Stochastic approximation with multiple coupled sequences (MSA) has found...
Invariant risk minimization (IRM) has received increasing attention as a...
Minimax optimization has seen a surge in interest with the advent of mod...
Data-heterogeneous federated learning (FL) systems suffer from two
signi...
Since reinforcement learning algorithms are notoriously data-intensive, ...
In this paper, we consider nonconvex minimax optimization, which is gain...
Federated Learning (FL) refers to the paradigm where multiple worker nod...
In this work, we focus on the study of stochastic zeroth-order (ZO)
opti...
In this work, we propose a distributed algorithm for stochastic non-conv...
In this work, we consider a distributed online convex optimization probl...
In this paper, we propose a distributed algorithm for stochastic smooth,...
In this work, we consider the distributed stochastic optimization proble...
As artificial intelligence is increasingly affecting all parts of societ...