4 papers
Variance Reduction Based Experience Replay for Policy Optimization
Hua Zheng, Wei Xie, M. Ben Feng +1
Effective reinforcement learning (RL) for complex stochastic systems requires leveraging historical data to improve sample efficiency and accelerate policy optimization. However, c…
On the Convergence of Experience Replay in Policy Optimization: Characterizing Bias, Variance, and Finite-Time Convergence
Hua Zheng, Wei Xie, M. Ben Feng
Experience replay is a core ingredient of modern deep reinforcement learning, yet its benefits in policy optimization are poorly understood beyond empirical heuristics. This paper…
Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection
Katrina Chen, Mingbin Feng, Tony S. Wirjanto
Time series anomaly detection (TSAD) plays a vital role in many industrial applications. While contrastive learning has gained momentum in the time series domain for its prowess in…
Efficient Input Uncertainty Quantification for Ratio Estimator
Linyun He, Ben Feng, Eunhye Song
We study the construction of a confidence interval (CI) for a simulation output performance measure that accounts for input uncertainty when the input models are estimated from fin…