Ian Gemp
Cited by
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Generative multi-adversarial networks
I Durugkar, I Gemp, S Mahadevan
International Conference on Learning Representations, 2017
Social diversity and social preferences in mixed-motive reinforcement learning
KR McKee, I Gemp, B McWilliams, EA Duéñez-Guzmán, E Hughes, ...
arXiv preprint arXiv:2002.02325, 2020
Proximal reinforcement learning: A new theory of sequential decision making in primal-dual spaces
S Mahadevan, B Liu, P Thomas, W Dabney, S Giguere, N Jacek, I Gemp, ...
arXiv preprint arXiv:1405.6757, 2014
Global convergence to the equilibrium of gans using variational inequalities
I Gemp, S Mahadevan
arXiv preprint arXiv:1808.01531, 2018
Quantitative analysis of synaptic release at the photoreceptor synapse
G Duncan, K Rabl, I Gemp, R Heidelberger, WB Thoreson
Biophysical journal 98 (10), 2102-2110, 2010
Eigengame: PCA as a nash equilibrium
I Gemp, B McWilliams, C Vernade, T Graepel
arXiv preprint arXiv:2010.00554, 2020
Learning to play no-press diplomacy with best response policy iteration
T Anthony, T Eccles, A Tacchetti, J Kramár, I Gemp, T Hudson, N Porcel, ...
Advances in Neural Information Processing Systems 33, 17987-18003, 2020
Cadherin-dependent cell morphology in an epithelium: constructing a quantitative dynamical model
IM Gemp, RW Carthew, S Hilgenfeldt
PLoS computational biology 7 (7), e1002115, 2011
Smooth markets: A basic mechanism for organizing gradient-based learners
D Balduzzi, WM Czarnecki, TW Anthony, IM Gemp, E Hughes, JZ Leibo, ...
arXiv preprint arXiv:2001.04678, 2020
Proximal gradient temporal difference learning: Stable reinforcement learning with polynomial sample complexity
B Liu, I Gemp, M Ghavamzadeh, J Liu, S Mahadevan, M Petrik
Journal of Artificial Intelligence Research 63, 461-494, 2018
Automated data cleansing through meta-learning
I Gemp, G Theocharous, M Ghavamzadeh
Proceedings of the AAAI Conference on Artificial Intelligence 31 (2), 4760-4761, 2017
D3C: Reducing the price of anarchy in multi-agent learning
I Gemp, KR McKee, R Everett, EA Duéñez-Guzmán, Y Bachrach, ...
arXiv preprint arXiv:2010.00575, 2020
Game-theoretic vocabulary selection via the shapley value and banzhaf index
R Patel, M Garnelo, I Gemp, C Dyer, Y Bachrach
Proceedings of the 2021 Conference of the North American Chapter of the …, 2021
Eigengame unloaded: When playing games is better than optimizing
I Gemp, B McWilliams, C Vernade, T Graepel
arXiv preprint arXiv:2102.04152, 2021
The unreasonable effectiveness of adam on cycles
I Gemp, B McWilliams
NeurIPS Workshop on Bridging Game Theory and Deep Learning, 2019
Sample-based approximation of Nash in large many-player games via gradient descent
I Gemp, R Savani, M Lanctot, Y Bachrach, T Anthony, R Everett, ...
arXiv preprint arXiv:2106.01285, 2021
Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy
J Kramár, T Eccles, I Gemp, A Tacchetti, KR McKee, M Malinowski, ...
Nature Communications 13 (1), 7214, 2022
Weakly semi-supervised neural topic models
I Gemp, R Nallapati, R Ding, F Nan, B Xiang
Online monotone games
I Gemp, S Mahadevan
arXiv preprint arXiv:1710.07328, 2017
Unmixing in the presence of nuisances with deep generative models
M Parente, I Gemp, I Durugkar
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017
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Articles 1–20