3 citations · 9 across the 9 of their papers we have counts for
9 papers
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression
Sijin Chen, Zhize Li, Yuejie Chi
We consider the problem of finding second-order stationary points of heterogeneous federated learning (FL). Previous works in FL mostly focus on first-order convergence guarantees,…
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization
Cong Ma, Xingyu Xu, Tian Tong +1
Many problems encountered in science and engineering can be formulated as estimating a low-rank object (e.g., matrices and tensors) from incomplete, and possibly corrupted, linear…
Global Convergence of Policy Gradient Methods in Reinforcement Learning, Games and Control
Shicong Cen, Yuejie Chi
Policy gradient methods, where one searches for the policy of interest by maximizing the value functions using first-order information, become increasingly popular for sequential d…
A Lightweight Transformer for Faster and Robust EBSD Data Collection
Harry Dong, Sean Donegan, Megna Shah +1
Three dimensional electron back-scattered diffraction (EBSD) microscopy is a critical tool in many applications in materials science, yet its data quality can fluctuate greatly dur…
Offline Reinforcement Learning with On-Policy Q-Function Regularization
Laixi Shi, Robert Dadashi, Yuejie Chi +2
The core challenge of offline reinforcement learning (RL) is dealing with the (potentially catastrophic) extrapolation error induced by the distribution shift between the history d…
Understanding Masked Autoencoders via Hierarchical Latent Variable Models
Lingjing Kong, Martin Q. Ma, Guangyi Chen +4
Masked autoencoder (MAE), a simple and effective self-supervised learning framework based on the reconstruction of masked image regions, has recently achieved prominent success in…