3 papers
stat.ML2026
Sample Complexity of Average-Reward Q-Learning: From Single-agent to Federated Reinforcement Learning
Yuchen Jiao, Jiin Woo, Gen Li +2
Average-reward reinforcement learning offers a principled framework for long-term decision-making by maximizing the mean reward per time step. Although Q-learning is a widely used…
cs.LG2025
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization
Sudeep Salgia, Nikola Pavlovic, Yuejie Chi +1
We consider the problem of differentially private stochastic convex optimization (DP-SCO) in a distributed setting with clients, where each of them has a local dataset of i…
cs.LG2024
The Sample-Communication Complexity Trade-off in Federated Q-Learning
Sudeep Salgia, Yuejie Chi
We consider the problem of federated Q-learning, where agents aim to collaboratively learn the optimal Q-function of an unknown infinite-horizon Markov decision process with fi…