research
∙
08/25/2022
Variance Reduction based Experience Replay for Policy Optimization
For reinforcement learning on complex stochastic systems where many fact...
share
research
∙
05/06/2022
Variance Reduction based Partial Trajectory Reuse to Accelerate Policy Gradient Optimization
We extend the idea underlying the success of green simulation assisted p...
research
∙
05/05/2022
Dynamic Bayesian Network Auxiliary ABC-SMC for Hybrid Model Bayesian Inference to Accelerate Biomanufacturing Process Mechanism Learning and Robust Control
Driven by the critical needs of biomanufacturing 4.0, we present a proba...
research
∙
01/10/2022
Opportunities of Hybrid Model-based Reinforcement Learning for Cell Therapy Manufacturing Process Development and Control
Driven by the key challenges of cell therapy manufacturing, including hi...
research
∙
12/15/2021
Is "my favorite new movie" my favorite movie? Probing the Understanding of Recursive Noun Phrases
Recursive noun phrases (NPs) have interesting semantic properties. For e...
research
∙
10/17/2021
Green Simulation Assisted Policy Gradient to Accelerate Stochastic Process Control
This study is motivated by the critical challenges in the biopharmaceuti...
research
∙
05/19/2021
Reinforcement Learning Assisted Oxygen Therapy for COVID-19 Patients Under Intensive Care
Patients with severe Coronavirus disease 19 (COVID-19) typically require...
research
∙
05/13/2021
Policy Optimization in Bayesian Network Hybrid Models of Biomanufacturing Processes
Biopharmaceutical manufacturing is a rapidly growing industry with impac...
research
∙
03/26/2021
Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehension
Conventional Machine Reading Comprehension (MRC) has been well-addressed...
research
∙
10/29/2020
Personalized Multimorbidity Management for Patients with Type 2 Diabetes Using Reinforcement Learning of Electronic Health Records
Comorbid chronic conditions are common among people with type 2 diabetes...
research
∙
09/27/2020
Inductively Representing Out-of-Knowledge-Graph Entities by Optimal Estimation Under Translational Assumptions
Conventional Knowledge Graph Completion (KGC) assumes that all test enti...
research
∙
06/17/2020
Green Simulation Assisted Reinforcement Learning with Model Risk for Biomanufacturing Learning and Control
Biopharmaceutical manufacturing faces critical challenges, including com...
research
∙
11/14/2019
Reinforcement Learning for Market Making in a Multi-agent Dealer Market
Market makers play an important role in providing liquidity to markets b...
research
∙
10/13/2019