Papers
1,396 papers found
The Complexity of Making the Gradient Small in Stochastic Convex Optimization
Dylan J. Foster, Ayush Sekhari, Ohad Shamir et al.
The implicit bias of gradient descent on nonseparable data
Ziwei Ji, Matus Telgarsky
The Optimal Approximation Factor in Density Estimation
Olivier Bousquet, Daniel Kane, Shay Moran
Theoretical guarantees for sampling and inference in generative models with latent diffusions
Belinda Tzen, Maxim Raginsky
The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling
Christopher Tosh, Sanjoy Dasgupta
Tight analyses for non-smooth stochastic gradient descent
Nicholas J. A. Harvey, Christopher Liaw, Yaniv Plan et al.
Towards Testing Monotonicity of Distributions Over General Posets
Maryam Aliakbarpour, Themis Gouleakis, John Peebles et al.
Uniform concentration and symmetrization for weak interactions
Andreas Maurer, Massimiliano Pontil
Universality of Computational Lower Bounds for Submatrix Detection
Matthew Brennan, Guy Bresler, Wasim Huleihel
VC Classes are Adversarially Robustly Learnable, but Only Improperly
Omar Montasser, Steve Hanneke, Nathan Srebro
Vortices Instead of Equilibria in MinMax Optimization: Chaos and Butterfly Effects of Online Learning in Zero-Sum Games
Yun Kuen Cheung, Georgios Piliouras
When can unlabeled data improve the learning rate?
Christina Göpfert, Shai Ben-David, Olivier Bousquet et al.
$\ell_1$ Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent
David Durfee, Kevin A. Lai, Saurabh Sawlani
Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent
Chi Jin, Praneeth Netrapalli, Michael I. Jordan
Accelerating Stochastic Gradient Descent for Least Squares Regression
Prateek Jain, Sham M. Kakade, Rahul Kidambi et al.
Action-Constrained Markov Decision Processes With Kullback-Leibler Cost
Ana Bušić, Sean Meyn
Actively Avoiding Nonsense in Generative Models
Steve Hanneke, Adam Tauman Kalai, Gautam Kamath et al.
Active Tolerant Testing
Avrim Blum, Lunjia Hu
Adaptivity to Smoothness in X-armed bandits
Andrea Locatelli, Alexandra Carpentier
A Data Prism: Semi-verified learning in the small-alpha regime
Michela Meister, Gregory Valiant
A Direct Sum Result for the Information Complexity of Learning
Ido Nachum, Jonathan Shafer, Amir Yehudayoff
A Faster Approximation Algorithm for the Gibbs Partition Function
Vladimir Kolmogorov
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation
Jalaj Bhandari, Daniel Russo, Raghav Singal
A General Approach to Multi-Armed Bandits Under Risk Criteria
Asaf Cassel, Shie Mannor, Assaf Zeevi