Papers
1,396 papers found
Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms
Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
Faster Rates for Convex-Concave Games
Jacob Abernethy, Kevin A. Lai, Kfir Y. Levy et al.
Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning
Gal Dalal, Gugan Thoppe, Balázs Szörényi et al.
Fitting a Putative Manifold to Noisy Data
Charles Fefferman, Sergei Ivanov, Yaroslav Kurylev et al.
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval
Marco Mondelli, Andrea Montanari
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints
Wenlong Mou, Liwei Wang, Xiyu Zhai et al.
Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints
Yanjun Han, Ayfer Özgür, Tsachy Weissman
Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk
Paul Hand, Vladislav Voroninski
Hardness of Learning Noisy Halfspaces using Polynomial Thresholds
Arnab Bhattacharyya, Suprovat Ghoshal, Rishi Saket
Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models
Yingjie Fei, Yudong Chen
Incentivizing Exploration by Heterogeneous Users
Bangrui Chen, Peter Frazier, David Kempe
Information Directed Sampling and Bandits with Heteroscedastic Noise
Johannes Kirschner, Andreas Krause
Iterate Averaging as Regularization for Stochastic Gradient Descent
Gergely Neu, Lorenzo Rosasco
Langevin Monte Carlo and JKO splitting
Espen Bernton
Learning Mixtures of Linear Regressions with Nearly Optimal Complexity
Yuanzhi Li, Yingyu Liang
Learning Patterns for Detection with Multiscale Scan Statistics
James Sharpnack
Learning Single-Index Models in Gaussian Space
Rishabh Dudeja, Daniel Hsu
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
Max Simchowitz, Horia Mania, Stephen Tu et al.
Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance
Yanjun Han, Jiantao Jiao, Tsachy Weissman
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability
Belinda Tzen, Tengyuan Liang, Maxim Raginsky
Log-concave sampling: Metropolis-Hastings algorithms are fast!
Raaz Dwivedi, Yuansi Chen, Martin J Wainwright et al.
Logistic Regression: The Importance of Being Improper
Dylan J. Foster, Satyen Kale, Haipeng Luo et al.
Lower Bounds for Higher-Order Convex Optimization
Naman Agarwal, Elad Hazan
Marginal Singularity, and the Benefits of Labels in Covariate-Shift
Samory Kpotufe, Guillaume Martinet
Minimax Bounds on Stochastic Batched Convex Optimization
John Duchi, Feng Ruan, Chulhee Yun