Papers
1,396 papers found
Faster Algorithms for High-Dimensional Robust Covariance Estimation
Yu Cheng, Ilias Diakonikolas, Rong Ge et al.
Fast Mean Estimation with Sub-Gaussian Rates
Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett
Finite-Time Error Bounds For Linear Stochastic Approximation andTD Learning
R. Srikant, Lei Ying
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric et al.
Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression
Jeongyeol Kwon, Wei Qian, Constantine Caramanis et al.
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds
Santosh Vempala, John Wilmes
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate
Vitaly Feldman, Jan Vondrak
How do infinite width bounded norm networks look in function space?
Pedro Savarese, Itay Evron, Daniel Soudry et al.
How Hard is Robust Mean Estimation?
Samuel B. Hopkins, Jerry Li
Improved Path-length Regret Bounds for Bandits
Sébastien Bubeck, Yuanzhi Li, Haipeng Luo et al.
Inference under Information Constraints: Lower Bounds from Chi-Square Contraction
Jayadev Acharya, Clément L Canonne, Himanshu Tyagi
Is your function low dimensional?
Anindya De, Elchanan Mossel, Joe Neeman
Learning from Weakly Dependent Data under Dobrushin’s Condition
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala et al.
Learning in Non-convex Games with an Optimization Oracle
Naman Agarwal, Alon Gonen, Elad Hazan
Learning Ising Models with Independent Failures
Surbhi Goel, Daniel M. Kane, Adam R. Klivans
Learning Linear Dynamical Systems with Semi-Parametric Least Squares
Max Simchowitz, Ross Boczar, Benjamin Recht
Learning Neural Networks with Two Nonlinear Layers in Polynomial Time
Surbhi Goel, Adam R. Klivans
Learning rates for Gaussian mixtures under group action
Victor-Emmanuel Brunel
Learning to Prune: Speeding up Repeated Computations
Daniel Alabi, Adam Tauman Kalai, Katrina Liggett et al.
Learning Two Layer Rectified Neural Networks in Polynomial Time
Ainesh Bakshi, Rajesh Jayaram, David P Woodruff
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning
Zakaria Mhammedi, Wouter M Koolen, Tim Van Erven
Lower Bounds for Locally Private Estimation via Communication Complexity
John Duchi, Ryan Rogers
Lower Bounds for Parallel and Randomized Convex Optimization
Jelena Diakonikolas, Cristóbal Guzmán
Lower bounds for testing graphical models: colorings and antiferromagnetic Ising models
Ivona Bezáková, Antonio Blanca, Zongchen Chen et al.
Making the Last Iterate of SGD Information Theoretically Optimal
Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli