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ORCIDCraig Boutilier
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- affiliation: University of Toronto, Canada
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2020 – today
- 2024
[j37]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): 20:1-20:57 (2024)- [j36]Christina Göpfert, Alex Haig, Chih-Wei Hsu, Yinlam Chow, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Hubert Pham, Mohammad Ghavamzadeh, Craig Boutilier:
Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors. Trans. Recomm. Syst. 2(4): 30:1-30:37 (2024) - [c183]Craig Boutilier, Martin Mladenov, Guy Tennenholtz:
Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization. AAAI 2024: 22575-22583 - [c182]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 - [c181]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: 2925-2929 - [i79]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 abs/2402.15957 (2024) - [i78]Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Ethan Liang, Craig Boutilier:
Embedding-Aligned Language Models. CoRR abs/2406.00024 (2024) - 2023
- [c180]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 - [c179]Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier:
Reinforcement Learning with History Dependent Dynamic Contexts. ICML 2023: 34011-34053 - [c178]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 - [c177]Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier:
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. NeurIPS 2023 - [i77]Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier:
Reinforcement Learning with History-Dependent Dynamic Contexts. CoRR abs/2302.02061 (2023) - [i76]Dhawal Gupta, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier:
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. CoRR abs/2302.10850 (2023) - [i75]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 abs/2302.12192 (2023) - [i74]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 abs/2305.16381 (2023) - [i73]Guy Tennenholtz, Martin Mladenov, Nadav Merlis, Craig Boutilier:
Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics. CoRR abs/2305.18333 (2023) - [i72]Siddharth Prasad, Martin Mladenov, Craig Boutilier:
Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems. CoRR abs/2309.00940 (2023) - [i71]Craig Boutilier, Martin Mladenov, Guy Tennenholtz:
Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models. CoRR abs/2309.06375 (2023) - [i70]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 abs/2310.04475 (2023) - [i69]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 abs/2310.06176 (2023) - [i68]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 abs/2310.20091 (2023) - [i67]Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier:
Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR abs/2311.02085 (2023) - 2022
- [c176]Filip Radlinski, Craig Boutilier, Deepak Ramachandran, Ivan Vendrov:
Subjective Attributes in Conversational Recommendation Systems: Challenges and Opportunities. AAAI 2022: 12287-12293 - [c175]Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier:
Thompson Sampling with a Mixture Prior. AISTATS 2022: 7565-7586 - [c174]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: 6:1-6:4 - [c173]Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier:
IMO^3: Interactive Multi-Objective Off-Policy Optimization. IJCAI 2022: 3523-3529 - [c172]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: 2411-2421 - [i66]Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier:
IMO3: Interactive Multi-Objective Off-Policy Optimization. CoRR abs/2201.09798 (2022) - [i65]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 abs/2202.02830 (2022) - [i64]Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier:
A Mixture-of-Expert Approach to RL-based Dialogue Management. CoRR abs/2206.00059 (2022) - [i63]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 abs/2207.10192 (2022) - [i62]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 abs/2208.02294 (2022) - [i61]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 A. Sloman, Shannon Vallor, Toby Walsh:
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. CoRR abs/2210.15767 (2022) - 2021
- [c171]Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári:
Meta-Thompson Sampling. ICML 2021: 5884-5893 - [c170]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. WWW 2021: 3872-3883 - [i60]Branislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári:
Meta-Thompson Sampling. CoRR abs/2102.06129 (2021) - [i59]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 abs/2103.08057 (2021) - [i58]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 abs/2105.02377 (2021) - [i57]Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier:
Thompson Sampling with a Mixture Prior. CoRR abs/2106.05608 (2021) - 2020
- [j35]Tyler Lu, Craig Boutilier:
Preference elicitation and robust winner determination for single- and multi-winner social choice. Artif. Intell. 279 (2020) - [j34]Paolo Viappiani, Craig Boutilier:
On the equivalence of optimal recommendation sets and myopically optimal query sets. Artif. Intell. 286: 103328 (2020) - [c169]Ivan Vendrov, Tyler Lu, Qingqing Huang, Craig Boutilier:
Gradient-Based Optimization for Bayesian Preference Elicitation. AAAI 2020: 10292-10301 - [c168]Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier:
Randomized Exploration in Generalized Linear Bandits. AISTATS 2020: 2066-2076 - [c167]Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier:
CAQL: Continuous Action Q-Learning. ICLR 2020 - [c166]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: 6987-6998 - [c165]Dijia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier:
ConQUR: Mitigating Delusional Bias in Deep Q-Learning. ICML 2020: 9187-9195 - [c164]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. IJCAI 2020: 2824-2830 - [c163]Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer:
Differentiable Meta-Learning of Bandit Policies. NeurIPS 2020 - [c162]Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier:
Latent Bandits Revisited. NeurIPS 2020 - [c161]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: 591-593 - [i56]Ge Liu, Rui Wu, Heng-Tze Cheng, Jing Wang, Jayden Ooi, Lihong Li, Ang Li, Wai Lok Sibon Li, Craig Boutilier, Ed H. Chi:
Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing. CoRR abs/2002.05229 (2020) - [i55]Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier:
BRPO: Batch Residual Policy Optimization. CoRR abs/2002.05522 (2020) - [i54]Craig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer:
Differentiable Bandit Exploration. CoRR abs/2002.06772 (2020) - [i53]Andy Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier:
ConQUR: Mitigating Delusional Bias in Deep Q-learning. CoRR abs/2002.12399 (2020) - [i52]Branislav Kveton, Martin Mladenov, Chih-Wei Hsu, Manzil Zaheer, Csaba Szepesvári, Craig Boutilier:
Differentiable Meta-Learning in Contextual Bandits. CoRR abs/2006.05094 (2020) - [i51]Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier:
Latent Bandits Revisited. CoRR abs/2006.08714 (2020) - [i50]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 abs/2008.00104 (2020) - [i49]Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier:
Non-Stationary Latent Bandits. CoRR abs/2012.00386 (2020)
2010 – 2019
- 2019
- [j33]Amirali Salehi-Abari, Craig Boutilier, Kate Larson:
Empathetic decision making in social networks. Artif. Intell. 275: 174-203 (2019) - [c160]Andrew Perrault, Craig Boutilier:
Experiential Preference Elicitation for Autonomous Heating and Cooling Systems. AAMAS 2019: 431-439 - [c159]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: 2592-2599 - [c158]Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier:
Perturbed-History Exploration in Stochastic Multi-Armed Bandits. IJCAI 2019: 2786-2793 - [c157]Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier:
Advantage Amplification in Slowly Evolving Latent-State Environments. IJCAI 2019: 3165-3172 - [c156]Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier:
Perturbed-History Exploration in Stochastic Linear Bandits. UAI 2019: 530-540 - [i48]Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier:
Perturbed-History Exploration in Stochastic Multi-Armed Bandits. CoRR abs/1902.10089 (2019) - [i47]Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier:
Perturbed-History Exploration in Stochastic Linear Bandits. CoRR abs/1903.09132 (2019) - [i46]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 abs/1905.12767 (2019) - [i45]Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier:
Advantage Amplification in Slowly Evolving Latent-State Environments. CoRR abs/1905.13559 (2019) - [i44]Branislav Kveton, Manzil Zaheer, Csaba Szepesvári, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier:
Randomized Exploration in Generalized Linear Bandits. CoRR abs/1906.08947 (2019) - [i43]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 abs/1909.04847 (2019) - [i42]Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier:
CAQL: Continuous Action Q-Learning. CoRR abs/1909.12397 (2019) - [i41]Ivan Vendrov, Tyler Lu, Qingqing Huang, Craig Boutilier:
Gradient-based Optimization for Bayesian Preference Elicitation. CoRR abs/1911.09153 (2019) - 2018
- [c155]Craig Boutilier:
Toward User-Centric Recommender Systems. AAMAS 2018: 2 - [c154]Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans:
Planning and Learning with Stochastic Action Sets. IJCAI 2018: 4674-4682 - [c153]Nevena Lazic, Craig Boutilier, Tyler Lu, Eehern Wong, Binz Roy, M. K. Ryu, Greg Imwalle:
Data center cooling using model-predictive control. NeurIPS 2018: 3818-3827 - [c152]Tyler Lu, Dale Schuurmans, Craig Boutilier:
Non-delusional Q-learning and value-iteration. NeurIPS 2018: 9971-9981 - [i40]Craig Boutilier, Alon Cohen, Amit Daniely, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans:
Planning and Learning with Stochastic Action Sets. CoRR abs/1805.02363 (2018) - [i39]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 abs/1810.02019 (2018) - 2017
- [c151]Andrew Perrault, Craig Boutilier:
Multiple-Profile Prediction-of-Use Games. AAMAS Workshops (Selected Papers) 2017: 275-295 - [c150]Andrew Perrault, Craig Boutilier:
Multiple-Profile Prediction-of-Use Games. AAMAS 2017: 1688-1690 - [c149]Andrew Perrault, Craig Boutilier:
Multiple-Profile Prediction-of-Use Games. IJCAI 2017: 366-373 - [c148]Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu:
Logistic Markov Decision Processes. IJCAI 2017: 2486-2493 - [i38]Tyler Lu, Martin Zinkevich, Craig Boutilier, Binz Roy, Dale Schuurmans:
Safe Exploration for Identifying Linear Systems via Robust Optimization. CoRR abs/1711.11165 (2017) - 2016
- [c147]Craig Boutilier, Tyler Lu:
Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes. UAI 2016 - [r1]Craig Boutilier, Jeffrey S. Rosenschein:
Incomplete Information and Communication in Voting. Handbook of Computational Social Choice 2016: 223-258 - 2015
- [j32]Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel D. Procaccia, Or Sheffet:
Optimal social choice functions: A utilitarian view. Artif. Intell. 227: 190-213 (2015) - [c146]Omer Lev, Joel Oren, Craig Boutilier, Jeffrey S. Rosenschein:
The Pricing War Continues: On Competitive Multi-Item Pricing. AAAI 2015: 972-978 - [c145]Tyler Lu, Craig Boutilier:
Value-Directed Compression of Large-Scale Assignment Problems. AAAI 2015: 1182-1190 - [c144]Xin Sui, Craig Boutilier:
Optimal Group Manipulation in Facility Location Problems. ADT 2015: 505-520 - [c143]Xin Sui, Craig Boutilier:
Approximately Strategy-proof Mechanisms for (Constrained) Facility Location. AAMAS 2015: 605-613 - [c142]Andrew Perrault, Craig Boutilier:
Approximately Stable Pricing for Coordinated Purchasing of Electricity. IJCAI 2015: 2624-2631 - [c141]Amirali Salehi-Abari, Craig Boutilier:
Preference-oriented Social Networks: Group Recommendation and Inference. RecSys 2015: 35-42 - [i37]Craig Boutilier, Britta Dorn, Nicolas Maudet, Vincent Merlin:
Computational Social Choice: Theory and Applications (Dagstuhl Seminar 15241). Dagstuhl Reports 5(6): 1-27 (2015) - 2014
- [j31]Reshef Meir, Tyler Lu, Moshe Tennenholtz, Craig Boutilier:
On the value of using group discounts under price competition. Artif. Intell. 216: 163-178 (2014) - [j30]Tyler Lu, Craig Boutilier:
Effective sampling and learning for mallows models with pairwise-preference data. J. Mach. Learn. Res. 15(1): 3783-3829 (2014) - [c140]Joanna Drummond, Craig Boutilier:
Preference Elicitation and Interview Minimization in Stable Matchings. AAAI 2014: 645-653 - [c139]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: 756-762 - [c138]Craig Boutilier, Jérôme Lang, Joel Oren, Héctor Palacios:
Robust Winners and Winner Determination Policies under Candidate Uncertainty. AAAI 2014: 1391-1397 - [c137]Joel Oren, Nina Narodytska, Craig Boutilier:
A Game-Theoretic Analysis of Catalog Optimization. AAAI 2014: 1463-1470 - [c136]Amirali Salehi-Abari, Craig Boutilier:
Empathetic social choice on social networks. AAMAS 2014: 693-700 - [c135]Andrew Perrault, Craig Boutilier:
Efficient coordinated power distribution on private infrastructure. AAMAS 2014: 805-812 - [i36]Omer Lev, Joel Oren, Craig Boutilier, Jeffrey S. Rosenschein:
The Pricing War Continues: On Competitive Multi-Item Pricing. CoRR abs/1408.0258 (2014) - 2013
- [c134]Reshef Meir, Tyler Lu, Moshe Tennenholtz, Craig Boutilier:
On the Value of Using Group Discounts under Price Competition. AAAI 2013: 683-689 - [c133]Joanna Drummond, Craig Boutilier:
Elicitation and Approximately Stable Matching with Partial Preferences. IJCAI 2013: 97-105 - [c132]Tyler Lu, Craig Boutilier:
Multi-Winner Social Choice with Incomplete Preferences. IJCAI 2013: 263-270 - [c131]Joel Oren, Yuval Filmus, Craig Boutilier:
Efficient Vote Elicitation under Candidate Uncertainty. IJCAI 2013: 309-316 - [c130]Xin Sui, Craig Boutilier, Tuomas Sandholm:
Analysis and Optimization of Multi-Dimensional Percentile Mechanisms. IJCAI 2013: 367-374 - [c129]Xin Sui, Alex Francois-Nienaber, Craig Boutilier:
Multi-Dimensional Single-Peaked Consistency and Its Approximations. IJCAI 2013: 375-382 - [i35]Craig Boutilier, Fahiem Bacchus, Ronen I. Brafman:
UCP-Networks: A Directed Graphical Representation of Conditional Utilities. CoRR abs/1301.2259 (2013) - [i34]Pascal Poupart, Craig Boutilier:
Vector-space Analysis of Belief-state Approximation for POMDPs. CoRR abs/1301.2304 (2013) - [i33]Pascal Poupart, Luis E. Ortiz, Craig Boutilier:
Value-Directed Sampling Methods for POMDPs. CoRR abs/1301.2305 (2013) - [i32]Craig Boutilier:
Approximately Optimal Monitoring of Plan Preconditions. CoRR abs/1301.3839 (2013) - [i31]Pascal Poupart, Craig Boutilier:
Value-Directed Belief State Approximation for POMDPs. CoRR abs/1301.3887 (2013) - [i30]Craig Boutilier, Ronen I. Brafman, Holger H. Hoos, David Poole:
Reasoning With Conditional Ceteris Paribus Preference Statem. CoRR abs/1301.6681 (2013) - [i29]Craig Boutilier, Moisés Goldszmidt, Bikash Sabata:
Continuous Value Function Approximation for Sequential Bidding Policies. CoRR abs/1301.6682 (2013) - [i28]Jesse Hoey, Robert St-Aubin, Alan J. Hu, Craig Boutilier:
SPUDD: Stochastic Planning using Decision Diagrams. CoRR abs/1301.6704 (2013) - [i27]