89 citations · 264 across the 31 of their papers we have counts for
14 papers · 1 filter
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
Yuanying Cai, Chuheng Zhang, Li Zhao +6
We consider an offline reinforcement learning (RL) setting where the agent need to learn from a dataset collected by rolling out multiple behavior policies. There are two challenge…
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu +6
Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the tw…
SODA: A Natural Language Processing Package to Extract Social Determinants of Health for Cancer Studies
Zehao Yu, Xi Yang, Chong Dang +12
Objective: We aim to develop an open-source natural language processing (NLP) package, SODA (i.e., SOcial DeterminAnts), with pre-trained transformer models to extract social deter…
Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu +3
Modeling sequential patterns from data is at the core of various time series forecasting tasks. Deep learning models have greatly outperformed many traditional models, but these bl…
Variational Temporal Deconfounder for Individualized Treatment Effect Estimation from Longitudinal Observational Data
Zheng Feng, Mattia Prosperi, Jiang Bian
Estimating treatment effects, especially individualized treatment effects (ITE), using observational data is challenging due to the complex situations of confounding bias. Existing…
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
Tianping Zhang, Yizhuo Zhang, Wei Cao +4
Multivariate time series forecasting has seen widely ranging applications in various domains, including finance, traffic, energy, and healthcare. To capture the sophisticated tempo…