

























[edit]
[edit]
Editors: Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
Conference on Learning Theory 2018: Preface
; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1-1
[abs][Download PDF]
Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations
Yuanzhi Li, Tengyu Ma, Hongyang Zhang; Proceedings of the 31st Conference On Learning Theory, PMLR 75:2-47
[abs][Download PDF]
Reducibility and Computational Lower Bounds for Problems with Planted Sparse Structure
Matthew Brennan, Guy Bresler, Wasim Huleihel; Proceedings of the 31st Conference On Learning Theory, PMLR 75:48-166
[abs][Download PDF]
Logistic Regression: The Importance of Being Improper
Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:167-208
[abs][Download PDF]
Actively Avoiding Nonsense in Generative Models
Steve Hanneke, Adam Tauman Kalai, Gautam Kamath, Christos Tzamos; Proceedings of the 31st Conference On Learning Theory, PMLR 75:209-227
[abs][Download PDF]
A Faster Approximation Algorithm for the Gibbs Partition Function
Vladimir Kolmogorov; Proceedings of the 31st Conference On Learning Theory, PMLR 75:228-249
[abs][Download PDF]
Exponential Convergence of Testing Error for Stochastic Gradient Methods
Loucas Pillaud-Vivien, Alessandro Rudi, Francis Bach; Proceedings of the 31st Conference On Learning Theory, PMLR 75:250-296
[abs][Download PDF]
Size-Independent Sample Complexity of Neural Networks
Noah Golowich, Alexander Rakhlin, Ohad Shamir; Proceedings of the 31st Conference On Learning Theory, PMLR 75:297-299
[abs][Download PDF]
Underdamped Langevin MCMC: A non-asymptotic analysis
Xiang Cheng, Niladri S. Chatterji, Peter L. Bartlett, Michael I. Jordan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:300-323
[abs][Download PDF]
Online Variance Reduction for Stochastic Optimization
Zalan Borsos, Andreas Krause, Kfir Y. Levy; Proceedings of the 31st Conference On Learning Theory, PMLR 75:324-357
[abs][Download PDF]
Information Directed Sampling and Bandits with Heteroscedastic Noise
Johannes Kirschner, Andreas Krause; Proceedings of the 31st Conference On Learning Theory, PMLR 75:358-384
[abs][Download PDF]
Testing Symmetric Markov Chains From a Single Trajectory
Constantinos Daskalakis, Nishanth Dikkala, Nick Gravin; Proceedings of the 31st Conference On Learning Theory, PMLR 75:385-409
[abs][Download PDF]
Detection limits in the high-dimensional spiked rectangular model
Ahmed El Alaoui, Michael I. Jordan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:410-438
[abs][Download PDF]
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
Max Simchowitz, Horia Mania, Stephen Tu, Michael I. Jordan, Benjamin Recht; Proceedings of the 31st Conference On Learning Theory, PMLR 75:439-473
[abs][Download PDF]
Active Tolerant Testing
Avrim Blum, Lunjia Hu; Proceedings of the 31st Conference On Learning Theory, PMLR 75:474-497
[abs][Download PDF]
Polynomial Time and Sample Complexity for Non-Gaussian Component Analysis: Spectral Methods
Yan Shuo Tan, Roman Vershynin; Proceedings of the 31st Conference On Learning Theory, PMLR 75:498-534
[abs][Download PDF]
Calibrating Noise to Variance in Adaptive Data Analysis
Vitaly Feldman, Thomas Steinke; Proceedings of the 31st Conference On Learning Theory, PMLR 75:535-544
[abs][Download PDF]
Accelerating Stochastic Gradient Descent for Least Squares Regression
Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford; Proceedings of the 31st Conference On Learning Theory, PMLR 75:545-604
[abs][Download PDF]
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints
Wenlong Mou, Liwei Wang, Xiyu Zhai, Kai Zheng; Proceedings of the 31st Conference On Learning Theory, PMLR 75:605-638
[abs][Download PDF]
Optimal approximation of continuous functions by very deep ReLU networks
Dmitry Yarotsky; Proceedings of the 31st Conference On Learning Theory, PMLR 75:639-649
[abs][Download PDF]
Averaging Stochastic Gradient Descent on Riemannian Manifolds
Nilesh Tripuraneni, Nicolas Flammarion, Francis Bach, Michael I. Jordan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:650-687
[abs][Download PDF]
Fitting a Putative Manifold to Noisy Data
Charles Fefferman, Sergei Ivanov, Yaroslav Kurylev, Matti Lassas, Hariharan Narayanan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:688-720
[abs][Download PDF]
Private Sequential Learning
John Tsitsiklis, Kuang Xu, Zhi Xu; Proceedings of the 31st Conference On Learning Theory, PMLR 75:721-727
[abs][Download PDF]
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models
Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, Lenka Zdeborová; Proceedings of the 31st Conference On Learning Theory, PMLR 75:728-731
[abs][Download PDF]
Exact and Robust Conformal Inference Methods for Predictive Machine Learning with Dependent Data
Victor Chernozhukov, Kaspar Wüthrich, Zhu Yinchu; Proceedings of the 31st Conference On Learning Theory, PMLR 75:732-749
[abs][Download PDF]
Nonstochastic Bandits with Composite Anonymous Feedback
Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour; Proceedings of the 31st Conference On Learning Theory, PMLR 75:750-773
[abs][Download PDF]
Lower Bounds for Higher-Order Convex Optimization
Naman Agarwal, Elad Hazan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:774-792
[abs][Download PDF]
Log-concave sampling: Metropolis-Hastings algorithms are fast!
Raaz Dwivedi, Yuansi Chen, Martin J Wainwright, Bin Yu; Proceedings of the 31st Conference On Learning Theory, PMLR 75:793-797
[abs][Download PDF]
Incentivizing Exploration by Heterogeneous Users
Bangrui Chen, Peter Frazier, David Kempe; Proceedings of the 31st Conference On Learning Theory, PMLR 75:798-818
[abs][Download PDF]
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms
Ilias Diakonikolas, Jerry Li, Ludwig Schmidt; Proceedings of the 31st Conference On Learning Theory, PMLR 75:819-842
[abs][Download PDF]
Time-Space Tradeoffs for Learning Finite Functions from Random Evaluations, with Applications to Polynomials
Paul Beame, Shayan Oveis Gharan, Xin Yang; Proceedings of the 31st Conference On Learning Theory, PMLR 75:843-856
[abs][Download PDF]
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability
Belinda Tzen, Tengyuan Liang, Maxim Raginsky; Proceedings of the 31st Conference On Learning Theory, PMLR 75:857-875
[abs][Download PDF]
Hardness of Learning Noisy Halfspaces using Polynomial Thresholds
Arnab Bhattacharyya, Suprovat Ghoshal, Rishi Saket; Proceedings of the 31st Conference On Learning Theory, PMLR 75:876-917
[abs][Download PDF]
Best of both worlds: Stochastic & adversarial best-arm identification
Yasin Abbasi-Yadkori, Peter Bartlett, Victor Gabillon, Alan Malek, Michal Valko; Proceedings of the 31st Conference On Learning Theory, PMLR 75:918-949
[abs][Download PDF]
Learning Patterns for Detection with Multiscale Scan Statistics
James Sharpnack; Proceedings of the 31st Conference On Learning Theory, PMLR 75:950-969
[abs][Download PDF]
Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk
Paul Hand, Vladislav Voroninski; Proceedings of the 31st Conference On Learning Theory, PMLR 75:970-978
[abs][Download PDF]
Small-loss bounds for online learning with partial information
Thodoris Lykouris, Karthik Sridharan, Éva Tardos; Proceedings of the 31st Conference On Learning Theory, PMLR 75:979-986
[abs][Download PDF]
Empirical bounds for functions with weak interactions
Andreas Maurer, Massimiliano Pontil; Proceedings of the 31st Conference On Learning Theory, PMLR 75:987-1010
[abs][Download PDF]
Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression
Shiva Prasad Kasiviswanathan, Mark Rudelson; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1011-1041
[abs][Download PDF]
Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent
Chi Jin, Praneeth Netrapalli, Michael I. Jordan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1042-1085
[abs][Download PDF]
Convex Optimization with Unbounded Nonconvex Oracles using Simulated Annealing
Oren Mangoubi, Nisheeth K. Vishnoi; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1086-1124
[abs][Download PDF]
Learning Mixtures of Linear Regressions with Nearly Optimal Complexity
Yuanzhi Li, Yingyu Liang; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1125-1144
[abs][Download PDF]
Detecting Correlations with Little Memory and Communication
Yuval Dagan, Ohad Shamir; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1145-1198
[abs][Download PDF]
Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning
Gal Dalal, Gugan Thoppe, Balázs Szörényi, Shie Mannor; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1199-1233
[abs][Download PDF]
Near-Optimal Sample Complexity Bounds for Maximum Likelihood Estimation of Multivariate Log-concave Densities
Timothy Carpenter, Ilias Diakonikolas, Anastasios Sidiropoulos, Alistair Stewart; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1234-1262
[abs][Download PDF]
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei, Haipeng Luo; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1263-1291
[abs][Download PDF]
Efficient Convex Optimization with Membership Oracles
Yin Tat Lee, Aaron Sidford, Santosh S. Vempala; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1292-1294
[abs][Download PDF]
A General Approach to Multi-Armed Bandits Under Risk Criteria
Asaf Cassel, Shie Mannor, Assaf Zeevi; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1295-1306
[abs][Download PDF]
An Optimal Learning Algorithm for Online Unconstrained Submodular Maximization
Tim Roughgarden, Joshua R. Wang; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1307-1325
[abs][Download PDF]
The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity
Vishesh Jain, Frederic Koehler, Elchanan Mossel; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1326-1347
[abs][Download PDF]
Approximation beats concentration? An approximation view on inference with smooth radial kernels
Mikhail Belkin; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1348-1361
[abs][Download PDF]
Non-Convex Matrix Completion Against a Semi-Random Adversary
Yu Cheng, Rong Ge; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1362-1394
[abs][Download PDF]
The Vertex Sample Complexity of Free Energy is Polynomial
Vishesh Jain, Frederic Koehler, Elchanan Mossel; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1395-1419
[abs][Download PDF]
Efficient Algorithms for Outlier-Robust Regression
Adam Klivans, Pravesh K. Kothari, Raghu Meka; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1420-1430
[abs][Download PDF]
Action-Constrained Markov Decision Processes With Kullback-Leibler Cost
Ana Bušić, Sean Meyn; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1431-1444
[abs][Download PDF]
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval
Marco Mondelli, Andrea Montanari; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1445-1450
[abs][Download PDF]
Cutting plane methods can be extended into nonconvex optimization
Oliver Hinder; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1451-1454
[abs][Download PDF]
An Analysis of the t-SNE Algorithm for Data Visualization
Sanjeev Arora, Wei Hu, Pravesh K. Kothari; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1455-1462
[abs][Download PDF]
Adaptivity to Smoothness in X-armed bandits
Andrea Locatelli, Alexandra Carpentier; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1463-1492
[abs][Download PDF]
Black-Box Reductions for Parameter-free Online Learning in Banach Spaces
Ashok Cutkosky, Francesco Orabona; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1493-1529
[abs][Download PDF]
A Data Prism: Semi-verified learning in the small-alpha regime
Michela Meister, Gregory Valiant; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1530-1546
[abs][Download PDF]
A Direct Sum Result for the Information Complexity of Learning
Ido Nachum, Jonathan Shafer, Amir Yehudayoff; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1547-1568
[abs][Download PDF]
Online learning over a finite action set with limited switching
Jason Altschuler, Kunal Talwar; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1569-1573
[abs][Download PDF]
Smoothed Online Convex Optimization in High Dimensions via Online Balanced Descent
Niangjun Chen, Gautam Goel, Adam Wierman; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1574-1594
[abs][Download PDF]
Faster Rates for Convex-Concave Games
Jacob Abernethy, Kevin A. Lai, Kfir Y. Levy, Jun-Kun Wang; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1595-1625
[abs][Download PDF]
$\ell_1$ Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent
David Durfee, Kevin A. Lai, Saurabh Sawlani; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1626-1656
[abs][Download PDF]
Optimal Single Sample Tests for Structured versus Unstructured Network Data
Guy Bresler, Dheeraj Nagaraj; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1657-1690
[abs][Download PDF]
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation
Jalaj Bhandari, Daniel Russo, Raghav Singal; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1691-1692
[abs][Download PDF]
Privacy-preserving Prediction
Cynthia Dwork, Vitaly Feldman; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1693-1702
[abs][Download PDF]
An Estimate Sequence for Geodesically Convex Optimization
Hongyi Zhang, Suvrit Sra; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1703-1723
[abs][Download PDF]
The Externalities of Exploration and How Data Diversity Helps Exploitation
Manish Raghavan, Aleksandrs Slivkins, Jennifer Vaughan Wortman, Zhiwei Steven Wu; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1724-1738
[abs][Download PDF]
Efficient Contextual Bandits in Non-stationary Worlds
Haipeng Luo, Chen-Yu Wei, Alekh Agarwal, John Langford; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1739-1776
[abs][Download PDF]
Langevin Monte Carlo and JKO splitting
Espen Bernton; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1777-1798
[abs][Download PDF]
Subpolynomial trace reconstruction for random strings \{and arbitrary deletion probability
Nina Holden, Robin Pemantle, Yuval Peres; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1799-1840
[abs][Download PDF]
An explicit analysis of the entropic penalty in linear programming
Jonathan Weed; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1841-1855
[abs][Download PDF]
Efficient active learning of sparse halfspaces
Chicheng Zhang; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1856-1880
[abs][Download PDF]
Marginal Singularity, and the Benefits of Labels in Covariate-Shift
Samory Kpotufe, Guillaume Martinet; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1882-1886
[abs][Download PDF]
Learning Single-Index Models in Gaussian Space
Rishabh Dudeja, Daniel Hsu; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1887-1930
[abs][Download PDF]
Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models
Yingjie Fei, Yudong Chen; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1931-1965
[abs][Download PDF]
Counting Motifs with Graph Sampling
Jason M. Klusowski, Yihong Wu; Proceedings of the 31st Conference On Learning Theory, PMLR 75:1966-2011
[abs][Download PDF]
Approximate Nearest Neighbors in Limited Space
Piotr Indyk, Tal Wagner; Proceedings of the 31st Conference On Learning Theory, PMLR 75:2012-2036
[abs][Download PDF]
Breaking the $1/\sqrt{n}$ Barrier: Faster Rates for Permutation-based Models in Polynomial Time
Cheng Mao, Ashwin Pananjady, Martin J. Wainwright; Proceedings of the 31st Conference On Learning Theory, PMLR 75:2037-2042
[abs][Download PDF]
Unleashing Linear Optimizers for Group-Fair Learning and Optimization
Daniel Alabi, Nicole Immorlica, Adam Kalai; Proceedings of the 31st Conference On Learning Theory, PMLR 75:2043-2066
[abs][Download PDF]
The Many Faces of Exponential Weights in Online Learning
Dirk Hoeven, Tim Erven, Wojciech Kotłowski; Proceedings of the 31st Conference On Learning Theory, PMLR 75:2067-2092
[abs][Download PDF]
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem
Andre Wibisono; Proceedings of the 31st Conference On Learning Theory, PMLR 75:2093-3027
[abs][Download PDF]
Online Learning: Sufficient Statistics and the Burkholder Method
Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3028-3064
[abs][Download PDF]
Minimax Bounds on Stochastic Batched Convex Optimization
John Duchi, Feng Ruan, Chulhee Yun; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3065-3162
[abs][Download PDF]
Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints
Yanjun Han, Ayfer Özgür, Tsachy Weissman; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3163-3188
[abs][Download PDF]
Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance
Yanjun Han, Jiantao Jiao, Tsachy Weissman; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3189-3221
[abs][Download PDF]
Iterate Averaging as Regularization for Stochastic Gradient Descent
Gergely Neu, Lorenzo Rosasco; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3222-3242
[abs][Download PDF]
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form
Srinadh Bhojanapalli, Nicolas Boumal, Prateek Jain, Praneeth Netrapalli; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3243-3270
[abs][Download PDF]
Certified Computation from Unreliable Datasets
Themis Gouleakis, Christos Tzamos, Manolis Zampetakis; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3271-3294
[abs][Download PDF]
Open Problem: The Dependence of Sample Complexity Lower Bounds on Planning Horizon
Nan Jiang, Alekh Agarwal; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3395-3398
[abs][Download PDF]
Open problem: Improper learning of mixtures of Gaussians
Elad Hazan, Livni Roi; Proceedings of the 31st Conference On Learning Theory, PMLR 75:3399-3402
[abs][Download PDF]
此内容由惯性聚合(RSS阅读器)自动聚合整理,仅供阅读参考。 原文来自 — 版权归原作者所有。