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    Author information
    First name: Shipra Agrawal
    Last name: 0001
    DBLP: a/ShipraAgrawal
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    Below you find the publications which have been written by this author.

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    Conference paper
    Shipra Agrawal 0001, Randy Jia.
    Posterior sampling for reinforcement learning: worst-case regret bounds.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Shipra Agrawal 0001, Vashist Avadhanula, Vineet Goyal, Assaf J. Zeevi.
    Thompson Sampling for the MNL-Bandit.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Shipra Agrawal 0001, Vashist Avadhanula, Vineet Goyal, Assaf J. Zeevi.
    MNL-Bandit: A Dynamic Learning Approach to Assortment Selection.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Shipra Agrawal 0001, Vashist Avadhanula, Vineet Goyal, Assaf J. Zeevi.
    Thompson Sampling for the MNL-Bandit.
    Proceedings of the 30th Conference on Learning Theory, COLT 2017, Amsterdam, The Netherlands, 7-10 July 2017 2017 (0) 2017
    Conference paper
    Ciara Pike-Burke, Shipra Agrawal 0001, Csaba Szepesvári, Steffen Grünewälder.
    Bandits with Delayed Anonymous Feedback.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Shipra Agrawal 0001, Navin Goyal.
    Near-Optimal Regret Bounds for Thompson Sampling.
    J. ACM 2017, Volume 64 (0) 2017
    Conference paper
    Shipra Agrawal 0001, Randy Jia.
    Optimistic posterior sampling for reinforcement learning: worst-case regret bounds.
    Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA 2017 (0) 2017
    Conference paper
    Shipra Agrawal 0001, Vashist Avadhanula, Vineet Goyal, Assaf J. Zeevi.
    A Near-Optimal Exploration-Exploitation Approach for Assortment Selection.
    Proceedings of the 2016 ACM Conference on Economics and Computation, EC '16, Maastricht, The Netherlands, July 24-28, 2016 2016 (0) 2016
    Conference paper
    Shipra Agrawal 0001, Nikhil R. Devanur.
    Linear Contextual Bandits with Knapsacks.
    Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain 2016 (0) 2016
    Conference paper
    Shipra Agrawal 0001, Nikhil R. Devanur, Lihong Li 0001.
    An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives.
    Proceedings of the 29th Conference on Learning Theory, COLT 2016, New York, USA, June 23-26, 2016 2016 (0) 2016
    Journal article
    Shipra Agrawal 0001, Nikhil R. Devanur, Lihong Li 0001.
    Contextual Bandits with Global Constraints and Objective.
    CoRR 2015, Volume 0 (0) 2015
    Conference paper
    Shipra Agrawal 0001, Nikhil R. Devanur.
    Fast Algorithms for Online Stochastic Convex Programming.
    Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2015, San Diego, CA, USA, January 4-6, 2015 2015 (0) 2015
    Conference paper
    Shipra Agrawal 0001, Nikhil R. Devanur.
    Linear Contextual Bandits with Global Constraints and Objective.
    CoRR 2015, Volume 0 (0) 2015
    Journal article
    Shipra Agrawal 0001, Nikhil R. Devanur.
    Bandits with concave rewards and convex knapsacks.
    CoRR 2014, Volume 0 (0) 2014
    Conference paper
    Shipra Agrawal 0001, Nikhil R. Devanur.
    Bandits with concave rewards and convex knapsacks.
    ACM Conference on Economics and Computation, EC '14, Stanford , CA, USA, June 8-12, 2014 2014 (0) 2014
    Conference paper
    Tomás Kocák, Michal Valko, Rémi Munos, Shipra Agrawal 0001.
    Spectral Thompson Sampling.
    Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada. 2014 (0) 2014
    Journal article
    Shipra Agrawal 0001, Zizhuo Wang, Yinyu Ye.
    A Dynamic Near-Optimal Algorithm for Online Linear Programming.
    Operations Research 2014, Volume 62 (0) 2014
    Conference paper
    Shipra Agrawal 0001, Nikhil R. Devanur.
    Fast Algorithms for Online Stochastic Convex Programming.
    CoRR 2014, Volume 0 (0) 2014
    Conference paper
    Shipra Agrawal 0001, Navin Goyal.
    Thompson Sampling for Contextual Bandits with Linear Payoffs.
    Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013 2013 (0) 2013
    Conference paper
    Shipra Agrawal 0001, Navin Goyal.
    Further Optimal Regret Bounds for Thompson Sampling.
    Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2013, Scottsdale, AZ, USA, April 29 - May 1, 2013 2013 (0) 2013
    Journal article
    Shipra Agrawal 0001, Yichuan Ding, Amin Saberi, Yinyu Ye.
    Price of Correlations in Stochastic Optimization.
    Operations Research 2012, Volume 60 (0) 2012
    Journal article
    Shipra Agrawal 0001, Navin Goyal.
    Thompson Sampling for Contextual Bandits with Linear Payoffs
    CoRR 2012, Volume 0 (0) 2012
    Journal article
    Shipra Agrawal 0001, Navin Goyal.
    Further Optimal Regret Bounds for Thompson Sampling
    CoRR 2012, Volume 0 (0) 2012
    Conference paper
    Shipra Agrawal 0001, Navin Goyal.
    Analysis of Thompson Sampling for the Multi-armed Bandit Problem.
    COLT 2012 - The 25th Annual Conference on Learning Theory, June 25-27, 2012, Edinburgh, Scotland 2012 (0) 2012
    Conference paper
    Shipra Agrawal 0001, Erick Delage, Mark Peters, Zizhuo Wang, Yinyu Ye.
    A Unified Framework for Dynamic Prediction Market Design.
    Operations Research 2011, Volume 59 (0) 2011
    Show item 1 to 25 of 44  

    Your query returned 44 matches in the database.