firstbacksecondback
132 Results
|
Poster
|
Wed 13:00 |
Estimating the Error of Randomized Newton Methods: A Bootstrap Approach Miles Lopes · Jessie X.T. Chen |
|
|
Poster
|
Wed 8:00 |
Optimal transport mapping via input convex neural networks Ashok Vardhan Makkuva · Amirhossein Taghvaei · Sewoong Oh · Jason Lee |
|
|
Poster
|
Thu 12:00 |
Conditional gradient methods for stochastically constrained convex minimization Maria-Luiza Vladarean · Ahmet Alacaoglu · Ya-Ping Hsieh · Volkan Cevher |
|
|
Poster
|
Thu 7:00 |
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data Di Wang · Hanshen Xiao · Srinivas Devadas · Jinhui Xu |
|
|
Poster
|
Tue 9:00 |
Nearly Linear Row Sampling Algorithm for Quantile Regression Yi Li · Ruosong Wang · Lin Yang · Hanrui Zhang |
|
|
Poster
|
Thu 6:00 |
Interpreting Robust Optimization via Adversarial Influence Functions Zhun Deng · Cynthia Dwork · Jialiang Wang · Linjun Zhang |
|
|
Poster
|
Tue 7:00 |
Differentiating through the Fréchet Mean Aaron Lou · Isay Katsman · Qingxuan Jiang · Serge Belongie · Ser Nam Lim · Christopher De Sa |
|
|
Poster
|
Thu 8:00 |
Coresets for Data-efficient Training of Machine Learning Models Baharan Mirzasoleiman · Jeff Bilmes · Jure Leskovec |
|
|
Poster
|
Wed 8:00 |
Online mirror descent and dual averaging: keeping pace in the dynamic case Huang Fang · Nick Harvey · Victor Sanches Portella · Michael Friedlander |
|
|
Poster
|
Tue 18:00 |
Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization Pan Zhou · Xiao-Tong Yuan |
|
|
Poster
|
Wed 12:00 |
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization Zhize Li · Dmitry Kovalev · Xun Qian · Peter Richtarik |
|
|
Poster
|
Tue 7:00 |
Self-Concordant Analysis of Frank-Wolfe Algorithms Pavel Dvurechenskii · Petr Ostroukhov · Kamil Safin · Shimrit Shtern · Mathias Staudigl |