|
Workshop
|
|
Stochastic Adaptive Regularization Method with Cubics: A High Probability Complexity Bound
Katya Scheinberg · Miaolan Xie
|
|
|
Poster
|
Thu 9:00
|
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
Yiping Lu · Jose Blanchet · Lexing Ying
|
|
|
Workshop
|
Sat 9:30
|
Niao He, Simple Fixes for Adaptive Gradient Methods for Nonconvex Min-Max Optimization
Niao He
|
|
|
Workshop
|
|
Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization
Chris Junchi Li · Angela Yuan · Gauthier Gidel · Michael Jordan
|
|
|
Workshop
|
|
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods
Aleksandr Beznosikov · Eduard Gorbunov · Hugo Berard · Nicolas Loizou
|
|
|
Poster
|
|
A Unified Convergence Theorem for Stochastic Optimization Methods
Xiao Li · Andre Milzarek
|
|
|
Workshop
|
|
Quadratic minimization: from conjugate gradients to an adaptive heavy-ball method with Polyak step-sizes
Baptiste Goujaud · Adrien Taylor · Aymeric Dieuleveut
|
|
|
Workshop
|
Fri 6:30
|
Efficient Second-Order Stochastic Methods for Machine Learning
Donald Goldfarb
|
|
|
Poster
|
Thu 14:00
|
Recursive Reasoning in Minimax Games: A Level k Gradient Play Method
Zichu Liu · Lacra Pavel
|
|
|
Poster
|
Wed 14:00
|
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems
Pouria Mahdavinia · Yuyang Deng · Haochuan Li · Mehrdad Mahdavi
|
|
|
Poster
|
Tue 9:00
|
Stability and Generalization for Markov Chain Stochastic Gradient Methods
Puyu Wang · Yunwen Lei · Yiming Ying · Ding-Xuan Zhou
|
|
|
Poster
|
|
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
Xuanyuan Luo · Bei Luo · Jian Li
|
|
