinite Dimensional Exponential Families

Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar

1312.3516

Message-Passing Estimation from Quantized Samples

Ulugbek Kamilov, Vivek K. Goyal, Sundeep Rangan

1105.6368

Non-parametric Stochastic Approximation with Large Step sizes

Aymeric Dieuleveut, Francis Bach

1408.0361

The lower tail of random quadratic forms, with applications to ordinary least squares and restricted eigenvalue properties

Roberto Imbuzeiro Oliveira

1312.2903

Covariance estimation for distributions with $2+\varepsilon$ moments

Nikhil Srivastava, Roman Vershynin

1106.2775

Community Detection in Degree-Corrected Block Models

Chao Gao, Zongming Ma, Anderson Y. Zhang, Harrison H. Zhou

1607.06993

Asymptotic Mutual Information for the Two-Groups Stochastic Block Model

Yash Deshpande, Emmanuel Abbe, Andrea Montanari

1507.08685

Information-theoretic bounds for exact recovery in weighted stochastic block models using the Renyi divergence

Varun Jog, Po-Ling Loh

1509.06418

Submatrix localization via message passing

Bruce Hajek, Yihong Wu, Jiaming Xu

1510.09219

Information-theoretically Optimal Sparse PCA

Yash Deshpande, Andrea Montanari

1402.2238

Semidefinite Programs for Exact Recovery of a Hidden Community

Bruce Hajek, Yihong Wu, Jiaming Xu

1602.06410

Computational barriers in minimax submatrix detection

Zongming Ma, Yihong Wu

1309.5914

State Evolution for General Approximate Message Passing Algorithms, with Applications to Spatial Coupling

Adel Javanmard, Andrea Montanari

1211.5164

Sparse PCA via Covariance Thresholding

Yash Deshpande, Andrea Montanari

1311.5179

Observed Universality of Phase Transitions in High-Dimensional Geometry, with Implications for Modern Data Analysis and Signal Processing

David L. Donoho, Jared Tanner

0906.2530

Rank-Sparsity Incoherence for Matrix Decomposition

Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky

0906.2220

Limits of spiked random matrices I

Alex Bloemendal, Bálint Virág

1011.1877

Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing

David L. Donoho, Adel Javanmard, Andrea Montanari

1112.0708

Latent variable graphical model selection via convex optimization

Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky

1008.1290

Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization

Benjamin Recht, Maryam Fazel, Pablo A. Parrilo

0706.4138

Enhancing Sparsity by Reweighted L1 Minimization

Emmanuel J. Candes, Michael B. Wakin, Stephen P. Boyd

0711.1612

The Fourier Transform of Poisson Multinomial Distributions and its Algorithmic Applications

Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart

1511.03592

A Size-Free CLT for Poisson Multinomials and its Applications

Constantinos Daskalakis, Anindya De, Gautam Kamath, Christos Tzamos

1511.03641

The pseudo-marginal approach for efficient Monte Carlo computations

Christophe Andrieu, Gareth O. Roberts

0903.5480

High-dimensional covariance matrix estimation with missing observations

Karim Lounici

1201.2577

The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond

Aurélien Garivier, Olivier Cappé

1102.2490

Challenging the empirical mean and empirical variance: a deviation study

Olivier Catoni

1009.2048

Deterministic Sequencing of Exploration and Exploitation for Multi-Armed Bandit Problems

Sattar Vakili, Keqin Liu, Qing Zhao

1106.6104

A Mean Field View of the Landscape of Two-Layers Neural Networks

Song Mei, Andrea Montanari, Phan-Minh Nguyen

1804.06561

Universality, Characteristic Kernels and RKHS Embedding of Measures

Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. G. Lanckriet

1003.0887

Bayesian Models of Graphs, Arrays and Other Exchangeable Random Structures

Peter Orbanz, Daniel M. Roy

1312.7857

How close is the sample covariance matrix to the actual covariance matrix?

Roman Vershynin

1004.3484

Asymptotic study of stochastic adaptive algorithm in non-convex landscape

Sébastien Gadat, Ioana Gavra

2012.05640

X-Armed Bandits

Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvari

1001.4475

Statistical guarantees for the EM algorithm: From population to sample-based analysis

Sivaraman Balakrishnan, Martin J. Wainwright, Bin Yu

1408.2156

On the Linear Convergence of the Alternating Direction Method of Multipliers

Mingyi Hong, Zhi-Quan Luo

1208.3922

Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems

Yash Deshpande, Andrea Montanari

1502.06590

Sum-of-Squares Lower Bounds for Sparse PCA

Tengyu Ma, Avi Wigderson

1507.06370

Universality of covariance matrices

Natesh S. Pillai, Jun Yin

1110.2501

Tracy-Widom law for the extreme eigenvalues of sample correlation matrices

Zhigang Bao, Guangming Pan, Wang Zhou

1110.5208

The spectrum of kernel random matrices

Noureddine El Karoui

1001.0492

Training behavior of deep neural network in frequency domain

Zhi-Qin John Xu, Yaoyu Zhang, Yanyang Xiao

1807.01251

List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians

Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart

1711.07211

Nonparametric Estimation of Renyi Divergence and Friends

Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman

1402.2966

Edge universality of correlation matrices

Natesh S. Pillai, Jun Yin

1112.2381

Equivalence of distance-based and RKHS-based statistics in hypothesis testing

Dino Sejdinovic, Bharath Sriperumbudur, Arthur Gretton, Kenji Fukumizu

1207.6076

Moments and Absolute Moments of the Normal Distribution

Andreas Winkelbauer

1209.4340

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models

Yudong Chen, Xiaodong Li, Jiaming Xu

1512.08425

Community detection in sparse networks via Grothendieck's inequality

Olivier Guédon, Roman Vershynin

1411.4686

The generalization error of random features regression: Precise asymptotics and double descent curve

Song Mei, Andrea Montanari

1908.05355

Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations

Boris Hanin

1708.02691

Surprises in High-Dimensional Ridgeless Least Squares Interpolation

Trevor Hastie, Andrea Montanari, Saharon Rosset, Ryan J. Tibshirani

1903.08560

Pseudo-likelihood methods for community detection in large sparse networks

Arash A. Amini, Aiyou Chen, Peter J. Bickel, Elizaveta Levina

1207.2340

Linearized two-layers neural networks in high dimension

Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari

1904.12191

Benign Overfitting in Linear Regression

Peter L. Bartlett, Philip M. Long, Gábor Lugosi, Alexander Tsigler

1906.11300

A mean-field limit for certain deep neural networks

Dyego Araújo, Roberto I. Oliveira, Daniel Yukimura

1906.00193

Accelerating Stochastic Gradient Descent For Least Squares Regression

Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford

1704.08227

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices

Yudong Chen, Jiaming Xu

1402.1267

Robust machine learning by median-of-means : theory and practice

Guillaume Lecué, Matthieu Lerasle

1711.10306

Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow

T. Tony Cai, Xiaodong Li, Zongming Ma

1506.03382

When Do Neural Networks Outperform Kernel Methods?

Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari

2006.13409

Deep learning: a statistical viewpoint

Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin

2103.09177

Benign overfitting in ridge regression

A. Tsigler, P. L. Bartlett

2009.14286

Statistical Query Lower Bounds for Robust Estimation of High-dimensional Gaussians and Gaussian Mixtures

Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart

1611.03473

How Well Can Generative Adversarial Networks Learn Densities: A Nonparametric View

Tengyuan Liang

1712.08244

On the principal components of sample covariance matrices

Alex Bloemendal, Antti Knowles, Horng-Tzer Yau, Jun Yin

1404.0788

Phase Retrieval via Wirtinger Flow: Theory and Algorithms

Emmanuel Candes, Xiaodong Li, Mahdi Soltanolkotabi

1407.1065

Sparse CCA: Adaptive Estimation and Computational Barriers

Chao Gao, Zongming Ma, Harrison H. Zhou

1409.8565

Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix

T. Tony Cai, Tengyuan Liang, Alexander Rakhlin

1502.01988

Non-asymptotic mixing of the MALA algorithm

Nawaf Bou-Rabee, Martin Hairer, Eric Vanden-Eijnden

1008.3514

Fast Algorithms for Robust PCA via Gradient Descent

Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis

1605.07784

Operator norm consistent estimation of large-dimensional sparse covariance matrices

Noureddine El Karoui

0901.3220

Phase Retrieval from Coded Diffraction Patterns

Emmanuel Candes, Xiaodong Li, Mahdi Soltanolkotabi

1310.3240

Optimizing The Integrator Step Size for Hamiltonian Monte Carlo

M. J. Betancourt, Simon Byrne, Mark Girolami

1411.6669

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

Yuejie Chi, Yue M. Lu, Yuxin Chen

1809.09573

Inference and Uncertainty Quantification for Noisy Matrix Completion

Yuxin Chen, Jianqing Fan, Cong Ma, Yuling Yan

1906.04159

Nonconvex Low-Rank Tensor Completion from Noisy Data

Changxiao Cai, Gen Li, H. Vincent Poor, Yuxin Chen

1911.04436

Nonlinear shrinkage estimation of large-dimensional covariance matrices

Olivier Ledoit, Michael Wolf

1207.5322

Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction

Dominik Stöger, Mahdi Soltanolkotabi

2106.15013

Phase retrieval with random Gaussian sensing vectors by alternating projections

Irène Waldspurger

1609.03088

Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

Yu Bai, Fan Chen, Huan Wang, Caiming Xiong, Song Mei

2306.04637

Kernel dimension reduction in regression

Kenji Fukumizu, Francis R. Bach, Michael I. Jordan

0908.1854

A note on the sample complexity of the Er-SpUD algorithm by Spielman, Wang and Wright for exact recovery of sparsely used dictionaries

Radosław Adamczak

1601.02049

Von Neumann Entropy Penalization and Low Rank Matrix Estimation

Vladimir Koltchinskii

1009.2439

Sharp analysis of low-rank kernel matrix approximations

Francis Bach

1208.2015

Regularized estimation of large covariance matrices

Peter J. Bickel, Elizaveta Levina

0803.1909

Nuclear norm penalization and optimal rates for noisy low rank matrix completion

Vladimir Koltchinskii, Alexandre B. Tsybakov, Karim Lounici

1011.6256

Spectral Methods for Data Science: A Statistical Perspective

Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma

2012.08496

Limitations of Lazy Training of Two-layers Neural Networks

Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari

1906.08899

Empirical entropy, minimax regret and minimax risk

Alexander Rakhlin, Karthik Sridharan, Alexandre B. Tsybakov

1308.1147

Eigenvectors of some large sample covariance matrix ensembles

Olivier Ledoit, Sandrine Péché

0911.3010

Flexible covariance estimation in graphical Gaussian models

Bala Rajaratnam, Hélène Massam, Carlos M. Carvalho

0901.3267

High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence

Pradeep Ravikumar, Martin J. Wainwright, Garvesh Raskutti, Bin Yu

0811.3628

Consistency of community detection in networks under degree-corrected stochastic block models

Yunpeng Zhao, Elizaveta Levina, Ji Zhu

1110.3854

Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit

Song Mei, Theodor Misiakiewicz, Andrea Montanari

1902.06015

Just Interpolate: Kernel "Ridgeless" Regression Can Generalize

Tengyuan Liang, Alexander Rakhlin

1808.00387

Wishart distributions for decomposable graphs

Gérard Letac, Hélène Massam

0708.2380

Sparse PCA: Optimal rates and adaptive estimation

T. Tony Cai, Zongming Ma, Yihong Wu

1211.1309

Kullback-Leibler upper confidence bounds for optimal sequential allocation

Olivier Cappé, Aurélien Garivier, Odalric-Ambrym Maillard, Rémi Munos, Gilles Stoltz

1210.1136

Privacy and Statistical Risk: Formalisms and Minimax Bounds

Rina Foygel Barber, John C. Duchi

1412.4451

Computational Lower Bounds for Community Detection on Random Graphs

Bruce Hajek, Yihong Wu, Jiaming Xu

1406.6625

Community Detection in Random Networks

Ery Arias-Castro, Nicolas Verzelen

1302.7099

Robust Learning of Fixed-Structure Bayesian Networks

Yu Cheng, Ilias Diakonikolas, Daniel Kane, Alistair Stewart

1606.07384

Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution

Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen

1711.10467

Statistical and computational trade-offs in estimation of sparse principal components

Tengyao Wang, Quentin Berthet, Richard J. Samworth

1408.5369

Stability and Convergence Trade-off of Iterative Optimization Algorithms

Yuansi Chen, Chi Jin, Bin Yu

1804.01619

Templates for Convex Cone Problems with Applications to Sparse Signal Recovery

Stephen R. Becker, Emmanuel J. Candès, Michael Grant

1009.2065

Interpolating between Optimal Transport and MMD using Sinkhorn Divergences

Jean Feydy, Thibault Séjourné, François-Xavier Vialard, Shun-ichi Amari, Alain Trouvé, Gabriel Peyré

1810.08278

Optimal Regularization Can Mitigate Double Descent

Preetum Nakkiran, Prayaag Venkat, Sham Kakade, Tengyu Ma

2003.01897

Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS

Lin Chen, Sheng Xu

2009.10683

Geometric Inference for General High-Dimensional Linear Inverse Problems

T. Tony Cai, Tengyuan Liang, Alexander Rakhlin

1404.4408

Spectral algorithms for tensor completion

Andrea Montanari, Nike Sun

1612.07866

Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation

Martin Azizyan, Aarti Singh, Larry Wasserman

1306.2035

Optimal Learning via the Fourier Transform for Sums of Independent Integer Random Variables

Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart

1505.00662

High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation

Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang

2205.01445

Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach

Yaniv Plan, Roman Vershynin

1202.1212

Feature allocations, probability functions, and paintboxes

Tamara Broderick, Jim Pitman, Michael I. Jordan

1301.6647

Flexible results for quadratic forms with applications to variance components estimation

Lee H. Dicker, Murat A. Erdogdu

1509.04388

High-dimensional Ising model selection using ${\ell_1}$-regularized logistic regression

Pradeep Ravikumar, Martin J. Wainwright, John D. Lafferty

1010.0311

Optimal rates of convergence for sparse covariance matrix estimation

T. Tony Cai, Harrison H. Zhou

1302.3030

Matrix estimation by Universal Singular Value Thresholding

Sourav Chatterjee

1212.1247

Lecture notes on rough paths and applications to machine learning

Thomas Cass, Cristopher Salvi

2404.06583

Convergence rates of efficient global optimization algorithms

Adam D. Bull

1101.3501

Degenerate U- and V-statistics under weak dependence: Asymptotic theory and bootstrap consistency

Anne Leucht

1205.1892

Kernel spectral clustering of large dimensional data

Romain Couillet, Florent Benaych-Georges

1510.03547

Learning from MOM's principles: Le Cam's approach

Lecué Guillaume, Lerasle Matthieu

1701.01961

Sharpening Jensen's Inequality

J. G. Liao, Arthur Berg

1707.08644

Non-negative Principal Component Analysis: Message Passing Algorithms and Sharp Asymptotics

Andrea Montanari, Emile Richard

1406.4775

A Complete Recipe for Stochastic Gradient MCMC

Yi-An Ma, Tianqi Chen, Emily B. Fox

1506.04696

Robust classification via MOM minimization

Guillaume Lecué, Matthieu Lerasle, Timothée Mathieu

1808.03106

How rotational invariance of common kernels prevents generalization in high dimensions

Konstantin Donhauser, Mingqi Wu, Fanny Yang

2104.04244

Optimal Shrinkage of Singular Values

Matan Gavish, David L. Donoho

1405.7511

Theoretical properties of the log-concave maximum likelihood estimator of a multidimensional density

Madeleine Cule, Richard Samworth

0908.4400

Approximating Continuous Functions by ReLU Nets of Minimal Width

Boris Hanin, Mark Sellke

1710.11278

On Learning Mixtures of Well-Separated Gaussians

Oded Regev, Aravindan Vijayaraghavan

1710.11592

Counterfactual Reasoning and Learning Systems

Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, Ed Snelson

1209.2355

Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems

Yuxin Chen, Emmanuel J. Candes

1505.05114

Regularization, sparse recovery, and median-of-means tournaments

Gábor Lugosi, Shahar Mendelson

1701.04112

Efficient Algorithms and Lower Bounds for Robust Linear Regression

Ilias Diakonikolas, Weihao Kong, Alistair Stewart

1806.00040

Spectrum of inner-product kernel matrices in the polynomial regime and multiple descent phenomenon in kernel ridge regression

Theodor Misiakiewicz

2204.10425

On the limitation of spectral methods: From the Gaussian hidden clique problem to rank one perturbations of Gaussian tensors

Andrea Montanari, Daniel Reichman, Ofer Zeitouni

1411.6149

Uniformly valid confidence intervals post-model-selection

François Bachoc, David Preinerstorfer, Lukas Steinberger

1611.01043

Universality of empirical risk minimization

Andrea Montanari, Basil Saeed

2202.08832

Minimax sparse principal subspace estimation in high dimensions

Vincent Q. Vu, Jing Lei

1211.0373

Understanding training and generalization in deep learning by Fourier analysis

Zhiqin John Xu

1808.04295

Harmless interpolation in regression and classification with structured features

Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya Muthukumar

2111.05198

Near-optimal mean estimators with respect to general norms

Gábor Lugosi, Shahar Mendelson

1806.06233

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Yen-Huan Li, Jonathan Scarlett, Pradeep Ravikumar, Volkan Cevher

1410.7605

Robustly Learning a Gaussian: Getting Optimal Error, Efficiently

Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart

1704.03866

Simultaneous support recovery in high dimensions: Benefits and perils of block $\ell_1/\ell_\infty$-regularization

S. Negahban, M. J. Wainwright

0905.0642

Performance of Bayesian linear regression in a model with mismatch

Jean Barbier, Wei-Kuo Chen, Dmitry Panchenko, Manuel Sáenz

2107.06936

Do semidefinite relaxations solve sparse PCA up to the information limit?

Robert Krauthgamer, Boaz Nadler, Dan Vilenchik

1306.3690

Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm

Alain Durmus, Eric Moulines

1507.05021

Minimax Estimation of Functionals of Discrete Distributions

Jiantao Jiao, Kartik Venkat, Yanjun Han, Tsachy Weissman

1406.6956

Dimension free ridge regression

Chen Cheng, Andrea Montanari

2210.08571

Nonparametric graphon estimation

Patrick J. Wolfe, Sofia C. Olhede

1309.5936

The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training

Andrea Montanari, Yiqiao Zhong

2007.12826

A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences

Odalric-Ambrym Maillard, Rémi Munos, Gilles Stoltz

1105.5820

Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classification

Maxime Bucher, Stéphane Herbin, Frédéric Jurie

1607.08085

Optimal selection of reduced rank estimators of high-dimensional matrices

Florentina Bunea, Yiyuan She, Marten H. Wegkamp

1004.2995

Finite sample approximation results for principal component analysis: a matrix perturbation approach

Boaz Nadler

0901.3245

Spectral norm of random tensors

Ryota Tomioka, Taiji Suzuki

1407.1870

Sequential Monte Carlo with Adaptive Weights for Approximate Bayesian Computation

Fernando V. Bonassi, Mike West

1503.07791

Restricted strong convexity and weighted matrix completion: Optimal bounds with noise

Sahand Negahban, Martin J. Wainwright

1009.2118

On the Structure, Covering, and Learning of Poisson Multinomial Distributions

Constantinos Daskalakis, Gautam Kamath, Christos Tzamos

1504.08363

Properly Learning Poisson Binomial Distributions in Almost Polynomial Time

Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart

1511.04066

Global and Individualized Community Detection in Inhomogeneous Multilayer Networks

Shuxiao Chen, Sifan Liu, Zongming Ma

2012.00933

Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability

Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan

1304.8087

The combinatorial structure of beta negative binomial processes

Creighton Heaukulani, Daniel M. Roy

1401.0062

Optimal rates of convergence for covariance matrix estimation

T. Tony Cai, Cun-Hui Zhang, Harrison H. Zhou

1010.3866

Learning curves of generic features maps for realistic datasets with a teacher-student model

Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová

2102.08127

Theoretical guarantees for approximate sampling from smooth and log-concave densities

Arnak S. Dalalyan

1412.7392

Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems

Thomas Bengtsson, Peter Bickel, Bo Li

0805.3034

Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model

David L. Donoho, Matan Gavish, Iain M. Johnstone

1311.0851

Testing conditional independence via Rosenblatt transforms

Kyungchul Song

0911.3787

Finite Sample Analysis of Approximate Message Passing Algorithms

Cynthia Rush, Ramji Venkataramanan

1606.01800

Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting

Frederic Koehler, Lijia Zhou, Danica J. Sutherland, Nathan Srebro

2106.09276

Learning subgaussian classes : Upper and minimax bounds

Guillaume Lecué, Shahar Mendelson

1305.4825

Ten Steps of EM Suffice for Mixtures of Two Gaussians

Constantinos Daskalakis, Christos Tzamos, Manolis Zampetakis

1609.00368

Sparse Additive Models

Pradeep Ravikumar, John Lafferty, Han Liu, Larry Wasserman

0711.4555

Learning Theory for Distribution Regression

Zoltan Szabo, Bharath Sriperumbudur, Barnabas Poczos, Arthur Gretton

1411.2066

Probably Approximately Correct Constrained Learning

Luiz F. O. Chamon, Alejandro Ribeiro

2006.05487

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Junzhou Huang, Tong Zhang

0901.2962

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Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang

2011.04019

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Tony Cai, Zongming Ma, Yihong Wu

1305.3235

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Ery Arias-Castro, Emmanuel J. Candès, Yaniv Plan

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A. W. van der Vaart, J. H. van Zanten

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Yash Deshpande, Andrea Montanari

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Michael H. Neumann, Efstathios Paparoditis

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Peter L. Bartlett, David P. Helmbold, Philip M. Long

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Hui Zou, Runze Li

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Aharon Birnbaum, Iain M. Johnstone, Boaz Nadler, Debashis Paul

1203.0967

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David Choi, Patrick J. Wolfe

1212.4093

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Song Mei, Theodor Misiakiewicz, Andrea Montanari

2102.13219

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Tatiana Xifara, Chris Sherlock, Samuel Livingstone, Simon Byrne, Mark Girolami

1309.2983

A Priori Estimates of the Population Risk for Two-layer Neural Networks

Weinan E, Chao Ma, Lei Wu

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Yuxin Chen, Chen Cheng, Jianqing Fan

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Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová

2002.11544

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Yi Yu, Tengyao Wang, Richard J. Samworth

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Junjie Ma, Ji Xu, Arian Maleki

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Pierre C. Bellec, Guillaume Lecué, Alexandre B. Tsybakov

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Zoltan Szabo

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Yu Cheng, Ilias Diakonikolas, Rong Ge

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Guillaume Obozinski, Martin J. Wainwright, Michael I. Jordan

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Song Mei, Theodor Misiakiewicz, Andrea Montanari

2101.10588

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Martin Ehler, Kasso A. Okoudjou

1101.0140

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Jonathan Weed, Francis Bach

1707.00087

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Cynthia Rudin, Robert E. Schapire, Ingrid Daubechies

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Arlene K. H. Kim, Richard J. Samworth

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Ji Xu, Daniel Hsu, Arian Maleki

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Quentin Berthet, Philippe Rigollet

1202.5070

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Fredrik Lindsten, Randal Douc, Eric Moulines

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Nikhil Ghosh, Song Mei, Bin Yu

2111.07167

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Adrien Saumard, Jon A. Wellner

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Botao Hao, Anru Zhang, Guang Cheng

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Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt

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Holden Lee, Jianfeng Lu, Yixin Tan

2209.12381

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David Donoho, Andrea Montanari

1310.7320

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Vincent Q. Vu, Jing Lei

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Alex Bloemendal, Bálint Virág

1109.3704

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Michał Dereziński, Feynman Liang, Michael W. Mahoney

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Yixin Wang, David M. Blei

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Clifford Lam, Jianqing Fan

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Dominic Schuhmacher, Andre Huesler, Lutz Duembgen

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Arseni Seregin, Jon A. Wellner

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Jianqing Fan, Cong Ma, Yiqiao Zhong

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Sebastian Engelke, Adrien S. Hitz

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Zongming Ma

1112.2432

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Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett

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Guillaume Lecué

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Cristina Butucea, Yuri I. Ingster

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Raj Rao Nadakuditi

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Sourav Chatterjee, Persi Diaconis, Allan Sly

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Liang Hong, Todd A. Kuffner, Ryan Martin

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Elina Robeva, Anna Seigal

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Karim Lounici, Massimiliano Pontil, Alexandre B. Tsybakov, Sara van de Geer

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Adityanand Guntuboyina, Bodhisattva Sen

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Shuhua Chang, Deli Li, Yongcheng Qi

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Ery Arias-Castro, Emmanuel J. Candès, Arnaud Durand

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Aurélien Garivier, Emilie Kaufmann

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Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath

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William Fithian, Dennis Sun, Jonathan Taylor

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Richard J. Samworth, Ming Yuan

1206.0457

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Johannes Buck, Claudia Klüppelberg

2003.00362

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Anirban Bhattacharya, Debdeep Pati, Natesh S. Pillai, David B. Dunson

1401.5398

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Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry Wasserman

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Zhiyang Xun, Shivam Gupta, Eric Price

2510.26324

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Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang

2209.11215

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Zhengjun Zhang

0804.1001

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Xin Chen, Changliang Zou, R. Dennis Cook

1211.3215

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Stanislav Minsker

1605.07129

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Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson

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Iain M Johnstone, Arthur Yu Lu

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2206.06227

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Christian Borgs, Jennifer Chayes, Devavrat Shah, Christina Lee Yu

1712.00710

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Alexei Onatski, Marcelo J. Moreira, Marc Hallin

1306.4867

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Joel A. Tropp

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Mahdi Soltanolkotabi, Emmanuel J. Candés

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Bruce Hajek, Sewoong Oh, Jiaming Xu

1406.5638

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Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi

2008.01036

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Po-Ling Loh, Martin J. Wainwright

1109.3714

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Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz, Russ Tedrake

2307.14619

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Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell

2103.12021

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1106.1497

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Luc Devroye, Matthieu Lerasle, Gabor Lugosi, Roberto I. Oliveira

1509.05845

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Zhou Fan, Zhichao Wang

2005.11879

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Samet Oymak, Christos Thrampoulidis, Babak Hassibi

1312.0641

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Sumit Mukherjee, Subhabrata Sen

2104.12232

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Veronika Rockova, Stephanie van der Pas

1708.08734

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Subhashis Ghosal, Jüri Lember, Aad van der Vaart

0802.0069

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Louigi Addario-Berry, Nicolas Broutin, Luc Devroye, Gábor Lugosi

0908.3437

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Joel A. Tropp

1504.05919

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Pierre Alquier, James Ridgway

1706.09293

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Tengyuan Liang, Pragya Sur

2002.01586

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Francis Bach

0910.4627

Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data

Yuxin Chen, Jianqing Fan, Cong Ma, Yuling Yan

2001.05484

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Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Nikos Zarifis

2006.12476

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Adel Javanmard, Marco Mondelli, Andrea Montanari

1901.01375

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Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington

2405.15074

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Boris Hanin

2107.01562

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Philippe Rigollet

0911.2919

The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors

S. L. van der Pas, B. J. K. Kleijn, A. W. van der Vaart

1404.0202

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Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová

2006.06560

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Peng Zhao, Guilherme Rocha, Bin Yu

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Clément L. Canonne, Ilias Diakonikolas, Themis Gouleakis, Ronitt Rubinfeld

1507.03558

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Rémi Bardenet, Odalric-Ambrym Maillard

1309.4029

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Stefan Wager, Susan Athey

1510.04342

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Sjoerd Dirksen, Guillaume Lecué, Holger Rauhut

1504.05073

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Wei Wang, Martin J. Wainwright, Kannan Ramchandran

0806.0604

Regularized rank-based estimation of high-dimensional nonparanormal graphical models

Lingzhou Xue, Hui Zou

1302.3082

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Justin Sirignano, Konstantinos Spiliopoulos

1611.05545

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Nadine Gissibl, Claudia Klüppelberg, Steffen Lauritzen

1901.03556

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Sahand Negahban, Martin J. Wainwright

0912.5100

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Mikhail Belkin

2105.14368

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Wen-Xin Zhou, Koushiki Bose, Jianqing Fan, Han Liu

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Houman Owhadi

1406.6668

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Jason D Lee, Jonathan E Taylor

1402.5596

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Guillaume Lecué, Shahar Mendelson

1601.05584

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Sifan Liu, Edgar Dobriban

1910.02373

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Fariborz Salehi, Ehsan Abbasi, Babak Hassibi

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Olga Klopp, Karim Lounici, Alexandre B. Tsybakov

1412.8132

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Ryan Martin, Stephen G. Walker

1304.7366

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Luc Devroye, Abbas Mehrabian, Tommy Reddad

1810.08693

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Yohann de Castro, Fabrice Gamboa

1103.4951

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Edgar Dobriban, Stefan Wager

1507.03003

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Andrea Montanari, Ramji Venkataramanan

1711.01682

High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath

2206.04030

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Mihailo Stojnic

1303.7291

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Navid Ardeshir, Clayton Sanford, Daniel Hsu

2105.14084

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Yihong Wu, Pengkun Yang

1612.03375

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Valentina Ros, Gerard Ben Arous, Giulio Biroli, Chiara Cammarota

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Wenhao Gui, Yongcheng Qi

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Guenther Walther

1002.4770

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Hemant Tyagi

2009.04859

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Emilie Kaufmann, Olivier Cappé, Aurélien Garivier

1405.3224

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Jian Huang, Joel L. Horowitz, Fengrong Wei

1010.4115

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Yen-Chi Chen, Christopher R. Genovese, Larry Wasserman

1504.05438

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Ming Gao, Wai Ming Tai, Bryon Aragam

2201.10548

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P. Baldi, G. Kerkyacharian, D. Marinucci, D. Picard

0807.5059

Ergodicity of Approximate MCMC Chains with Applications to Large Data Sets

Natesh S. Pillai, Aaron Smith

1405.0182

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Pierre Alquier, Karim Lounici

1009.2707

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Rajen D. Shah, Jonas Peters

1804.07203

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Rina Foygel Barber, Emmanuel J. Candès

1404.5609

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Frédéric Chazal, Brittany T. Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo, Larry Wasserman

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David Donoho, Jiashun Jin

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Emmanuel Gobet, Plamen Turkedjiev

1601.01186

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Christos Thrampoulidis, Ehsan Abbasi, Babak Hassibi

1601.06233

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Shashank Singh, Barnabás Póczos

1603.08578

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Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel Ward

1408.4045

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Walid Hachem, Philippe Loubaton, Xavier Mestre, Jamal Najim, Pascal Vallet

1106.5119

Robust Estimation of High-Dimensional Mean Regression

Jianqing Fan, Quefeng Li, Yuyan Wang

1410.2150

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Emmanuel J. Candes, Carlos A. Sing-Long, Joshua D. Trzasko

1210.4139

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Anirban Bhattacharya, Debdeep Pati, Yun Yang

1611.01125

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Pauliina Ilmonen, Davy Paindaveine

1202.5159

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Nabarun Deb, Bodhisattva Sen

1909.08733

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Edoardo M Airoldi, David M Blei, Stephen E Fienberg, Eric P Xing

0705.4485

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Emilien Joly, Gábor Lugosi

1504.04580

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Naveen Naidu Narisetty, Xuming He

1405.6545

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Christian Robert, Jean-Michel Marin

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Sitan Chen, Ankur Moitra

2004.07659

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Adityanand Guntuboyina

1002.0042

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Lutz Duembgen, Richard Samworth, Dominic Schuhmacher

1002.3448

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Christos Thrampoulidis, Samet Oymak, Babak Hassibi

1401.6578

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Krishnakumar Balasubramanian, Saeed Ghadimi

1809.06474

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Stanislav Minsker, Xiaohan Wei

1708.00502

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Jason M. Altschuler, Sinho Chewi

2302.10249

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Christos Thrampoulidis, Samet Oymak, Mahdi Soltanolkotabi

2011.07729

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T. Tony Cai, Anru Zhang

1306.1154

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Xiaoying Tian, Jonathan E. Taylor

1507.06739

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Jianqing Fan, Yuan Liao, Martina Mincheva

1201.0175

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Francis Bach

0804.1302

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Amandine Schreck, Gersende Fort, Sylvain Le Corff, Eric Moulines

1312.5658

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Likun Zhang, Benjamin A. Shaby, Jennifer L. Wadsworth

1907.09617

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Xiaoying Tian, Jonathan Taylor

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Ping Ma, Xinlian Zhang, Xin Xing, Jingyi Ma, Michael W. Mahoney

2002.10526

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Yuxin Chen, Jianqing Fan, Cong Ma, Kaizheng Wang

1707.09971

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Steven R. Howard, Aaditya Ramdas, Jon McAuliffe, Jasjeet Sekhon

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T. Tony Cai, Wen-Xin Zhou

1309.6013

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Afonso S. Bandeira, Moses Charikar, Amit Singer, Andy Zhu

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Jianqing Fan, Weichen Wang, Yiqiao Zhong

1603.03516

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Victor Veitch, Daniel M. Roy

1512.03099

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Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli, Larry Wasserman

1212.5156

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Jason D. Lee, Dennis L. Sun, Yuekai Sun, Jonathan E. Taylor

1311.6238

Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective

Dylan J. Foster, Alexander Rakhlin, David Simchi-Levi, Yunzong Xu

2010.03104

1-Bit Matrix Completion

Mark A. Davenport, Yaniv Plan, Ewout van den Berg, Mary Wootters

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Ismaël Castillo, Johannes Schmidt-Hieber, Aad van der Vaart

1403.0735

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Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco

2006.06386

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Ying Jin, Zhuoran Yang, Zhaoran Wang

2012.15085

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Aad van der Vaart, Harry van Zanten

0710.3679

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A. W. van der Vaart, J. H. van Zanten

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Subhashis Ghosal, Aad van der Vaart

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A. W. van der Vaart, J. H. van Zanten

0805.3252

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Subhashis Ghosal, Aad van der Vaart

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Stephen G. Walker, Antonio Lijoi, Igor Prünster

0708.1892

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Yaming Yu

0905.2646

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Radoslav Harman, Luc Pronzato

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Venkat Chandrasekaran, Michael I. Jordan

1211.1073

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Peter J. Bickel, Aiyou Chen, Elizaveta Levina

1202.5101

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Ery Arias-Castro, Sébastien Bubeck, Gábor Lugosi

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Quentin Berthet, Philippe Rigollet

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Debashis Paul, Iain M. Johnstone

1202.1242

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Karl Rohe, Sourav Chatterjee, Bin Yu

1007.1684

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Methodology and convergence rates for functional linear regression

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High-dimensional analysis of semidefinite relaxations for sparse principal components

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Consistency of Sparse PCA in High Dimension, Low Sample Size Contexts

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Asymptotic properties of bridge estimators in sparse high-dimensional regression models

Jian Huang, Joel L. Horowitz, Shuangge Ma

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Simultaneous analysis of Lasso and Dantzig selector

Peter J. Bickel, Ya'acov Ritov, Alexandre B. Tsybakov

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Lasso-type recovery of sparse representations for high-dimensional data

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Sparsity oracle inequalities for the Lasso

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On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing

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Limit theorems for sample eigenvalues in a generalized spiked population model

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Performance of Statistical Tests for Single Source Detection using Random Matrix Theory

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Sequential Selection Procedures and False Discovery Rate Control

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Valid post-selection inference

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Asymptotic normality and optimalities in estimation of large Gaussian graphical models

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Some sharp performance bounds for least squares regression with $L_1$ regularization

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Statistical significance in high-dimensional linear models

Peter Bühlmann

1202.1377

Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory

Adel Javanmard, Andrea Montanari

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High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression

Pradeep Ravikumar, Martin J. Wainwright, John D. Lafferty

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Thresholding-based Iterative Selection Procedures for Model Selection and Shrinkage

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Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap

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Uniform Asymptotic Inference and the Bootstrap After Model Selection

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The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning

Léo Miolane, Andrea Montanari

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Causal inference using the algorithmic Markov condition

Dominik Janzing, Bernhard Schoelkopf

0804.3678

On Universal Prediction and Bayesian Confirmation

Marcus Hutter

0709.1516

CoinPress: Practical Private Mean and Covariance Estimation

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2006.06618

Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions

Pierre Alquier, Vincent Cottet, Guillaume Lecué

1702.01402

Faster Algorithms for High-Dimensional Robust Covariance Estimation

Yu Cheng, Ilias Diakonikolas, Rong Ge, David Woodruff

1906.04661

Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection

Yihe Dong, Samuel B. Hopkins, Jerry Li

1906.11366

Identifiability of deep generative models without auxiliary information

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Batch Policy Learning in Average Reward Markov Decision Processes

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2007.11771

Convergence Rates of Variational Posterior Distributions

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Random Projections For Large-Scale Regression

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The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method

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Simple, Scalable and Accurate Posterior Interval Estimation

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Piecewise Deterministic Markov Processes for Continuous-Time Monte Carlo

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