Atia, George K.

13 publications

ICML 2025 A Reduction Framework for Distributionally Robust Reinforcement Learning Under Average Reward Zachary Andrew Roch, George K. Atia, Yue Wang

AAAI 2025 Align-Pro: A Principled Approach to Prompt Optimization for LLM Alignment Prashant Trivedi, Souradip Chakraborty, Avinash Reddy, Vaneet Aggarwal, Amrit Singh Bedi, George K. Atia

ICLR 2025 Model-Free Offline Reinforcement Learning with Enhanced Robustness Chi Zhang, Zain Ulabedeen Farhat, George K. Atia, Yue Wang

ICML 2025 Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning Chi Zhang, Ziying Jia, George K. Atia, Sihong He, Yue Wang

JAIR 2024 Robust Average-Reward Reinforcement Learning Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou

ICML 2023 Model-Free Robust Average-Reward Reinforcement Learning Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou

AAAI 2023 Robust Average-Reward Markov Decision Processes Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou

UAI 2023 Scalable and Robust Tensor Ring Decomposition for Large-Scale Data Yicong He, George K. Atia

AAAI 2022 Multi-Mode Tensor Space Clustering Based on Low-Tensor-Rank Representation Yicong He, George K. Atia

AAAI 2021 Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search Alvaro Velasquez, Brett Bissey, Lior Barak, Andre Beckus, Ismail Alkhouri, Daniel Melcer, George K. Atia

JAIR 2021 Steady-State Planning in Expected Reward Multichain MDPs George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez

IJCAI 2020 Steady-State Policy Synthesis in Multichain Markov Decision Processes George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez

ICCVW 2017 Robust and Scalable Column/Row Sampling from Corrupted Big Data Mostafa Rahmani, George K. Atia