Følg
Shipra Agrawal
Tittel
Sitert av
Sitert av
År
Analysis of thompson sampling for the multi-armed bandit problem
S Agrawal, N Goyal
Conference on learning theory, 39.1-39.26, 2012
13982012
Thompson sampling for contextual bandits with linear payoffs
S Agrawal, N Goyal
International conference on machine learning, 127-135, 2013
10032013
Near-optimal regret bounds for thompson sampling
S Agrawal, N Goyal
Journal of the ACM (JACM) 64 (5), 1-24, 2017
5852017
A dynamic near-optimal algorithm for online linear programming
S Agrawal, Z Wang, Y Ye
Operations Research 62 (4), 876-890, 2014
3342014
A framework for high-accuracy privacy-preserving mining
S Agrawal, JR Haritsa
21st International Conference on Data Engineering (ICDE'05), 193-204, 2005
2392005
Optimistic posterior sampling for reinforcement learning: worst-case regret bounds
S Agrawal, R Jia
Advances in Neural Information Processing Systems 30, 2017
2252017
A near-optimal exploration-exploitation approach for assortment selection
S Agrawal, V Avadhanula, V Goyal, A Zeevi
Proceedings of the 2016 ACM Conference on Economics and Computation, 599-600, 2016
204*2016
Bandits with concave rewards and convex knapsacks
S Agrawal, NR Devanur
Proceedings of the fifteenth ACM conference on Economics and computation …, 2014
1952014
Fast Algorithms for Online Stochastic Convex Programming
S Agrawal, NR Devanur
SODA 2015, 2015
1802015
Price of correlations in stochastic optimization
S Agrawal, Y Ding, A Saberi, Y Ye
Operations Research 60 (1), 150-162, 2012
149*2012
Linear contextual bandits with knapsacks
S Agrawal, N Devanur
Advances in Neural Information Processing Systems 29, 2016
1362016
Reinforcement learning for integer programming: Learning to cut
Y Tang, S Agrawal, Y Faenza
International conference on machine learning, 9367-9376, 2020
1352020
Thompson sampling for the mnl-bandit
S Agrawal, V Avadhanula, V Goyal, A Zeevi
Conference on learning theory, 76-78, 2017
1122017
On addressing efficiency concerns in privacy-preserving mining
S Agrawal, V Krishnan, JR Haritsa
Database Systems for Advanced Applications: 9th International Conference …, 2004
1102004
Bandits with delayed, aggregated anonymous feedback
C Pike-Burke, S Agrawal, C Szepesvari, S Grunewalder
International Conference on Machine Learning, 4105-4113, 2018
1042018
Discretizing continuous action space for on-policy optimization
Y Tang, S Agrawal
Proceedings of the aaai conference on artificial intelligence 34 (04), 5981-5988, 2020
902020
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives
S Agrawal, NR Devanur, L Li
Conference on Learning Theory, 4-18, 2016
892016
Efficient detection of distributed constraint violations
S Agrawal, S Deb, KVM Naidu, R Rastogi
2007 IEEE 23rd International Conference on Data Engineering, 1320-1324, 2006
762006
A near-optimal exploration-exploitation approach for assortment selection
S Agrawal, V Avadhanula, V Goyal, A Zeevi
Proceedings of the 2016 ACM Conference on Economics and Computation, 599-600, 2016
642016
A unified framework for dynamic prediction market design
S Agrawal, E Delage, M Peters, Z Wang, Y Ye
Operations research 59 (3), 550-568, 2011
63*2011
Systemet kan ikke utføre handlingen. Prøv på nytt senere.
Artikler 1–20