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math.OC2022★ 2 cited
On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games
Runyu Zhang, Jincheng Mei, Bo Dai +2
Softmax policy gradient is a popular algorithm for policy optimization in single-agent reinforcement learning, particularly since projection is not needed for each gradient update.…
math.OC2014★ 13 cited
Generalized Conditional Gradient for Sparse Estimation
Yaoliang Yu, Xinhua Zhang, Dale Schuurmans
Structured sparsity is an important modeling tool that expands the applicability of convex formulations for data analysis, however it also creates significant challenges for effici…