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cs.LG2026
K-Score: Kalman Filter as a Principled Alternative to Reward Normalization in Reinforcement Learning
Zixuan Xia, Quanxi Li
We propose a simple yet effective alternative to reward normalization in policy gradient reinforcement learning by integrating a 1D Kalman filter for online reward estimation. Inst…
cs.LG2025
KOALA++: Efficient Kalman-Based Optimization with Gradient-Covariance Products
Zixuan Xia, Aram Davtyan, Paolo Favaro
We propose KOALA++, a scalable Kalman-based optimization algorithm that explicitly models structured gradient uncertainty in neural network training. Unlike second-order methods, w…