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math.OC2026
Newton Method for Fixed-Support Doubly Entropic Wasserstein Barycenter
Jianting Pan, Sirong Dai, Lei Yang +3
We study the fixed-support doubly regularized Wasserstein barycenter problem. Using the semi-dual formulation of entropic optimal transport, we reformulate the problem as a smooth,…
cs.LG2026
AdaGamma: State-Dependent Discounting for Temporal Adaptation in Reinforcement Learning
Yaomin Wang, Jianting Pan, Ran Tian +4
The discount factor in reinforcement learning controls both the effective planning horizon and the strength of bootstrapping, yet most deep RL methods use a single fixed value acro…
math.OC2026
Inexact Bregman Sparse Newton Method for Efficient Optimal Transport
Jianting Pan, Ji'an Li, Ming Yan +1
Computing exact optimal transport (OT) distances at large scale remains computationally challenging. Entropy-regularized OT can be solved efficiently, but its solution is biased to…