Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li, Yu Lu, Denny Zhou
Proceedings of the 34th International Conference on Machine Learning (ICML) | August 2017
论文与出版物
按年份分类的论文与出版物
-
-
Click-based Hot Fixes for Underperforming Torso Queries
Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, Maarten de Rijke
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | July 2016
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
On the Prior Sensitivity of Thompson Sampling
Lihong Li
Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT) | June 2016
Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT)
Online Evaluation for Information Retrieval
Katja Hofmann, Lihong Li, Filip Radlinski
Foundations and Trends® in Information Retrieval | June 2016, 第 10 卷: pp. 1-117
An Efficient Algorithm for Contextual Bandits with Knapsacks, and an Extension to Concave Objectives
Shipra Agrawal, Nikhil Devanur, Lihong Li
Proceedings of the 29th Conference on Learning Theory (COLT) - JMLR: Workshop and Conference Proceedings | June 2016
Doubly Robust Off-policy Evaluation for Reinforcement Learning
Nan Jiang, Lihong Li
JMLR: Workshop and Conference Proceedings; Proceedings of the 33rd International Conference on Machine Learning (ICML) | June 2016
-
Doubly Robust Off-policy Evaluation for Reinforcement Learning
Nan Jiang, Lihong Li
MSR-TR-2015-86 | November 2015
Counterfactual Estimation and Optimization of Click Metrics in Search Engines: A Case Study
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
Proceedings of the 24th International World Wide Web Conference (WWW'14), Companion Volume | May 2015
Evaluation of Explore-Exploit Policies in Multi-result Ranking Systems
Dragomir Yankov, Pavel Berkhin, Lihong Li
MSR-TR-2015-34 | May 2015
Toward Minimax Off-policy Value Estimation
Lihong Li, Remi Munos, Csaba Szepesvari
Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) | May 2015
Truthful Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
Journal of the ACM (JACM) | May 2015, 第 62 卷(2)
Offline Evaluation and Optimization for Interactive Systems
Lihong Li
Proceedings of the 8th ACM International Conference on Web Search and Data Mining | February 2015
Proceedings of the 8th ACM International Conference on Web Search and Data Mining
Toward Predicting the Outcome of an A/B Experiment for Search Relevance
Lihong Li, Imed Zitouni, Jin Young Kim
Proceedings of the 8th ACM International Conference on Web Search and Data Mining | February 2015
Proceedings of the 8th ACM International Conference on Web Search and Data Mining
-
Doubly Robust Policy Evaluation and Optimization
Miro Dudík, Dumitru Erhan, John Langford, Lihong Li
Statistical Science | November 2014
On Minimax Optimal Offline Policy Evaluation
Lihong Li
MSR-TR-2014-124 | September 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
The 31st International Conference on Machine Learning (ICML 2014) | June 2014
Counterfactual Estimation and Optimization of Click Metrics for Search Engines
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
MSR-TR-2014-32 | March 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hus, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
MSR-TR-2014-33 | February 2014
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
15th ACM Conf. on Economics and Computation (EC) | January 2014
-
Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
Aleksandrs Slivkins, Jennifer Wortman Vaughan
ACM SIGecom Exchanges | December 2013, 第 12 卷(2): pp. 4-23
Position paper and survey.
Generalized Thompson Sampling for Contextual Bandits
Lihong Li
MSR-TR-2013-136 | October 2013
Sample complexity of multi-task reinforcement learning
Emma Brunskill, Lihong Li
Proceedings of the Twenty-Nineth Conference on Uncertainty in Artificial Intelligence (UAI-13) | July 2013
Multi-parameter Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (ACM-EC 2013) | June 2013
Adaptive crowdsourcing algorithms for the bandit survey problem
Ittai Abraham, Omar Alonso, Vasilis Kandylas, Aleksandrs Slivkins
26th Conf. on Learning Theory (COLT) | January 2013
-
Dynamic Pricing with Limited Supply
Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'12) | June 2012
-
Monotone multi-armed bandit allocations
Aleksandrs Slivkins, Aleksandrs Slivkins
Proceedings of the 24th Annual Conference on Learning Theory | April 2011
-
Learning optimally diverse rankings over large document collections
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi
Proc. of the 27th International Conference on Machine Learning (ICML 2010) | June 2010
Proc. of the 27th International Conference on Machine Learning (ICML 2010)
Full version can be found at arxiv.org (http://arxiv.org/abs/1005.5197).
Truthful Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'10) | June 2010
Best Paper Award (ACM EC 2010). The full version can be found on arxiv.org (http://arxiv.org/abs/1004.3630).
Sharp Dichotomies for Regret Minimization in Metric Spaces
Robert Kleinberg, Aleksandrs Slivkins
21st ACM-SIAM Symp. on Discrete Algorithms (SODA) | January 2010
Full version available on arxiv.org (http://arxiv.org/abs/0911.1174).
-
Characterizing Truthful Multi-Armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'09) | July 2009
Full version can be found on arxiv.org (http://arxiv.org/abs/0812.2291).
-
Characterizing Truthful Multi-armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
SIAM Journal on Computing (SICOMP) | November 2008, 第 43 卷: pp. 194-230
Adapting to a Changing Environment: the Brownian Restless Bandits
Aleksandrs Slivkins, Eli Upfal
21st Conference on Learning Theory (COLT) | July 2008
Multi-armed bandits in metric spaces
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
ACM Symposium on Theory of Computing (STOC) | May 2008
ACM Symposium on Theory of Computing (STOC)
ISBN: 978-1-60558-047-0
The full version is available from arxiv.org (http://arxiv.org/abs/0809.4882).
-
Contextual bandit learning with predictable rewards
Miro Dudík, Satyen Kale, John Langford, Alekh Agarwal, Robert E. Schapire
Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS-12) | January 2000
Resourceful Contextual Bandits
Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins
27th Conf. on Learning Theory (COLT) | January 2000
按研究领域分类的论文与出版物
-
Resourceful Contextual Bandits
Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins
27th Conf. on Learning Theory (COLT) | January 2000
Contextual bandit learning with predictable rewards
Miro Dudík, Satyen Kale, John Langford, Alekh Agarwal, Robert E. Schapire
Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS-12) | January 2000
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li, Yu Lu, Denny Zhou
Proceedings of the 34th International Conference on Machine Learning (ICML) | August 2017
Click-based Hot Fixes for Underperforming Torso Queries
Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, Maarten de Rijke
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | July 2016
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
On the Prior Sensitivity of Thompson Sampling
Lihong Li
Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT) | June 2016
Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT)
Doubly Robust Off-policy Evaluation for Reinforcement Learning
Nan Jiang, Lihong Li
JMLR: Workshop and Conference Proceedings; Proceedings of the 33rd International Conference on Machine Learning (ICML) | June 2016
An Efficient Algorithm for Contextual Bandits with Knapsacks, and an Extension to Concave Objectives
Shipra Agrawal, Nikhil Devanur, Lihong Li
Proceedings of the 29th Conference on Learning Theory (COLT) - JMLR: Workshop and Conference Proceedings | June 2016
Doubly Robust Off-policy Evaluation for Reinforcement Learning
Nan Jiang, Lihong Li
MSR-TR-2015-86 | November 2015
Counterfactual Estimation and Optimization of Click Metrics in Search Engines: A Case Study
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
Proceedings of the 24th International World Wide Web Conference (WWW'14), Companion Volume | May 2015
Evaluation of Explore-Exploit Policies in Multi-result Ranking Systems
Dragomir Yankov, Pavel Berkhin, Lihong Li
MSR-TR-2015-34 | May 2015
Toward Minimax Off-policy Value Estimation
Lihong Li, Remi Munos, Csaba Szepesvari
Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) | May 2015
Toward Predicting the Outcome of an A/B Experiment for Search Relevance
Lihong Li, Imed Zitouni, Jin Young Kim
Proceedings of the 8th ACM International Conference on Web Search and Data Mining | February 2015
Proceedings of the 8th ACM International Conference on Web Search and Data Mining
Offline Evaluation and Optimization for Interactive Systems
Lihong Li
Proceedings of the 8th ACM International Conference on Web Search and Data Mining | February 2015
Proceedings of the 8th ACM International Conference on Web Search and Data Mining
Doubly Robust Policy Evaluation and Optimization
Miro Dudík, Dumitru Erhan, John Langford, Lihong Li
Statistical Science | November 2014
On Minimax Optimal Offline Policy Evaluation
Lihong Li
MSR-TR-2014-124 | September 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
The 31st International Conference on Machine Learning (ICML 2014) | June 2014
Counterfactual Estimation and Optimization of Click Metrics for Search Engines
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
MSR-TR-2014-32 | March 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hus, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
MSR-TR-2014-33 | February 2014
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
15th ACM Conf. on Economics and Computation (EC) | January 2014
Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
Aleksandrs Slivkins, Jennifer Wortman Vaughan
ACM SIGecom Exchanges | December 2013, 第 12 卷(2): pp. 4-23
Position paper and survey.
Generalized Thompson Sampling for Contextual Bandits
Lihong Li
MSR-TR-2013-136 | October 2013
Sample complexity of multi-task reinforcement learning
Emma Brunskill, Lihong Li
Proceedings of the Twenty-Nineth Conference on Uncertainty in Artificial Intelligence (UAI-13) | July 2013
Dynamic Pricing with Limited Supply
Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'12) | June 2012
Monotone multi-armed bandit allocations
Aleksandrs Slivkins, Aleksandrs Slivkins
Proceedings of the 24th Annual Conference on Learning Theory | April 2011
Learning optimally diverse rankings over large document collections
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi
Proc. of the 27th International Conference on Machine Learning (ICML 2010) | June 2010
Proc. of the 27th International Conference on Machine Learning (ICML 2010)
Full version can be found at arxiv.org (http://arxiv.org/abs/1005.5197).
Characterizing Truthful Multi-armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
SIAM Journal on Computing (SICOMP) | November 2008, 第 43 卷: pp. 194-230
Adapting to a Changing Environment: the Brownian Restless Bandits
Aleksandrs Slivkins, Eli Upfal
21st Conference on Learning Theory (COLT) | July 2008
Multi-armed bandits in metric spaces
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
ACM Symposium on Theory of Computing (STOC) | May 2008
ACM Symposium on Theory of Computing (STOC)
ISBN: 978-1-60558-047-0
The full version is available from arxiv.org (http://arxiv.org/abs/0809.4882).
-
Click-based Hot Fixes for Underperforming Torso Queries
Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, Maarten de Rijke
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | July 2016
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
-
Click-based Hot Fixes for Underperforming Torso Queries
Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, Maarten de Rijke
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | July 2016
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Online Evaluation for Information Retrieval
Katja Hofmann, Lihong Li, Filip Radlinski
Foundations and Trends® in Information Retrieval | June 2016, 第 10 卷: pp. 1-117
Toward Predicting the Outcome of an A/B Experiment for Search Relevance
Lihong Li, Imed Zitouni, Jin Young Kim
Proceedings of the 8th ACM International Conference on Web Search and Data Mining | February 2015
Proceedings of the 8th ACM International Conference on Web Search and Data Mining
Learning optimally diverse rankings over large document collections
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi
Proc. of the 27th International Conference on Machine Learning (ICML 2010) | June 2010
Proc. of the 27th International Conference on Machine Learning (ICML 2010)
Full version can be found at arxiv.org (http://arxiv.org/abs/1005.5197).
-
Resourceful Contextual Bandits
Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins
27th Conf. on Learning Theory (COLT) | January 2000
Truthful Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
Journal of the ACM (JACM) | May 2015, 第 62 卷(2)
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
15th ACM Conf. on Economics and Computation (EC) | January 2014
Multi-parameter Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (ACM-EC 2013) | June 2013
Dynamic Pricing with Limited Supply
Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'12) | June 2012
Truthful Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'10) | June 2010
Best Paper Award (ACM EC 2010). The full version can be found on arxiv.org (http://arxiv.org/abs/1004.3630).
Characterizing Truthful Multi-Armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'09) | July 2009
Full version can be found on arxiv.org (http://arxiv.org/abs/0812.2291).
-
Resourceful Contextual Bandits
Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins
27th Conf. on Learning Theory (COLT) | January 2000
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
15th ACM Conf. on Economics and Computation (EC) | January 2014
Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
Aleksandrs Slivkins, Jennifer Wortman Vaughan
ACM SIGecom Exchanges | December 2013, 第 12 卷(2): pp. 4-23
Position paper and survey.
Multi-parameter Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (ACM-EC 2013) | June 2013
Adaptive crowdsourcing algorithms for the bandit survey problem
Ittai Abraham, Omar Alonso, Vasilis Kandylas, Aleksandrs Slivkins
26th Conf. on Learning Theory (COLT) | January 2013
Dynamic Pricing with Limited Supply
Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'12) | June 2012
Learning optimally diverse rankings over large document collections
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi
Proc. of the 27th International Conference on Machine Learning (ICML 2010) | June 2010
Proc. of the 27th International Conference on Machine Learning (ICML 2010)
Full version can be found at arxiv.org (http://arxiv.org/abs/1005.5197).
Truthful Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'10) | June 2010
Best Paper Award (ACM EC 2010). The full version can be found on arxiv.org (http://arxiv.org/abs/1004.3630).
Sharp Dichotomies for Regret Minimization in Metric Spaces
Robert Kleinberg, Aleksandrs Slivkins
21st ACM-SIAM Symp. on Discrete Algorithms (SODA) | January 2010
Full version available on arxiv.org (http://arxiv.org/abs/0911.1174).
Characterizing Truthful Multi-Armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'09) | July 2009
Full version can be found on arxiv.org (http://arxiv.org/abs/0812.2291).
Characterizing Truthful Multi-armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
SIAM Journal on Computing (SICOMP) | November 2008, 第 43 卷: pp. 194-230
Adapting to a Changing Environment: the Brownian Restless Bandits
Aleksandrs Slivkins, Eli Upfal
21st Conference on Learning Theory (COLT) | July 2008
Multi-armed bandits in metric spaces
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
ACM Symposium on Theory of Computing (STOC) | May 2008
ACM Symposium on Theory of Computing (STOC)
ISBN: 978-1-60558-047-0
The full version is available from arxiv.org (http://arxiv.org/abs/0809.4882).
按类型分类的论文与出版物
-
Resourceful Contextual Bandits
Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins
27th Conf. on Learning Theory (COLT) | January 2000
Contextual bandit learning with predictable rewards
Miro Dudík, Satyen Kale, John Langford, Alekh Agarwal, Robert E. Schapire
Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS-12) | January 2000
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li, Yu Lu, Denny Zhou
Proceedings of the 34th International Conference on Machine Learning (ICML) | August 2017
Click-based Hot Fixes for Underperforming Torso Queries
Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, Maarten de Rijke
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) | July 2016
Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
On the Prior Sensitivity of Thompson Sampling
Lihong Li
Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT) | June 2016
Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT)
Doubly Robust Off-policy Evaluation for Reinforcement Learning
Nan Jiang, Lihong Li
JMLR: Workshop and Conference Proceedings; Proceedings of the 33rd International Conference on Machine Learning (ICML) | June 2016
An Efficient Algorithm for Contextual Bandits with Knapsacks, and an Extension to Concave Objectives
Shipra Agrawal, Nikhil Devanur, Lihong Li
Proceedings of the 29th Conference on Learning Theory (COLT) - JMLR: Workshop and Conference Proceedings | June 2016
Counterfactual Estimation and Optimization of Click Metrics in Search Engines: A Case Study
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
Proceedings of the 24th International World Wide Web Conference (WWW'14), Companion Volume | May 2015
Toward Minimax Off-policy Value Estimation
Lihong Li, Remi Munos, Csaba Szepesvari
Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) | May 2015
Toward Predicting the Outcome of an A/B Experiment for Search Relevance
Lihong Li, Imed Zitouni, Jin Young Kim
Proceedings of the 8th ACM International Conference on Web Search and Data Mining | February 2015
Proceedings of the 8th ACM International Conference on Web Search and Data Mining
Offline Evaluation and Optimization for Interactive Systems
Lihong Li
Proceedings of the 8th ACM International Conference on Web Search and Data Mining | February 2015
Proceedings of the 8th ACM International Conference on Web Search and Data Mining
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
The 31st International Conference on Machine Learning (ICML 2014) | June 2014
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
15th ACM Conf. on Economics and Computation (EC) | January 2014
Sample complexity of multi-task reinforcement learning
Emma Brunskill, Lihong Li
Proceedings of the Twenty-Nineth Conference on Uncertainty in Artificial Intelligence (UAI-13) | July 2013
Multi-parameter Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (ACM-EC 2013) | June 2013
Adaptive crowdsourcing algorithms for the bandit survey problem
Ittai Abraham, Omar Alonso, Vasilis Kandylas, Aleksandrs Slivkins
26th Conf. on Learning Theory (COLT) | January 2013
Dynamic Pricing with Limited Supply
Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'12) | June 2012
Monotone multi-armed bandit allocations
Aleksandrs Slivkins, Aleksandrs Slivkins
Proceedings of the 24th Annual Conference on Learning Theory | April 2011
Learning optimally diverse rankings over large document collections
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi
Proc. of the 27th International Conference on Machine Learning (ICML 2010) | June 2010
Proc. of the 27th International Conference on Machine Learning (ICML 2010)
Full version can be found at arxiv.org (http://arxiv.org/abs/1005.5197).
Truthful Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'10) | June 2010
Best Paper Award (ACM EC 2010). The full version can be found on arxiv.org (http://arxiv.org/abs/1004.3630).
Sharp Dichotomies for Regret Minimization in Metric Spaces
Robert Kleinberg, Aleksandrs Slivkins
21st ACM-SIAM Symp. on Discrete Algorithms (SODA) | January 2010
Full version available on arxiv.org (http://arxiv.org/abs/0911.1174).
Characterizing Truthful Multi-Armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
ACM Conference on Electronic Commerce (EC'09) | July 2009
Full version can be found on arxiv.org (http://arxiv.org/abs/0812.2291).
Adapting to a Changing Environment: the Brownian Restless Bandits
Aleksandrs Slivkins, Eli Upfal
21st Conference on Learning Theory (COLT) | July 2008
Multi-armed bandits in metric spaces
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
ACM Symposium on Theory of Computing (STOC) | May 2008
ACM Symposium on Theory of Computing (STOC)
ISBN: 978-1-60558-047-0
The full version is available from arxiv.org (http://arxiv.org/abs/0809.4882).
-
Online Evaluation for Information Retrieval
Katja Hofmann, Lihong Li, Filip Radlinski
Foundations and Trends® in Information Retrieval | June 2016, 第 10 卷: pp. 1-117
Truthful Mechanisms with Implicit Payment Computation
Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins
Journal of the ACM (JACM) | May 2015, 第 62 卷(2)
Doubly Robust Policy Evaluation and Optimization
Miro Dudík, Dumitru Erhan, John Langford, Lihong Li
Statistical Science | November 2014
Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
Aleksandrs Slivkins, Jennifer Wortman Vaughan
ACM SIGecom Exchanges | December 2013, 第 12 卷(2): pp. 4-23
Position paper and survey.
Characterizing Truthful Multi-armed Bandit Mechanisms
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
SIAM Journal on Computing (SICOMP) | November 2008, 第 43 卷: pp. 194-230
-
Doubly Robust Off-policy Evaluation for Reinforcement Learning
Nan Jiang, Lihong Li
MSR-TR-2015-86 | November 2015
Evaluation of Explore-Exploit Policies in Multi-result Ranking Systems
Dragomir Yankov, Pavel Berkhin, Lihong Li
MSR-TR-2015-34 | May 2015
On Minimax Optimal Offline Policy Evaluation
Lihong Li
MSR-TR-2014-124 | September 2014
Counterfactual Estimation and Optimization of Click Metrics for Search Engines
Lihong Li, Shunbao Chen, Jim Kleban, Ankur Gupta
MSR-TR-2014-32 | March 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hus, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
MSR-TR-2014-33 | February 2014
Generalized Thompson Sampling for Contextual Bandits
Lihong Li
MSR-TR-2013-136 | October 2013
人员
Robert Schapire
Partner Researcher
Paul Mineiro
Principal Data and Applied Scientist
Siddhartha Sen
Principal Researcher
Sarah Bird
Chief Product Officer of Responsible AI @ Microsoft
Alex Slivkins
Senior Principal Researcher
Miro Dudík
Sr Principal Researcher Manager
John Langford
Partner Researcher Manager
Markus Cozowicz
Senior Research Engineer