Pierre Alquier

According to our database, Pierre Alquier authored at least 30 papers between 2010 and 2024.

Collaborative distances:

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

2024

User-friendly Introduction to PAC-Bayes Bounds.

Pierre Alquier

Found. Trends Mach. Learn., 2024

Convergence of Statistical Estimators via Mutual Information Bounds.

E. L. Mahdi Khribch, Pierre Alquier

CoRR, 2024

Minimax optimality of deep neural networks on dependent data via PAC-Bayes bounds.

Pierre Alquier, William Kengne

CoRR, 2024

Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning.

Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin

CoRR, 2024

2023

Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes.

Charles Riou, Pierre Alquier, Badr-Eddine Chérief-Abdellatif

CoRR, 2023

PAC-Bayesian Offline Contextual Bandits With Guarantees.

Otmane Sakhi, Pierre Alquier, Nicolas Chopin

Proceedings of the International Conference on Machine Learning, 2023

2022

Variance-Aware Estimation of Kernel Mean Embedding.

Geoffrey Wolfer, Pierre Alquier

CoRR, 2022

2021

Meta-Strategy for Learning Tuning Parameters with Guarantees.

Dimitri Meunier, Pierre Alquier

Entropy, 2021

Simultaneous dimension reduction and clustering via the NMF-EM algorithm.

Léna Carel, Pierre Alquier

Adv. Data Anal. Classif., 2021

Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions.

Pierre Alquier

Proceedings of the 38th International Conference on Machine Learning, 2021

A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix.

Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

High-dimensional VAR with low-rank transition.

Pierre Alquier, Karine Bertin, Paul Doukhan, Rémy Garnier

Stat. Comput., 2020

Approximate Bayesian Inference.

Pierre Alquier

Entropy, 2020

2019

Informed sub-sampling MCMC: approximate Bayesian inference for large datasets.

Florian Maire, Nial Friel, Pierre Alquier

Stat. Comput., 2019

Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence.

Badr-Eddine Chérief-Abdellatif, Pierre Alquier

CoRR, 2019

A Generalization Bound for Online Variational Inference.

Badr-Eddine Chérief-Abdellatif, Pierre Alquier, Mohammad Emtiyaz Khan

Proceedings of The 11th Asian Conference on Machine Learning, 2019

MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy.

Badr-Eddine Chérief-Abdellatif, Pierre Alquier

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019

2018

1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation.

Vincent Cottet, Pierre Alquier

Mach. Learn., 2018

Simpler PAC-Bayesian bounds for hostile data.

Pierre Alquier, Benjamin Guedj

Mach. Learn., 2018

Exponential inequalities for nonstationary Markov Chains.

Pierre Alquier, Paul Doukhan, Xiequan Fan

CoRR, 2018

2017

Concentration of tempered posteriors and of their variational approximations.

Pierre Alquier, James Ridgway

CoRR, 2017

Non-negative matrix factorization as a pre-processing tool for travelers temporal profiles clustering.

Léna Carel, Pierre Alquier

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Regret Bounds for Lifelong Learning.

Pierre Alquier, The Tien Mai, Massimiliano Pontil

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels.

Pierre Alquier, Nial Friel, Richard G. Everitt, Aidan Boland

Stat. Comput., 2016

On the properties of variational approximations of Gibbs posteriors.

Pierre Alquier, James Ridgway, Nicolas Chopin

J. Mach. Learn. Res., 2016

2014

PAC-Bayesian AUC classification and scoring.

James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Sparse single-index model.

Pierre Alquier, Gérard Biau

J. Mach. Learn. Res., 2013

Bayesian Methods for Low-Rank Matrix Estimation: Short Survey and Theoretical Study.

Pierre Alquier

Proceedings of the Algorithmic Learning Theory - 24th International Conference, 2013

2012

Prediction of Quantiles by Statistical Learning and Application to GDP Forecasting.

Pierre Alquier, Xiaoyin Li

Proceedings of the Discovery Science - 15th International Conference, 2012

2010

An Algorithm for Iterative Selection of Blocks of Features.

Pierre Alquier

Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010