Valentin Dalibard
Valentin Dalibard
Verified email at - Homepage
Cited by
Cited by
Grandmaster level in StarCraft II using multi-agent reinforcement learning
O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ...
Nature 575 (7782), 350-354, 2019
Population based training of neural networks
M Jaderberg, V Dalibard, S Osindero, WM Czarnecki, J Donahue, ...
arXiv preprint arXiv:1711.09846, 2017
Alphastar: Mastering the real-time strategy game starcraft ii
O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, ...
DeepMind blog 2, 20, 2019
Open-ended learning leads to generally capable agents
OEL Team, A Stooke, A Mahajan, C Barros, C Deck, J Bauer, J Sygnowski, ...
arXiv preprint arXiv:2107.12808, 2021
BOAT: Building auto-tuners with structured Bayesian optimization
V Dalibard, M Schaarschmidt, E Yoneki
Proceedings of the 26th International Conference on World Wide Web, 479-488, 2017
A generalized framework for population based training
A Li, O Spyra, S Perel, V Dalibard, M Jaderberg, C Gu, D Budden, ...
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
Robocat: A self-improving foundation agent for robotic manipulation
K Bousmalis, G Vezzani, D Rao, C Devin, AX Lee, M Bauza, T Davchev, ...
arXiv preprint arXiv:2306.11706, 2023
Rapid training of deep neural networks without skip connections or normalization layers using deep kernel shaping
J Martens, A Ballard, G Desjardins, G Swirszcz, V Dalibard, ...
arXiv preprint arXiv:2110.01765, 2021
Population Based Training of Neural Networks (PBT)
M Jaderberg, V Dalibard, S Osindero, WM Czarnecki, J Donahue, ...
PrefEdge: SSD prefetcher for large-scale graph traversal
K Nilakant, V Dalibard, A Roy, E Yoneki
Proceedings of International Conference on Systems and Storage, 1-12, 2014
Discovering evolution strategies via meta-black-box optimization
R Lange, T Schaul, Y Chen, T Zahavy, V Dalibard, C Lu, S Singh, ...
Proceedings of the Companion Conference on Genetic and Evolutionary …, 2023
Discovering attention-based genetic algorithms via meta-black-box optimization
R Lange, T Schaul, Y Chen, C Lu, T Zahavy, V Dalibard, S Flennerhag
Proceedings of the Genetic and Evolutionary Computation Conference, 929-937, 2023
Faster improvement rate population based training
V Dalibard, M Jaderberg
arXiv preprint arXiv:2109.13800, 2021
Learning runtime parameters in computer systems with delayed experience injection
M Schaarschmidt, F Gessert, V Dalibard, E Yoneki
arXiv preprint arXiv:1610.09903, 2016
A framework to build bespoke auto-tuners with structured Bayesian optimisation
V Dalibard
University of Cambridge, Computer Laboratory, 2017
RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
K Bousmalis, G Vezzani, D Rao, CM Devin, AX Lee, MB Villalonga, ...
Transactions on Machine Learning Research, 2023
Population-based training of machine learning models
A Li, VC Dalibard, D Budden, O Spyra, ME Jaderberg, TJA Harley, S Perel, ...
US Patent 11,907,821, 2024
Perception-prediction-reaction agents for deep reinforcement learning
A Stooke, V Dalibard, SM Jayakumar, WM Czarnecki, M Jaderberg
arXiv preprint arXiv:2006.15223, 2020
Tuning the scheduling of distributed stochastic gradient descent with Bayesian optimization
V Dalibard, M Schaarschmidt, E Yoneki
arXiv preprint arXiv:1612.00383, 2016
Mitigating I/O latency in SSD-based graph traversal
A Roy, K Nilakant, V Dalibard, E Yoneki
University of Cambridge, Computer Laboratory, 2012
The system can't perform the operation now. Try again later.
Articles 1–20