Valentin Dalibard

According to our database, Valentin Dalibard authored at least 14 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation.

Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauzá, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo F. Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, Jose Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess

CoRR, 2023

Discovering Evolution Strategies via Meta-Black-Box Optimization.

Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization.

Robert Tjarko Lange, Tom Schaul, Yutian Chen, Chris Lu, Tom Zahavy, Valentin Dalibard, Sebastian Flennerhag

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

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

Faster Improvement Rate Population Based Training.

Valentin Dalibard, Max Jaderberg

CoRR, 2021

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, Nathaniel Wong, Nicolas Porcel, Roberta Raileanu, Steph Hughes-Fitt, Valentin Dalibard, Wojciech Marian Czarnecki

CoRR, 2021

2020

Perception-Prediction-Reaction Agents for Deep Reinforcement Learning.

Adam Stooke, Valentin Dalibard, Siddhant M. Jayakumar, Wojciech M. Czarnecki, Max Jaderberg

CoRR, 2020

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, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver

Nat., 2019

A Generalized Framework for Population Based Training.

Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

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

BOAT: Building Auto-Tuners with Structured Bayesian Optimization.

Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki

Proceedings of the 26th International Conference on World Wide Web, 2017

2016

Learning Runtime Parameters in Computer Systems with Delayed Experience Injection.

Michael Schaarschmidt, Felix Gessert, Valentin Dalibard, Eiko Yoneki

CoRR, 2016

Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization.

Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki

CoRR, 2016

2014

PrefEdge: SSD Prefetcher for Large-Scale Graph Traversal.

Karthik Nilakant, Valentin Dalibard, Amitabha Roy, Eiko Yoneki

Proceedings of the International Conference on Systems and Storage, 2014