260 citations · 275 across the 7 of their papers we have counts for
7 papers
A Bayesian Approach to Robust Inverse Reinforcement Learning
Ran Wei, Siliang Zeng, Chenliang Li +3
We consider a Bayesian approach to offline model-based inverse reinforcement learning (IRL). The proposed framework differs from existing offline model-based IRL approaches by perf…
When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
Siliang Zeng, Chenliang Li, Alfredo Garcia +1
Offline inverse reinforcement learning (Offline IRL) aims to recover the structure of rewards and environment dynamics that underlie observed actions in a fixed, finite set of demo…
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees
Siliang Zeng, Chenliang Li, Alfredo Garcia +1
Inverse reinforcement learning (IRL) aims to recover the reward function and the associated optimal policy that best fits observed sequences of states and actions implemented by an…
Path-based Deep Network for Candidate Item Matching in Recommenders
Houyi Li, Zhihong Chen, Chenliang Li +5
The large-scale recommender system mainly consists of two stages: matching and ranking. The matching stage (also known as the retrieval step) identifies a small fraction of relevan…
Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders
Yu Duan, Canwen Xu, Jiaxin Pei +2
Conditional Text Generation has drawn much attention as a topic of Natural Language Generation (NLG) which provides the possibility for humans to control the properties of generate…
Targeted Sentiment Analysis: A Data-Driven Categorization
Jiaxin Pei, Aixin Sun, Chenliang Li
Targeted sentiment analysis (TSA), also known as aspect based sentiment analysis (ABSA), aims at detecting fine-grained sentiment polarity towards targets in a given opinion docume…
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi +1
With the development of high computational devices, deep neural networks (DNNs), in recent years, have gained significant popularity in many Artificial Intelligence (AI) applicatio…