Benjamin Van Roy

Получаване на мой собствен потребителски профил

Позовавания

	Всички	От 2019
Позовавания	19592	10536
h-индекс	60	45
i10-индекс	131	96

2100

1050

525

1575

19981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020202120222023202450 68 71 109 169 159 209 308 339 424 447 553 574 563 612 548 633 604 638 751 997 1287 1667 1841 1983 2032 1719

Публичен достъп

Преглед на всички

5 статии

0 статии

налични

неналични

Въз основа на изисквания при финансирането

Съавтори

Ian OsbandOpenAIПотвърден имейл адрес: openai.com
John TsitsiklisProfessor of Electrical Engineering, MITПотвърден имейл адрес: mit.edu
Zheng WenGoogle DeepMindПотвърден имейл адрес: google.com
Daniel RussoColumbia UniversityПотвърден имейл адрес: gsb.columbia.edu
Gabriel Y WeintraubStanford GSBПотвърден имейл адрес: stanford.edu
Ciamac MoallemiProfessor, Graduate School of Business, Columbia UniversityПотвърден имейл адрес: gsb.columbia.edu
Morteza IbrahimiStanford UniversityПотвърден имейл адрес: stanford.edu
Paat RusmevichientongProfessor, Marshall School of Business, University of Southern CaliforniaПотвърден имейл адрес: marshall.usc.edu
Vivek FariasMassachusetts Institute of TechnologyПотвърден имейл адрес: mit.edu
Abbas KazerouniStanford UniversityПотвърден имейл адрес: stanford.edu
Anant SAHAIEECS, University of California, BerkeleyПотвърден имейл адрес: eecs.berkeley.edu
Alexander PritzelDeepmindПотвърден имейл адрес: google.com
Charles BlundellResearch Scientist at DeepMindПотвърден имейл адрес: google.com
Tsachy WeissmanProfessor of Electrical Engineering at Stanford UniversityПотвърден имейл адрес: stanford.edu
Yi-Hao KaoPhD Candidate, Electrical Engineering, Stanford UniversityПотвърден имейл адрес: stanford.edu
Hui ZhangCarnegie Mellon University, ConvivaПотвърден имейл адрес: andrew.cmu.edu
Richard ZeckhauserHarvard UniversityПотвърден имейл адрес: harvard.edu
Per EngeProfessor, Stanford UniversityПотвърден имейл адрес: stanford.edu
Ramesh GovindanProfessor of Computer Science, University of Southern CaliforniaПотвърден имейл адрес: usc.edu
Ashish GoelProfessor of Management Science and Engineering, and by courtesy, Computer Science, Stanford UniversityПотвърден имейл адрес: stanford.edu

Следене

Benjamin Van Roy

Stanford University

Потвърден имейл адрес: stanford.edu - Начална страница

reinforcement learning operations research information theory


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
Analysis of temporal-diffference learning with function approximation J Tsitsiklis, B Van Roy Advances in neural information processing systems 9, 1996	2246	1996
Deep exploration via bootstrapped DQN I Osband, C Blundell, A Pritzel, B Van Roy Advances in neural information processing systems 29, 2016	1505	2016
A tutorial on thompson sampling D Russo, B Van Roy, A Kazerouni, I Osband, Z Wen Foundations and Trends in Machine Learning 11 (1), pp. 1-96, 2018	1198	2018
The linear programming approach to approximate dynamic programming DP De Farias, B Van Roy Operations research 51 (6), 850-865, 2003	977	2003
Regression methods for pricing complex American-style options JN Tsitsiklis, B Van Roy IEEE Transactions on Neural Networks 12 (4), 694-703, 2001	864	2001
Learning to optimize via posterior sampling D Russo, B Van Roy Mathematics of Operations Research 39 (4), 1221-1243, 2014	766	2014
Feature-based methods for large scale dynamic programming JN Tsitsiklis, B Van Roy Machine Learning 22 (1), 59-94, 1996	724	1996
Markov perfect industry dynamics with many firms G Weintraub, CL Benkard, B Van Roy Econometrica 76 (6), 1375-1411, 2008	571	2008
On constraint sampling in the linear programming approach to approximate dynamic programming DP De Farias, B Van Roy Mathematics of operations research 29 (3), 462-478, 2004	497	2004
Optimal stopping of Markov processes: Hilbert space theory, approximation algorithms, and an application to pricing high-dimensional financial derivatives JN Tsitsiklis, B Van Roy IEEE Transactions on Automatic Control 44 (10), 1840-1851, 1999	491	1999
An information-theoretic analysis of thompson sampling D Russo, B Van Roy Journal of Machine Learning Research 17 (68), 1-30, 2016	434	2016
Deep Exploration via Randomized Value Functions. I Osband, B Van Roy, DJ Russo, Z Wen The Journal of Machine Learning Research 20 (124), 1-62, 2019	342	2019
Generalization and exploration via randomized value functions I Osband, B Van Roy, Z Wen International Conference on Machine Learning, 2377-2386, 2016	338	2016
Consensus propagation CC Moallemi, B Van Roy IEEE Transactions on Information Theory 52 (11), 4753-4766, 2006	307	2006
Eluder dimension and the sample complexity of optimistic exploration D Russo, B Van Roy Advances in Neural Information Processing Systems 26, 2013	274	2013
Why is posterior sampling better than optimism for reinforcement learning? I Osband, B Van Roy International conference on machine learning, 2701-2710, 2017	272	2017
Dynamic pricing with a prior on market response VF Farias, B Van Roy Operations Research 58 (1), 16-29, 2010	271	2010
Solving data mining problems through pattern recognition RL Kennedy, Y Lee, B Van Roy, CD Reed, RP Lippman Upper Saddle River, NJ: Prentice Hall PTR, 2011	270*	2011
Learning to optimize via information-directed sampling D Russo, B Van Roy Advances in neural information processing systems 27, 2014	244	2014
Average cost temporal-difference learning JN Tsitsiklis, B Van Roy Automatica 35, 319-349, 1999	241	1999

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