Papers
1,396 papers found
Near-Optimal Entrywise Sampling of Numerically Sparse Matrices
Vladimir Braverman, Robert Krauthgamer, Aditya R. Krishnan et al.
Non-asymptotic approximations of neural networks by Gaussian processes
Ronen Eldan, Dan Mikulincer, Tselil Schramm
Non-Euclidean Differentially Private Stochastic Convex Optimization
Raef Bassily, Cristobal Guzman, Anupama Nandi
Non-stationary Reinforcement Learning without Prior Knowledge: an Optimal Black-box Approach
Chen-Yu Wei, Haipeng Luo
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries
Badih Ghazi, Ravi Kumar, Pasin Manurangsi
On Empirical Bayes Variational Autoencoder: An Excess Risk Bound
Rong Tang, Yun Yang
Online Learning from Optimal Actions
Omar Besbes, Yuri Fonseca, Ilan Lobel
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games
Steve Hanneke, Roi Livni, Shay Moran
Online Markov Decision Processes with Aggregate Bandit Feedback
Alon Cohen, Haim Kaplan, Tomer Koren et al.
On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function
Gellert Weisz, Philip Amortila, Barnabás Janzer et al.
On the Approximation Power of Two-Layer Networks of Random ReLUs
Daniel Hsu, Clayton H Sanford, Rocco Servedio et al.
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness
Murat A Erdogdu, Rasa Hosseinzadeh
On the Minimal Error of Empirical Risk Minimization
Gil Kur, Alexander Rakhlin
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning
Alain Durmus, Eric Moulines, Alexey Naumov et al.
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm
Sinho Chewi, Chen Lu, Kwangjun Ahn et al.
Optimal Dynamic Regret in Exp-Concave Online Learning
Dheeraj Baby, Yu-Xiang Wang
Optimizing Optimizers: Regret-optimal gradient descent algorithms
Philippe Casgrain, Anastasis Kratsios
Outlier-Robust Learning of Ising Models Under Dobrushin’s Condition
Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart et al.
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes
Peter Grunwald, Thomas Steinke, Lydia Zakynthinou
Provable Memorization via Deep Neural Networks using Sub-linear Parameters
Sejun Park, Jaeho Lee, Chulhee Yun et al.
Quantifying Variational Approximation for Log-Partition Function
Romain Cosson, Devavrat Shah
Query complexity of least absolute deviation regression via robust uniform convergence
Xue Chen, Michal Derezinski