3 papers
cs.LG2026
Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noise
Xinwen Zhang, Yihan Zhang, Heng Liang +1
Existing decentralized stochastic optimization methods assume the lower-level loss function is strongly convex and the stochastic gradient noise has finite variance. These strong a…
cs.LG2025
Federated Stochastic Minimax Optimization under Heavy-Tailed Noises
Xinwen Zhang, Hongchang Gao
Heavy-tailed noise has attracted growing attention in nonconvex stochastic optimization, as numerous empirical studies suggest it offers a more realistic assumption than standard b…
cs.LG2025
On Provable Benefits of Muon in Federated Learning
Xinwen Zhang, Hongchang Gao
The recently introduced optimizer, Muon, has gained increasing attention due to its superior performance across a wide range of applications. However, its effectiveness in federate…