3 papers
cs.LG2026
Federated stochastic bilevel optimization with fully first-order gradients
Yihan Zhang, Rohit Dhaipule, Chiu C Tan +2
Federated stochastic bilevel optimization has been actively studied in recent years due to its widespread applications in machine learning. However, most existing federated stochas…
cs.LG2025
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.LG2023
Decentralized Multi-Level Compositional Optimization Algorithms with Level-Independent Convergence Rate
Hongchang Gao
Stochastic multi-level compositional optimization problems cover many new machine learning paradigms, e.g., multi-step model-agnostic meta-learning, which require efficient optimiz…