Antoine Chambaz

According to our database, Antoine Chambaz authored at least 16 papers between 2006 and 2025.

Collaborative distances:

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

2025

Forecasting the cost of drought events in France by Super Learning from a short time series of many slightly dependent data.

Geoffrey Ecoto, Aurélien F. Bibaut, Antoine Chambaz

Comput. Stat., June, 2025

Probabilistic prediction of arrivals and hospitalizations in emergency departments in Île-de-France.

Herbert Susmann, Antoine Chambaz, Julie Josse, Philippe Aegerter, Mathias Wargon, Emmanuel Bacry

Int. J. Medical Informatics, 2025

Quantile Super Learning for independent and online settings with application to solar power forecasting.

Herbert Susmann, Antoine Chambaz

Comput. Stat. Data Anal., 2025

2024

Positivity-free Policy Learning with Observational Data.

Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Simple Sorting Criteria Help Find the Causal Order in Additive Noise Models.

Alexander G. Reisach, Myriam Tami, Christof Seiler, Antoine Chambaz, Sebastian Weichwald

CoRR, 2023

A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models.

Alexander G. Reisach, Myriam Tami, Christof Seiler, Antoine Chambaz, Sebastian Weichwald

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Personalized Online Machine Learning.

Ivana Malenica, Rachael V. Phillips, Romain Pirracchio, Antoine Chambaz, Alan E. Hubbard, Mark J. van der Laan

CoRR, 2021

Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning.

Aurélien Bibaut, Nathan Kallus, Maria Dimakopoulou, Antoine Chambaz, Mark J. van der Laan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Post-Contextual-Bandit Inference.

Aurélien Bibaut, Maria Dimakopoulou, Nathan Kallus, Antoine Chambaz, Mark J. van der Laan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Targeted Machine Learning: how we can use machine learning for causal inference.

Antoine Chambaz

Proceedings of the Extraction et Gestion des Connaissances, 2021

2020

Rate-adaptive model selection over a collection of black-box contextual bandit algorithms.

Aurélien F. Bibaut, Antoine Chambaz, Mark J. van der Laan

CoRR, 2020

Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits.

Aurélien Bibaut, Antoine Chambaz, Mark J. van der Laan

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Asymptotically optimal algorithms for budgeted multiple play bandits.

Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz

Mach. Learn., 2019

2016

Asymptotically Optimal Algorithms for Multiple Play Bandits with Partial Feedback.

Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz

CoRR, 2016

2015

tmle.npvi: targeted, integrative search of associations between DNA copy number and gene expression, accounting for DNA methylation.

Antoine Chambaz, Pierre Neuvial

Bioinform., 2015

2006

Sifting abstracts from Medline and evaluating their relevance to molecular biology.

Natalia Grabar, Marie-Christine Jaulent, Antoine Chambaz, Céline Lefebvre, Christian Néri

Proceedings of the Ubiquity: Technologies for Better Health in Aging Societies, 2006