Thompson Sampling for Combinatorial Multi-armed Bandit with Probabilistically Triggered Arms. - Alihan Hüyük; Cem Tekin (CoRR, 2018)

Analysis of Thompson Sampling for Combinatorial Multi-armed Bandit with Probabilistically Triggered Arms. - Alihan Hüyük; Cem Tekin (AISTATS, 2019)

Lexicographic Multiarmed Bandit. - Alihan Hüyük; Cem Tekin (CoRR, 2019)

Batch Inverse Reinforcement Learning Using Counterfactuals for Understanding Decision Making. - Ioana Bica; Daniel Jarrett; Alihan Hüyük; Mihaela van der Schaar (CoRR, 2020)

Thompson Sampling for Combinatorial Network Optimization in Unknown Environments. - Alihan Hüyük; Cem Tekin (IEEE/ACM Trans. Netw., 2020)

Learning "What-if" Explanations for Sequential Decision-Making. - Ioana Bica; Daniel Jarrett; Alihan Hüyük; Mihaela van der Schaar (ICLR, 2021)

Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning. - Alihan Hüyük; Daniel Jarrett; Cem Tekin; Mihaela van der Schaar (ICLR, 2021)

Inverse Decision Modeling: Learning Interpretable Representations of Behavior. - Daniel Jarrett; Alihan Hüyük; Mihaela van der Schaar (ICML, 2021)

The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. - Alex J. Chan; Ioana Bica; Alihan Hüyük; Daniel Jarrett; Mihaela van der Schaar (NeurIPS Datasets and Benchmarks, 2021)

Closing the loop in medical decision support by understanding clinical decision-making: A case study on organ transplantation. - Yuchao Qin; Fergus Imrie; Alihan Hüyük; Daniel Jarrett; Alexander Gimson; Mihaela van der Schaar (NeurIPS, 2021)

Multi-objective multi-armed bandit with lexicographically ordered and satisficing objectives. - Alihan Hüyük; Cem Tekin (Mach. Learn., 2021)

Inferring Lexicographically-Ordered Rewards from Preferences. - Alihan Hüyük; William R. Zame; Mihaela van der Schaar (AAAI, 2022)

Inverse Contextual Bandits: Learning How Behavior Evolves over Time. - Alihan Hüyük; Daniel Jarrett; Mihaela van der Schaar (ICML, 2022)

Online Decision Mediation. - Daniel Jarrett; Alihan Hüyük; Mihaela van der Schaar (NeurIPS, 2022)

Adaptively Identifying Patient Populations With Treatment Benefit in Clinical Trials. - Alicia Curth; Alihan Hüyük; Mihaela van der Schaar (CoRR, 2022)

MARS: Assisting Human with Information Processing Tasks Using Machine Learning. - Cong Shen 001; Zhaozhi Qian; Alihan Hüyük; Mihaela van der Schaar (ACM Trans. Comput. Heal., 2022)

Neural Laplace Control for Continuous-time Delayed Systems. - Samuel Holt; Alihan Hüyük; Zhaozhi Qian; Hao Sun 017; Mihaela van der Schaar (AISTATS, 2023)

When to Make and Break Commitments? - Alihan Hüyük; Zhaozhi Qian; Mihaela van der Schaar (ICLR, 2023)

Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions. - Alicia Curth; Alihan Hüyük; Mihaela van der Schaar (ICML, 2023)

Active Observing in Continuous-time Control. - Samuel Holt; Alihan Hüyük; Mihaela van der Schaar (NeurIPS, 2023)

Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples. - Hao Sun 017; Alihan Hüyük; Daniel Jarrett; Mihaela van der Schaar (NeurIPS, 2023)

Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning. - Alihan Hüyük; Daniel Jarrett; Mihaela van der Schaar (CoRR, 2023)

Optimising Human-AI Collaboration by Learning Convincing Explanations. - Alex J. Chan; Alihan Hüyük; Mihaela van der Schaar (CoRR, 2023)

When is Off-Policy Evaluation Useful? A Data-Centric Perspective. - Hao Sun 017; Alex J. Chan; Nabeel Seedat; Alihan Hüyük; Mihaela van der Schaar (CoRR, 2023)

Adaptive Experiment Design with Synthetic Controls. - Alihan Hüyük; Zhaozhi Qian; Mihaela van der Schaar (AISTATS, 2024)

Defining Expertise: Applications to Treatment Effect Estimation. - Alihan Hüyük; Qiyao Wei; Alicia Curth; Mihaela van der Schaar (ICLR, 2024)

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL. - Hao Sun 017; Alihan Hüyük; Mihaela van der Schaar (ICLR, 2024)

Disentangling Recognition and Decision Regrets in Image-Based Reinforcement Learning. - Alihan Hüyük; Arndt Ryo Koblitz; Atefeh Mohajeri; Matthew Andrews (CoRR, 2024)

Directly Optimizing Explanations for Desired Properties. - Hiwot Belay Tadesse; Alihan Hüyük; Weiwei Pan; Finale Doshi-Velez (CoRR, 2024)

Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions. - Omer Noy Klein; Alihan Hüyük; Ron Shamir; Uri Shalit; Mihaela van der Schaar (AISTATS, 2025)

Reasoning Elicitation in Language Models via Counterfactual Feedback. - Alihan Hüyük; Xinnuo Xu; Jacqueline R. M. A. Maasch; Aditya V. Nori; Javier González 002 (ICLR, 2025)

Transparent Trade-offs between Properties of Explanations. - Hiwot Belay Tadesse; Alihan Hüyük; Yaniv Yacoby; Weiwei Pan; Finale Doshi-Velez (UAI, 2025)

Compositional Causal Reasoning Evaluation in Language Models. - Jacqueline R. M. A. Maasch; Alihan Hüyük; Xinnuo Xu; Aditya V. Nori; Javier González 002 (CoRR, 2025)

Strategically Linked Decisions in Long-Term Planning and Reinforcement Learning. - Alihan Hüyük; Finale Doshi-Velez (CoRR, 2025)