Craig Boutilier

ORCID

Publication Activity (10 Years)

Years Active: 1989-2024
Publications (10 Years): 83

Top Venues

Publications

Craig Boutilier, Martin Mladenov, Guy Tennenholtz
Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization. AAAI (2024)
Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
Demystifying Embedding Spaces using Large Language Models. ICLR (2024)
Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Chloé Bakalar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Xian Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis. Trans. Recomm. Syst. 2 (3) (2024)
Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. CoRR (2024)
Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Ethan Liang, Craig Boutilier
Embedding-Aligned Language Models. CoRR (2024)
Chih-Wei Hsu, Martin Mladenov, Ofer Meshi, James Pine, Hubert Pham, Shane Li, Xujian Liang, Anton Polishko, Li Yang, Ben Scheetz, Craig Boutilier
Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies. SIGIR (2024)
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. CoRR (2023)
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee
Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models. NeurIPS (2023)
Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
Demystifying Embedding Spaces using Large Language Models. CoRR (2023)
Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
A Mixture-of-Expert Approach to RL-based Dialogue Management. ICLR (2023)
Dhawal Gupta, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. CoRR (2023)
Guy Tennenholtz, Martin Mladenov, Nadav Merlis, Craig Boutilier
Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics. CoRR (2023)
Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier
Reinforcement Learning with History-Dependent Dynamic Contexts. CoRR (2023)
Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue Liu, Craig Boutilier, Maryam Karimzadehgan
Density-based User Representation through Gaussian Process Regression for Multi-interest Personalized Retrieval. CoRR (2023)
Siddharth Prasad, Martin Mladenov, Craig Boutilier
Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems. CoRR (2023)
Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier
Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR (2023)
Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. NeurIPS (2023)
Craig Boutilier, Martin Mladenov, Guy Tennenholtz
Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models. CoRR (2023)
Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier
Reinforcement Learning with History Dependent Dynamic Contexts. ICML (2023)
Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Shixiang Shane Gu
Aligning Text-to-Image Models using Human Feedback. CoRR (2023)
Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
Factual and Personalized Recommendations using Language Models and Reinforcement Learning. CoRR (2023)
Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller, Ido Greenberg, Avinatan Hassidim, Michael Fink, Yossi Matias, Idan Szpektor, Craig Boutilier, Gal Elidan
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning. CoRR (2022)
Martin Mladenov, Sanjay Ganapathy Subramaniam, Chih-Wei Hsu, Neha Arora, Andrew Tomkins, Craig Boutilier, Carolina Osorio
An adversarial variational inference approach for travel demand calibration of urban traffic simulators. SIGSPATIAL/GIS (2022)
Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. WWW (2022)
Michael L. Littman, Ifeoma Ajunwa, Guy Berger, Craig Boutilier, Morgan Currie, Finale Doshi-Velez, Gillian K. Hadfield, Michael C. Horowitz, Charles Isbell, Hiroaki Kitano, Karen Levy, Terah Lyons, Melanie Mitchell, Julie Shah, Steven Sloman, Shannon Vallor, Toby Walsh
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. CoRR (2022)
Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier
IMO^3: Interactive Multi-Objective Off-Policy Optimization. IJCAI (2022)
Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
A Mixture-of-Expert Approach to RL-based Dialogue Management. CoRR (2022)
Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. CoRR (2022)
Filip Radlinski, Craig Boutilier, Deepak Ramachandran, Ivan Vendrov
Subjective Attributes in Conversational Recommendation Systems: Challenges and Opportunities. AAAI (2022)
Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
Thompson Sampling with a Mixture Prior. AISTATS (2022)
Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier
: Interactive Multi-Objective Off-Policy Optimization. CoRR (2022)
Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy X. Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis. CoRR (2022)
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. CoRR (2021)
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári
Meta-Thompson Sampling. CoRR (2021)
Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
Thompson Sampling with a Mixture Prior. CoRR (2021)
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed Chi, Minmin Chen
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. WWW (2021)
Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári
Meta-Thompson Sampling. ICML (2021)
Martin Mladenov, Chih-Wei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov, Craig Boutilier
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems. CoRR (2021)
Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard S. Zemel, Craig Boutilier
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. CoRR (2020)
Dijia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier
ConQUR: Mitigating Delusional Bias in Deep Q-Learning. ICML (2020)
Paolo Viappiani, Craig Boutilier
On the equivalence of optimal recommendation sets and myopically optimal query sets. Artif. Intell. 286 (2020)
Martin Mladenov, Chih-Wei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov, Craig Boutilier
Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG. RecSys (2020)
Ge Liu, Rui Wu, Heng-Tze Cheng, Jing Wang, Jayden Ooi, Lihong Li, Ang Li, Wai Lok Sibon Li, Craig Boutilier, Ed Chi
Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing. CoRR (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier
Non-Stationary Latent Bandits. CoRR (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
Latent Bandits Revisited. CoRR (2020)
Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer
Differentiable Meta-Learning of Bandit Policies. NeurIPS (2020)
Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier
CAQL: Continuous Action Q-Learning. ICLR (2020)
Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
Randomized Exploration in Generalized Linear Bandits. AISTATS (2020)
Ivan Vendrov, Tyler Lu, Qingqing Huang, Craig Boutilier
Gradient-Based Optimization for Bayesian Preference Elicitation. AAAI (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
Latent Bandits Revisited. NeurIPS (2020)
Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard S. Zemel, Craig Boutilier
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. ICML (2020)
Branislav Kveton, Martin Mladenov, Chih-Wei Hsu, Manzil Zaheer, Csaba Szepesvári, Craig Boutilier
Differentiable Meta-Learning in Contextual Bandits. CoRR (2020)
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier
BRPO: Batch Residual Policy Optimization. IJCAI (2020)
Andy Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier
ConQUR: Mitigating Delusional Bias in Deep Q-learning. CoRR (2020)
Tyler Lu, Craig Boutilier
Preference elicitation and robust winner determination for single- and multi-winner social choice. Artif. Intell. 279 (2020)
Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer
Differentiable Bandit Exploration. CoRR (2020)
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier
BRPO: Batch Residual Policy Optimization. CoRR (2020)
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
Perturbed-History Exploration in Stochastic Linear Bandits. CoRR (2019)
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
Perturbed-History Exploration in Stochastic Linear Bandits. UAI (2019)
Amirali Salehi-Abari, Craig Boutilier, Kate Larson
Empathetic decision making in social networks. Artif. Intell. 275 (2019)
Eugene Ie, Chih-Wei Hsu, Martin Mladenov, Vihan Jain, Sanmit Narvekar, Jing Wang, Rui Wu, Craig Boutilier
RecSim: A Configurable Simulation Platform for Recommender Systems. CoRR (2019)
Eugene Ie, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Tushar Chandra, Craig Boutilier
SlateQ: A Tractable Decomposition for Reinforcement Learning with Recommendation Sets. IJCAI (2019)
Ivan Vendrov, Tyler Lu, Qingqing Huang, Craig Boutilier
Gradient-based Optimization for Bayesian Preference Elicitation. CoRR (2019)
Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier
Advantage Amplification in Slowly Evolving Latent-State Environments. CoRR (2019)
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
Perturbed-History Exploration in Stochastic Multi-Armed Bandits. IJCAI (2019)
Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier
CAQL: Continuous Action Q-Learning. CoRR (2019)
Andrew Perrault, Craig Boutilier
Experiential Preference Elicitation for Autonomous Heating and Cooling Systems. AAMAS (2019)
Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier
Advantage Amplification in Slowly Evolving Latent-State Environments. IJCAI (2019)
Eugene Ie, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Morgane Lustman, Vince Gatto, Paul Covington, Jim McFadden, Tushar Chandra, Craig Boutilier
Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology. CoRR (2019)
Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
Randomized Exploration in Generalized Linear Bandits. CoRR (2019)
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier
Perturbed-History Exploration in Stochastic Multi-Armed Bandits. CoRR (2019)
Tyler Lu, Dale Schuurmans, Craig Boutilier
Non-delusional Q-learning and value-iteration. NeurIPS (2018)
Craig Boutilier, Alon Cohen, Amit Daniely, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans
Planning and Learning with Stochastic Action Sets. CoRR (2018)
Craig Boutilier
Toward User-Centric Recommender Systems. AAMAS (2018)
Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans
Planning and Learning with Stochastic Action Sets. IJCAI (2018)
Nevena Lazic, Craig Boutilier, Tyler Lu, Eehern Wong, Binz Roy, M. K. Ryu, Greg Imwalle
Data center cooling using model-predictive control. NeurIPS (2018)
Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Huai-hsin Chi, Elad Eban, Xiyang Luo, Alan Mackey, Ofer Meshi
Seq2Slate: Re-ranking and Slate Optimization with RNNs. CoRR (2018)
Andrew Perrault, Craig Boutilier
Multiple-Profile Prediction-of-Use Games. IJCAI (2017)
Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu
Logistic Markov Decision Processes. IJCAI (2017)
Tyler Lu, Martin Zinkevich, Craig Boutilier, Binz Roy, Dale Schuurmans
Safe Exploration for Identifying Linear Systems via Robust Optimization. CoRR (2017)
Andrew Perrault, Craig Boutilier
Multiple-Profile Prediction-of-Use Games. AAMAS Workshops (Selected Papers) (2017)
Andrew Perrault, Craig Boutilier
Multiple-Profile Prediction-of-Use Games. AAMAS (2017)
Craig Boutilier, Tyler Lu
Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes. UAI (2016)
Tyler Lu, Craig Boutilier
Value-Directed Compression of Large-Scale Assignment Problems. AAAI (2015)
Craig Boutilier, Britta Dorn, Nicolas Maudet, Vincent Merlin
Computational Social Choice: Theory and Applications (Dagstuhl Seminar 15241). Dagstuhl Reports 5 (6) (2015)
Xin Sui, Craig Boutilier
Approximately Strategy-proof Mechanisms for (Constrained) Facility Location. AAMAS (2015)
Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel D. Procaccia, Or Sheffet
Optimal social choice functions: A utilitarian view. Artif. Intell. 227 (2015)
Amirali Salehi-Abari, Craig Boutilier
Preference-oriented Social Networks: Group Recommendation and Inference. RecSys (2015)
Andrew Perrault, Craig Boutilier
Approximately Stable Pricing for Coordinated Purchasing of Electricity. IJCAI (2015)
Xin Sui, Craig Boutilier
Optimal Group Manipulation in Facility Location Problems. ADT (2015)
Omer Lev, Joel Oren, Craig Boutilier, Jeffrey S. Rosenschein
The Pricing War Continues: On Competitive Multi-Item Pricing. AAAI (2015)
Andrew Perrault, Craig Boutilier
Efficient coordinated power distribution on private infrastructure. AAMAS (2014)
Reshef Meir, Tyler Lu, Moshe Tennenholtz, Craig Boutilier
On the value of using group discounts under price competition. Artif. Intell. 216 (2014)
Joanna Drummond, Craig Boutilier
Preference Elicitation and Interview Minimization in Stable Matchings. AAAI (2014)
Craig Boutilier, Jérôme Lang, Joel Oren, Héctor Palacios
Robust Winners and Winner Determination Policies under Candidate Uncertainty. AAAI (2014)
Tyler Lu, Craig Boutilier
Effective sampling and learning for mallows models with pairwise-preference data. J. Mach. Learn. Res. 15 (1) (2014)
Thanh Hong Nguyen, Amulya Yadav, Bo An, Milind Tambe, Craig Boutilier
Regret-Based Optimization and Preference Elicitation for Stackelberg Security Games with Uncertainty. AAAI (2014)
Joel Oren, Nina Narodytska, Craig Boutilier
A Game-Theoretic Analysis of Catalog Optimization. AAAI (2014)
Amirali Salehi-Abari, Craig Boutilier
Empathetic social choice on social networks. AAMAS (2014)
Omer Lev, Joel Oren, Craig Boutilier, Jeffrey S. Rosenschein
The Pricing War Continues: On Competitive Multi-Item Pricing. CoRR (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Craig Boutilier