3 citations · 11 across the 11 of their papers we have counts for
7 papers · 1 filter
Fully First-Order Methods for Decentralized Bilevel Optimization
Xiaoyu Wang, Xuxing Chen, Shiqian Ma +1
This paper focuses on decentralized stochastic bilevel optimization (DSBO) where agents only communicate with their neighbors. We propose Decentralized Stochastic Gradient Descent…
Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization
Jiaxiang Li, Xuxing Chen, Shiqian Ma +1
Existing decentralized algorithms usually require knowledge of problem parameters for updating local iterates. For example, the hyperparameters (such as learning rate) usually requ…
Stochastic Nested Compositional Bi-level Optimization for Robust Feature Learning
Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi
We develop and analyze stochastic approximation algorithms for solving nested compositional bi-level optimization problems. These problems involve a nested composition of poten…
Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions
Xuxing Chen, Tesi Xiao, Krishnakumar Balasubramanian
Stochastic Bilevel optimization usually involves minimizing an upper-level (UL) function that is dependent on the arg-min of a strongly-convex lower-level (LL) function. Several al…
A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization
Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian +1
We focus on decentralized stochastic non-convex optimization, where agents work together to optimize a composite objective function which is a sum of a smooth term and a non-sm…
Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity
Xuxing Chen, Minhui Huang, Shiqian Ma +1
Bilevel optimization recently has received tremendous attention due to its great success in solving important machine learning problems like meta learning, reinforcement learning,…
Decentralized Bilevel Optimization
Xuxing Chen, Minhui Huang, Shiqian Ma
Bilevel optimization has been successfully applied to many important machine learning problems. Algorithms for solving bilevel optimization have been studied under various settings…