19 citations · 21 across the 7 of their papers we have counts for
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cs.LG2026
Ratio-Variance Regularized Policy Optimization
Yu Luo, Shuo Han, Yihan Hu +5
Standard on-policy reinforcement learning relies on heuristic clipping to enforce trust regions, but this mechanism imposes a severe cost by indiscriminately truncating high-return…
cs.LG2024
Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks
Jialin Zhao, Yingtao Zhang, Xinghang Li +2
The growing demands on GPU memory posed by the increasing number of neural network parameters call for training approaches that are more memory-efficient. Previous memory reduction…