Stebėti
Thore Graepel
Thore Graepel
Global Lead Computational Science, AI & ML at Altos Labs and Chair of Machine Learning, UCL
Patvirtintas el. paštas ucl.ac.uk - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
Mastering the game of Go with deep neural networks and tree search
D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ...
nature 529 (7587), 484-489, 2016
205342016
Mastering the game of go without human knowledge
D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ...
nature 550 (7676), 354-359, 2017
116612017
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ...
Science 362 (6419), 1140-1144, 2018
49492018
Private traits and attributes are predictable from digital records of human behavior
M Kosinski, D Stillwell, T Graepel
Proceedings of the national academy of sciences 110 (15), 5802-5805, 2013
39982013
Mastering atari, go, chess and shogi by planning with a learned model
J Schrittwieser, I Antonoglou, T Hubert, K Simonyan, L Sifre, S Schmitt, ...
Nature 588 (7839), 604-609, 2020
26342020
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ...
arXiv preprint arXiv:1712.01815, 2017
24302017
Value-decomposition networks for cooperative multi-agent learning
P Sunehag, G Lever, A Gruslys, WM Czarnecki, V Zambaldi, M Jaderberg, ...
arXiv preprint arXiv:1706.05296, 2017
19392017
Large margin rank boundaries for ordinal regression
R Herbrich, T Graepel, K Obermayer
14772000
TrueSkill™: a Bayesian skill rating system
R Herbrich, T Minka, T Graepel
Advances in neural information processing systems 19, 2006
11122006
Human-level performance in 3D multiplayer games with population-based reinforcement learning
M Jaderberg, WM Czarnecki, I Dunning, L Marris, G Lever, AG Castaneda, ...
Science 364 (6443), 859-865, 2019
10192019
Multi-agent reinforcement learning in sequential social dilemmas
JZ Leibo, V Zambaldi, M Lanctot, J Marecki, T Graepel
arXiv preprint arXiv:1702.03037, 2017
9362017
A unified game-theoretic approach to multiagent reinforcement learning
M Lanctot, V Zambaldi, A Gruslys, A Lazaridou, K Tuyls, J Pérolat, D Silver, ...
Advances in neural information processing systems 30, 2017
7782017
Web-scale bayesian click-through rate prediction for sponsored search advertising in microsoft's bing search engine
T Graepel, JQ Candela, T Borchert, R Herbrich
Omnipress 27, 13-20, 2010
7462010
Personality and patterns of Facebook usage
Y Bachrach, M Kosinski, T Graepel, P Kohli, D Stillwell
Proceedings of the 4th annual ACM web science conference, 24-32, 2012
6752012
ML confidential: Machine learning on encrypted data
T Graepel, K Lauter, M Naehrig
International conference on information security and cryptology, 1-21, 2012
6562012
Support vector learning for ordinal regression
R Herbrich, T Graepel, K Obermayer
IET Digital Library, 1999
5871999
Manifestations of user personality in website choice and behaviour on online social networks
M Kosinski, Y Bachrach, P Kohli, D Stillwell, T Graepel
Machine learning 95, 357-380, 2014
4562014
Matchbox: large scale online bayesian recommendations
DH Stern, R Herbrich, T Graepel
Proceedings of the 18th international conference on World wide web, 111-120, 2009
3692009
Bayes point machines
R Herbrich, T Graepel, C Campbell
Journal of Machine Learning Research 1 (Aug), 245-279, 2001
3402001
The mechanics of n-player differentiable games
D Balduzzi, S Racaniere, J Martens, J Foerster, K Tuyls, T Graepel
International Conference on Machine Learning, 354-363, 2018
3292018
Sistema negali atlikti operacijos. Bandykite vėliau dar kartą.
Straipsniai 1–20