Antoine Dedieu

According to our database1, Antoine Dedieu authored at least 20 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Diffusion Model Predictive Control.
CoRR, 2024

DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors.
CoRR, 2024

Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low.
Oper. Res., January, 2023

Schema-learning and rebinding as mechanisms of in-context learning and emergence.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation.
Proceedings of the International Conference on Machine Learning, 2023

2022
Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation.
J. Mach. Learn. Res., 2022

2021
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives.
J. Mach. Learn. Res., 2021

Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping.
CoRR, 2021

Perturb-and-max-product: Sampling and learning in discrete energy-based models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Query Training: Learning and inference for directed and undirected graphical models.
CoRR, 2020

2019
An error bound for Lasso and Group Lasso in high dimensions.
CoRR, 2019

Sparse (group) learning with Lipschitz loss functions: a unified analysis.
CoRR, 2019

Learning higher-order sequential structure with cloned HMMs.
CoRR, 2019

Solving large-scale L1-regularized SVMs and cousins: the surprising effectiveness of column and constraint generation.
CoRR, 2019

Error bounds for sparse classifiers in high-dimensions.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Hierarchical Modeling and Shrinkage for User Session Length Prediction in Media Streaming.
CoRR, 2018

Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018


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