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Emma Brunskill
Emma Brunskill
Associate Professor of Computer Science, Stanford University
Zweryfikowany adres z cs.stanford.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
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
49002021
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
8922013
Data-efficient off-policy policy evaluation for reinforcement learning
P Thomas, E Brunskill
International conference on machine learning, 2139-2148, 2016
7852016
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
6222020
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
3902001
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
3452011
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
3412017
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
3212019
Sample complexity of episodic fixed-horizon reinforcement learning
C Dann, E Brunskill
Advances in Neural Information Processing Systems 28, 2015
2842015
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
2722013
Faster teaching via pomdp planning
AN Rafferty, E Brunskill, TL Griffiths, P Shafto
Cognitive science 40 (6), 1290-1332, 2016
2692016
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
2602020
Offline policy evaluation across representations with applications to educational games.
T Mandel, YE Liu, S Levine, E Brunskill, Z Popovic
AAMAS 1077, 2014
2542014
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
2362020
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
2312019
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
2172020
Efficient exploration through bayesian deep q-networks
K Azizzadenesheli, E Brunskill, A Anandkumar
2018 Information Theory and Applications Workshop (ITA), 1-9, 2018
2152018
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
2102019
On the opportunities and risks of foundation models. arXiv
R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ...
arXiv preprint arXiv:2108.07258 10, 2021
1982021
The Impact on Individualizing Student Models on Necessary Practice Opportunities.
JI Lee, E Brunskill
International educational data mining society, 2012
1802012
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