activity
20192022
most citedInverse Reinforcement Learning with Missing Data

2 citations · 7 across the 7 of their papers we have counts for

collaborators

8 papers

cs.LG20221 cited

Imitating Opponent to Win: Adversarial Policy Imitation Learning in Two-player Competitive Games

The Viet Bui, Tien Mai, Thanh H. Nguyen

Recent research on vulnerabilities of deep reinforcement learning (RL) has shown that adversarial policies adopted by an adversary agent can influence a target RL agent (victim age…

cs.LG20221 cited

Scalable Distributional Robustness in a Class of Non Convex Optimization with Guarantees

Avinandan Bose, Arunesh Sinha, Tien Mai

Distributionally robust optimization (DRO) has shown lot of promise in providing robustness in learning as well as sample based optimization problems. We endeavor to provide DRO so…

econ.EM2022

Estimation of Recursive Route Choice Models with Incomplete Trip Observations

Tien Mai, The Viet Bui, Quoc Phong Nguyen +1

This work concerns the estimation of recursive route choice models in the situation that the trip observations are incomplete, i.e., there are unconnected links (or nodes) in the o…

cs.GT2022

Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach

Tien Mai, Arunesh Sinha

Vaccine delivery in under-resourced locations with security risks is not just challenging but also life threatening. The current COVID pandemic and the need to vaccinate have added…

math.OC20202 cited

A Relation Analysis of Markov Decision Process Frameworks

Tien Mai, Patrick Jaillet

We study the relation between different Markov Decision Process (MDP) frameworks in the machine learning and econometrics literatures, including the standard MDP, the entropy and g…

eess.SY20201 cited

Modeling Route Choice with Real-Time Information: Comparing the Recursive and Non-Recursive Models

Xinlian Yu, Tien Mai, Jing Ding-Mastera +2

We study the routing policy choice problems in a stochastic time-dependent (STD) network. A routing policy is defined as a decision rule applied at the end of each link that maps t…