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ORCIDTien Mai
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2020 – today
- 2024
[c9]Huy Hoang, Tien Mai, Pradeep Varakantham
:
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning. AAAI 2024: 12439-12447- [c8]Hao Jiang, Tien Mai, Pradeep Varakantham, Huy Hoang:
Reward Penalties on Augmented States for Solving Richly Constrained RL Effectively. AAAI 2024: 19867-19875 - [i18]Huy Hoang, Tien Mai, Pradeep Varakantham:
SubIQ: Inverse Soft-Q Learning for Offline Imitation with Suboptimal Demonstrations. CoRR abs/2402.13147 (2024) - [i17]Hoang Giang Pham, Tien Thanh Dam, Ngan Ha Duong, Tien Mai, Minh Hoàng Hà:
Competitive Facility Location under Random Utilities and Routing Constraints. CoRR abs/2403.04264 (2024) - [i16]Hoang Giang Pham, Tien Mai:
Outer Approximation and Super-modular Cuts for Constrained Assortment Optimization under Mixed-Logit Model. CoRR abs/2407.18532 (2024) - 2023
- [j8]Ngan Ha Duong, Tien Thanh Dam, Thuy Anh Ta, Tien Mai:
Joint location and cost planning in maximum capture facility location under random utilities. Comput. Oper. Res. 159: 106336 (2023) - [j7]Tien Thanh Dam, Thuy Anh Ta, Tien Mai:
Robust maximum capture facility location under random utility maximization models. Eur. J. Oper. Res. 310(3): 1128-1150 (2023) - [c7]Tien Mai, Arunesh Sinha:
Securing Lifelines: Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach. AAAI 2023: 5805-5813 - [c6]Avinandan Bose, Tracey Li, Arunesh Sinha, Tien Mai:
A Fair Incentive Scheme for Community Health Workers. AAAI 2023: 14127-14135 - [c5]Viet The Bui, Tien Mai:
Imitation Improvement Learning for Large-Scale Capacitated Vehicle Routing Problems. ICAPS 2023: 551-559 - [c4]The Viet Bui, Tien Mai, Thanh Hong Nguyen:
Imitating Opponent to Win: Adversarial Policy Imitation Learning in Two-player Competitive Games. AAMAS 2023: 1285-1293 - [i15]Hao Jiang, Tien Mai, Pradeep Varakantham:
Solving Constrained Reinforcement Learning through Augmented State and Reward Penalties. CoRR abs/2301.11592 (2023) - [i14]Tien Mai, Avinandan Bose, Arunesh Sinha, Thanh Hong Nguyen:
Tackling Stackelberg Network Interdiction against a Boundedly Rational Adversary. CoRR abs/2301.12232 (2023) - [i13]The Viet Bui, Tien Mai, Thanh Hong Nguyen:
Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Competitive Games. CoRR abs/2308.10188 (2023) - [i12]The Viet Bui, Tien Mai, Thanh Hong Nguyen:
Inverse Factorized Q-Learning for Cooperative Multi-agent Imitation Learning. CoRR abs/2310.06801 (2023) - [i11]Huy Hoang, Tien Mai, Pradeep Varakantham:
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning. CoRR abs/2312.10385 (2023) - 2022
- [j6]Tien Thanh Dam, Thuy Anh Ta, Tien Mai:
Submodularity and local search approaches for maximum capture problems under generalized extreme value models. Eur. J. Oper. Res. 300(3): 953-965 (2022) - [j5]Tien Thanh Dam, Thuy Anh Ta, Tien Mai:
Joint chance-constrained staffing optimization in multi-skill call centers. J. Comb. Optim. 44(1): 354-378 (2022) - [j4]Tien Mai, Emma Frejinger:
Undiscounted Recursive Path Choice Models: Convergence Properties and Algorithms. Transp. Sci. 56(6): 1469-1482 (2022) - [c3]Tien Mai, Arunesh Sinha:
Choices Are Not Independent: Stackelberg Security Games with Nested Quantal Response Models. AAAI 2022: 5141-5149 - [c2]Avinandan Bose, Arunesh Sinha, Tien Mai:
Scalable Distributional Robustness in a Class of Non-Convex Optimization with Guarantees. NeurIPS 2022 - [c1]Thuy Anh Ta, Tien Mai, Fabian Bastin, Pierre L'Ecuyer:
A Logistic Regression and Linear Programming Approach for Multi-Skill Staffing Optimization in Call Centers. WSC 2022: 3087-3098 - [i10]Tien Mai, Arunesh Sinha:
Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach. CoRR abs/2204.11451 (2022) - [i9]Avinandan Bose, Arunesh Sinha, Tien Mai:
Scalable Distributional Robustness in a Class of Non Convex Optimization with Guarantees. CoRR abs/2205.15624 (2022) - [i8]The Viet Bui, Tien Mai, Patrick Jaillet:
Weighted Maximum Entropy Inverse Reinforcement Learning. CoRR abs/2208.09611 (2022) - [i7]The Viet Bui, Tien Mai, Thanh Hong Nguyen:
Imitating Opponent to Win: Adversarial Policy Imitation Learning in Two-player Competitive Games. CoRR abs/2210.16915 (2022) - 2021
- [j3]Thuy Anh Ta, Tien Mai, Fabian Bastin, Pierre L'Ecuyer:
On a multistage discrete stochastic optimization problem with stochastic constraints and nested sampling. Math. Program. 190(1): 1-37 (2021) - [i6]Tien Mai, Patrick Jaillet:
Robust Entropy-regularized Markov Decision Processes. CoRR abs/2112.15364 (2021) - 2020
- [j2]Tien Mai, Andrea Lodi:
A multicut outer-approximation approach for competitive facility location under random utilities. Eur. J. Oper. Res. 284(3): 874-881 (2020) - [i5]Xinlian Yu, Tien Mai, Jing Ding-Mastera, Song Gao, Emma Frejinger:
Modeling Route Choice with Real-Time Information: Comparing the Recursive and Non-Recursive Models. CoRR abs/2005.05783 (2020) - [i4]Tien Mai, Patrick Jaillet:
A Relation Analysis of Markov Decision Process Frameworks. CoRR abs/2008.07820 (2020)
2010 – 2019
- 2019
- [i3]Tien Mai, Kennard Chan, Patrick Jaillet:
Generalized Maximum Causal Entropy for Inverse Reinforcement Learning. CoRR abs/1911.06928 (2019) - [i2]Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet:
Inverse Reinforcement Learning with Missing Data. CoRR abs/1911.06930 (2019) - [i1]Tien Mai, Patrick Jaillet:
Robust Multi-product Pricing under General Extreme Value Models. CoRR abs/1912.09552 (2019) - 2018
- [j1]Tien Mai, Fabian Bastin, Emma Frejinger:
A decomposition method for estimating recursive logit based route choice models. EURO J. Transp. Logist. 7(3): 253-275 (2018)
Coauthor Index
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last updated on 2024-10-07 01:24 CEST by the dblp team
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