Emma Brunskill

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Philip ThomasUniversity of Massachusetts AmherstDirección de correo verificada de cs.umass.edu
Alessandro LazaricResearch Scientist, Facebook Artificial Intelligence ResearchDirección de correo verificada de inria.fr
Christoph DannResearch Scientist, GoogleDirección de correo verificada de google.com
Nicholas RoyMITDirección de correo verificada de csail.mit.edu
Shayan DoroudiAssistant Professor at the University of California, IrvineDirección de correo verificada de uci.edu
Zoran PopovicProfessor of Computer Science, Director Center for Game Science, University of WashingtonDirección de correo verificada de cs.washington.edu
Lihong Li (李力鸿)AmazonDirección de correo verificada de amazon.com
Ken KoedingerHCII, Carnegie Mellon UniversityDirección de correo verificada de cmu.edu
Thomas KollarWayve, Head of AI (Foundation Models)Dirección de correo verificada de wayve.ai
Seth Flaxmanassociate professor at OxfordDirección de correo verificada de cs.ox.ac.uk
Gretchen A StevensWorld Health OrganizationDirección de correo verificada de who.int
William ThiesEverwell (formerly Microsoft Research, MIT)Dirección de correo verificada de everwell.org
Anna RaffertyAssistant Professor, Carleton CollegeDirección de correo verificada de carleton.edu
Ion StoicaProfessor of Computer Science, UC BerkeleyDirección de correo verificada de cs.berkeley.edu
Frank DabekGoogleDirección de correo verificada de google.com
Frans KaashoekMassuchesetts Institute of Technology (MIT)Dirección de correo verificada de mit.edu
David KargerProfessor of Computer Science, MITDirección de correo verificada de mit.edu
Mohammad Gheshlaghi AzarCohereDirección de correo verificada de cohere.com
Tomas Lozano-PerezProfessor of Computer Science, MITDirección de correo verificada de mit.edu

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Emma Brunskill

Associate Professor of Computer Science, Stanford University

Dirección de correo verificada de cs.stanford.edu - Página principal

Reinforcement Learning Machine Learning Decision Making Under Uncertainty Online Education


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021	3808	2021
Global and regional hearing impairment prevalence: an analysis of 42 studies in 29 countries G Stevens, S Flaxman, E Brunskill, M Mascarenhas, CD Mathers, ... The European Journal of Public Health 23 (1), 146-152, 2013	862	2013
Data-efficient off-policy policy evaluation for reinforcement learning P Thomas, E Brunskill International Conference on Machine Learning, 2139-2148, 2016	743	2016
Towards the systematic reporting of the energy and carbon footprints of machine learning P Henderson, J Hu, J Romoff, E Brunskill, D Jurafsky, J Pineau Journal of Machine Learning Research 21 (248), 1-43, 2020	534	2020
Building peer-to-peer systems with Chord, a distributed lookup service F Dabek, E Brunskill, MF Kaashoek, D Karger, R Morris, I Stoica, ... Proceedings Eighth Workshop on Hot Topics in Operating Systems, 81-86, 2001	389	2001
Designing mobile interfaces for novice and low-literacy users I Medhi, S Patnaik, E Brunskill, SNN Gautama, W Thies, K Toyama ACM Transactions on Computer-Human Interaction (TOCHI) 18 (1), 1-28, 2011	339	2011
Unifying PAC and regret: Uniform PAC bounds for episodic reinforcement learning C Dann, T Lattimore, E Brunskill Advances in Neural Information Processing Systems 30, 2017	323	2017
Tighter problem-dependent regret bounds in reinforcement learning without domain knowledge using value function bounds A Zanette, E Brunskill International Conference on Machine Learning, 7304-7312, 2019	306	2019
Sample complexity of episodic fixed-horizon reinforcement learning C Dann, E Brunskill Advances in Neural Information Processing Systems 28, 2015	278	2015
New potentials for data-driven intelligent tutoring system development and optimization KR Koedinger, E Brunskill, RSJ Baker, EA McLaughlin, J Stamper AI Magazine 34 (3), 27-41, 2013	254	2013
Faster teaching via pomdp planning AN Rafferty, E Brunskill, TL Griffiths, P Shafto Cognitive science 40 (6), 1290-1332, 2016	253	2016
Offline policy evaluation across representations with applications to educational games. T Mandel, YE Liu, S Levine, E Brunskill, Z Popovic AAMAS 1077, 2014	244	2014
Learning near optimal policies with low inherent bellman error A Zanette, A Lazaric, M Kochenderfer, E Brunskill International Conference on Machine Learning, 10978-10989, 2020	240	2020
Provably good batch off-policy reinforcement learning without great exploration Y Liu, A Swaminathan, A Agarwal, E Brunskill Advances in neural information processing systems 33, 1264-1274, 2020	219	2020
Quizbot: A dialogue-based adaptive learning system for factual knowledge S Ruan, L Jiang, J Xu, BJK Tham, Z Qiu, Y Zhu, EL Murnane, E Brunskill, ... Proceedings of the 2019 CHI conference on human factors in computing systems …, 2019	210	2019
Preventing undesirable behavior of intelligent machines PS Thomas, B Castro da Silva, AG Barto, S Giguere, Y Brun, E Brunskill Science 366 (6468), 999-1004, 2019	204	2019
Efficient exploration through bayesian deep q-networks K Azizzadenesheli, E Brunskill, A Anandkumar 2018 Information Theory and Applications Workshop (ITA), 1-9, 2018	203	2018
Scaling up behavioral science interventions in online education RF Kizilcec, J Reich, M Yeomans, C Dann, E Brunskill, G Lopez, S Turkay, ... Proceedings of the National Academy of Sciences 117 (26), 14900-14905, 2020	191	2020
The Impact on Individualizing Student Models on Necessary Practice Opportunities. JI Lee, E Brunskill International educational data mining society, 2012	178	2012
Evaluating the accuracy of data collection on mobile phones: A study of forms, SMS, and voice S Patnaik, E Brunskill, W Thies 2009 International Conference on Information and Communication Technologies …, 2009	177	2009

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