2 papers
cs.LG2026
Probabilistic Smoothing with Ratio-Monotone Transforms for Global Optimization
Kukyoung Jang, Taehyun Cho, Junrui Zhang +2
Probabilistic smoothing is a standard tool for global optimization, but existing methods rely on Gaussian kernels and specific transforms, often resulting in strong hyperparameter…
cs.LG2026
DFedReweighting: A Unified Framework for Objective-Oriented Reweighting in Decentralized Federated Learning
Kaichuang Zhang, Wei Yin, Jinghao Yang +1
Decentralized federated learning (DFL) has emerged as a promising paradigm that enables multiple clients to collaboratively train machine learning models through iterative rounds o…