8 citations · 8 across the 6 of their papers we have counts for
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stat.ML2026
Continuous-Time Trajectory Generation from Discrete Observations with Stochasticity
Ruifeng Shang, Shu Liu, Yuhua Zhu
Physical systems evolve continuously in time, yet their states are typically observed only at discrete times. Generating trajectories consistent with their probability densities fr…
stat.ML2025
Variance Reduction via Resampling and Experience Replay
Jiale Han, Xiaowu Dai, Yuhua Zhu
Experience replay is a foundational technique in reinforcement learning that enhances learning stability by storing past experiences in a replay buffer and reusing them during trai…
stat.ML2018★ 8 cited
Towards Theoretical Understanding of Large Batch Training in Stochastic Gradient Descent
Xiaowu Dai, Yuhua Zhu
Stochastic gradient descent (SGD) is almost ubiquitously used for training non-convex optimization tasks. Recently, a hypothesis proposed by Keskar et al. [2017] that large batch m…