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Emma Brunskill
Emma Brunskill
Associate Professor of Computer Science, Stanford University
Bestätigte E-Mail-Adresse bei cs.stanford.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
18832021
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
7792013
Data-efficient off-policy policy evaluation for reinforcement learning
P Thomas, E Brunskill
International Conference on Machine Learning, 2139-2148, 2016
6772016
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
3862001
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
3862001
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
The Journal of Machine Learning Research 21 (1), 10039-10081, 2020
3392020
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
3172011
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
2852017
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
2612019
Sample complexity of episodic fixed-horizon reinforcement learning
C Dann, E Brunskill
Advances in Neural Information Processing Systems 28, 2015
2532015
Faster teaching via pomdp planning
AN Rafferty, E Brunskill, TL Griffiths, P Shafto
Cognitive science 40 (6), 1290-1332, 2016
2232016
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
2232013
Offline policy evaluation across representations with applications to educational games.
T Mandel, YE Liu, S Levine, E Brunskill, Z Popovic
AAMAS 1077, 2014
2162014
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
1992020
Efficient exploration through bayesian deep q-networks
K Azizzadenesheli, E Brunskill, A Anandkumar
2018 Information Theory and Applications Workshop (ITA), 1-9, 2018
1822018
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
1762020
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
1742009
The Impact on Individualizing Student Models on Necessary Practice Opportunities.
JI Lee, E Brunskill
International Educational Data Mining Society, 2012
1662012
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
1652019
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
1632019
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