PrefEdge: SSD Prefetcher for Large-Scale Graph Traversal. - Karthik Nilakant; Valentin Dalibard; Amitabha Roy 002; Eiko Yoneki (SYSTOR, 2014)

Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization. - Valentin Dalibard; Michael Schaarschmidt; Eiko Yoneki (CoRR, 2016)

Learning Runtime Parameters in Computer Systems with Delayed Experience Injection. - Michael Schaarschmidt; Felix Gessert; Valentin Dalibard; Eiko Yoneki (CoRR, 2016)

BOAT: Building Auto-Tuners with Structured Bayesian Optimization. - Valentin Dalibard; Michael Schaarschmidt; Eiko Yoneki (WWW, 2017)

Population Based Training of Neural Networks. - Max Jaderberg; Valentin Dalibard; Simon Osindero; Wojciech M. Czarnecki; Jeff Donahue; Ali Razavi; Oriol Vinyals; Tim Green; Iain Dunning; Karen Simonyan; Chrisantha Fernando; Koray Kavukcuoglu (CoRR, 2017)

A Generalized Framework for Population Based Training. - Ang Li 001; Ola Spyra; Sagi Perel; Valentin Dalibard; Max Jaderberg; Chenjie Gu; David Budden; Tim Harley; Pramod Gupta (KDD, 2019)

Grandmaster level in StarCraft II using multi-agent reinforcement learning. - Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; et al. (Nat., 2019)

Perception-Prediction-Reaction Agents for Deep Reinforcement Learning. - Adam Stooke; Valentin Dalibard; Siddhant M. Jayakumar; Wojciech M. Czarnecki; Max Jaderberg (CoRR, 2020)

Open-Ended Learning Leads to Generally Capable Agents. - Open Ended Learning Team; Adam Stooke; Anuj Mahajan; Catarina Barros; Charlie Deck; Jakob Bauer; Jakub Sygnowski; Maja Trebacz; Max Jaderberg; Michaël Mathieu; Nat McAleese; Nathalie Bradley-Schmieg; et al. (CoRR, 2021)

Faster Improvement Rate Population Based Training. - Valentin Dalibard; Max Jaderberg (CoRR, 2021)

Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping. - James Martens; Andy Ballard; Guillaume Desjardins; Grzegorz Swirszcz; Valentin Dalibard; Jascha Sohl-Dickstein; Samuel S. Schoenholz (CoRR, 2021)

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. - Robert Tjarko Lange; Tom Schaul; Yutian Chen 001; Chris Lu 001; Tom Zahavy; Valentin Dalibard; Sebastian Flennerhag (GECCO, 2023)

Discovering Evolution Strategies via Meta-Black-Box Optimization. - Robert Tjarko Lange; Tom Schaul; Yutian Chen 001; Tom Zahavy; Valentin Dalibard; Chris Lu 001; Satinder Singh 001; Sebastian Flennerhag (GECCO Companion, 2023)

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Devin; Alex X. Lee; Maria Bauzá 001; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (CoRR, 2023)

DemoStart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots. - Maria Bauzá 001; José Enrique Chen; Valentin Dalibard; Nimrod Gileadi; Roland Hafner; Murilo F. Martins; Joss Moore; Rugile Pevceviciute; Antoine Laurens; Dushyant Rao; Martina Zambelli; Martin A. Riedmiller; et al. (CoRR, 2024)

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Manon Devin; Alex X. Lee; Maria Bauzá Villalonga; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (Trans. Mach. Learn. Res., 2024)