Antoine Dedieu
Antoine Dedieu
Research Scientist at DeepMind
Verified email at - Homepage
Cited by
Cited by
The DeepMind JAX Ecosystem
I Babuschkin, K Baumli, A Bell, S Bhupatiraju, J Bruce, P Buchlovsky, ...
URL http://github. com/deepmind 24, 25, 2020
Subset selection with shrinkage: Sparse linear modeling when the SNR is low
R Mazumder, P Radchenko, A Dedieu
Operations Research 71 (1), 129-147, 2023
Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps
D George, RV Rikhye, N Gothoskar, JS Guntupalli, A Dedieu, ...
Nature communications 12 (1), 2392, 2021
Learning sparse classifiers: Continuous and mixed integer optimization perspectives
A Dedieu, H Hazimeh, R Mazumder
Journal of Machine Learning Research 22 (2021), 2021
Learning higher-order sequential structure with cloned HMMs
A Dedieu, N Gothoskar, S Swingle, W Lehrach, M Lázaro-Gredilla, ...
arXiv preprint arXiv:1905.00507, 2019
Deep reinforcement learning for 2048
A Dedieu, J Amar
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables
M Lázaro-Gredilla, W Lehrach, N Gothoskar, G Zhou, A Dedieu, D George
Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8252-8260, 2021
Solving L1-regularized SVMs and related linear programs: Revisiting the effectiveness of Column and Constraint Generation
A Dedieu, R Mazumder, H Wang
Journal of Machine Learning Research 23 (164), 1-41, 2022
A detailed mathematical theory of thalamic and cortical microcircuits based on inference in a generative vision model
D George, M Lazaro-Gredilla, W Lehrach, A Dedieu, G Zhou
Biorxiv, 2020.09. 09.290601, 2020
Improved error rates for sparse (group) learning with Lipschitz loss functions
A Dedieu
arXiv preprint arXiv:1910.08880, 2019
Error bounds for sparse classifiers in high-dimensions
A Dedieu
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX
G Zhou, N Kumar, A Dedieu, M Lázaro-Gredilla, S Kushagra, D George
arXiv preprint arXiv:2202.04110, 2022
Learning attention-controllable border-ownership for objectness inference and binding
A Dedieu, RV Rikhye, M Lázaro-Gredilla, D George
bioRxiv, 2020.12. 31.424926, 2021
Perturb-and-max-product: Sampling and learning in discrete energy-based models
M Lazaro-Gredilla, A Dedieu, D George
Advances in Neural Information Processing Systems 34, 928-940, 2021
An error bound for Lasso and Group Lasso in high dimensions
A Dedieu
arXiv preprint arXiv:1912.11398, 2019
Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping
G Zhou, W Lehrach, A Dedieu, M Lázaro-Gredilla, D George
arXiv preprint arXiv:2112.03371, 2021
Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models
A Dedieu, M Lázaro-Gredilla, D George
Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7193-7200, 2021
Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming
A Dedieu, R Mazumder, Z Zhu, H Vahabi
Proceedings of the 27th ACM International Conference on Information and …, 2018
Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation
A Dedieu, G Zhou, D George, M Lazaro-Gredilla
arXiv preprint arXiv:2302.00099, 2023
Method and system for query training
M Lazaro-Gredilla, W Lehrach, N Gothoskar, Z GuangYao, A Dedieu, ...
US Patent App. 17/482,896, 2022
The system can't perform the operation now. Try again later.
Articles 1–20