Stebėti
Gabriel Dulac-Arnold
Gabriel Dulac-Arnold
Google Research
Patvirtintas el. paštas blacksheep.ai - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
Learning from demonstrations for real world reinforcement learning
T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, A Sendonaris, ...
arXiv preprint arXiv:1704.03732, 2017
1184*2017
Deep reinforcement learning in large discrete action spaces
G Dulac-Arnold, R Evans, H van Hasselt, P Sunehag, T Lillicrap, J Hunt, ...
arXiv preprint arXiv:1512.07679, 2015
6082015
Challenges of real-world reinforcement learning
G Dulac-Arnold, D Mankowitz, T Hester
ICML Workshop on Real-Life RL, 2019
5522019
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis
G Dulac-Arnold, N Levine, DJ Mankowitz, J Li, C Paduraru, S Gowal, ...
Machine Learning 110 (9), 2419-2468, 2021
332*2021
The predictron: End-to-end learning and planning
D Silver, H Hasselt, M Hessel, T Schaul, A Guez, T Harley, ...
International Conference on Machine Learning, 3191-3199, 2017
2792017
Acme: A research framework for distributed reinforcement learning
MW Hoffman, B Shahriari, J Aslanides, G Barth-Maron, N Momchev, ...
arXiv preprint arXiv:2006.00979, 2020
2052020
Rl unplugged: A suite of benchmarks for offline reinforcement learning
C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ...
Advances in Neural Information Processing Systems 33, 7248-7259, 2020
146*2020
Model-based offline planning
A Argenson, G Dulac-Arnold
ICLR 2021, 2020
1102020
Datum-wise classification: a sequential approach to sparsity
G Dulac-Arnold, L Denoyer, P Preux, P Gallinari
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011
612011
Learning to run a power network challenge: a retrospective analysis
A Marot, B Donnot, G Dulac-Arnold, A Kelly, A O’Sullivan, J Viebahn, ...
NeurIPS 2020 Competition and Demonstration Track, 112-132, 2021
452021
Deep reinforcement learning with attention for slate markov decision processes with high-dimensional states and actions
P Sunehag, R Evans, G Dulac-Arnold, Y Zwols, D Visentin, B Coppin
arXiv preprint arXiv:1512.01124, 2015
452015
Text classification: A sequential reading approach
G Dulac-Arnold, L Denoyer, P Gallinari
European Conference on Information Retrieval, 411-423, 2011
392011
Differentiable deep clustering with cluster size constraints
A Genevay, G Dulac-Arnold, JP Vert
arXiv preprint arXiv:1910.09036, 2019
312019
Deep multi-class learning from label proportions
G Dulac-Arnold, N Zeghidour, M Cuturi, L Beyer, JP Vert
arXiv preprint arXiv:1905.12909, 2019
282019
Fast reinforcement learning with large action sets using error-correcting output codes for mdp factorization
G Dulac-Arnold, L Denoyer, P Preux, P Gallinari
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012
282012
AI-based mobile application to fight antibiotic resistance
M Pascucci, G Royer, J Adamek, MA Asmar, D Aristizabal, L Blanche, ...
Nature communications 12 (1), 1173, 2021
272021
Sequential approaches for learning datum-wise sparse representations
G Dulac-Arnold, L Denoyer, P Preux, P Gallinari
Machine learning 89, 87-122, 2012
222012
Sequentially Generated Instance-Dependent Image Representations for Classification
M Cord, N Thome, L Denoyer, G Dulac-Arnold
ICLR, 2013
20*2013
Learning dynamics models for model predictive agents
M Lutter, L Hasenclever, A Byravan, G Dulac-Arnold, P Trochim, N Heess, ...
arXiv preprint arXiv:2109.14311, 2021
192021
L2rpn: Learning to run a power network in a sustainable world neurips2020 challenge design
A Marot, I Guyon, B Donnot, G Dulac-Arnold, P Panciatici, M Awad, ...
Tutorial5/pdf/111. pdf, 2020
102020
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