4 papers
AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning
Zehui Tang, Yuchen Liu, Feihu Huang
Federated learning (FL) is a popular distributed learning paradigm in machine learning, which enables multiple clients to collaboratively train models under the guidance of a serve…
Faster Adaptive Decentralized Learning Algorithms
Feihu Huang, Jianyu Zhao
Decentralized learning recently has received increasing attention in machine learning due to its advantages in implementation simplicity and system robustness, data privacy. Meanwh…
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
Feihu Huang
Bilevel optimization is widely applied in many machine learning tasks such as hyper-parameter learning, meta learning and reinforcement learning. Although many algorithms recently…
Adaptive Mirror Descent Bilevel Optimization
Feihu Huang
In the paper, we propose a class of efficient adaptive bilevel methods based on mirror descent for nonconvex bilevel optimization, where its upper-level problem is nonconvex possib…