Pierre Alquier

Orcid: 0000-0003-4249-7337

According to our database1, Pierre Alquier authored at least 28 papers between 2010 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
User-friendly Introduction to PAC-Bayes Bounds.
Found. Trends Mach. Learn., 2024

Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning.
CoRR, 2024

2023
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes.
CoRR, 2023

PAC-Bayesian Offline Contextual Bandits With Guarantees.
Proceedings of the International Conference on Machine Learning, 2023

2022
Variance-Aware Estimation of Kernel Mean Embedding.
CoRR, 2022

2021
Meta-Strategy for Learning Tuning Parameters with Guarantees.
Entropy, 2021

Simultaneous dimension reduction and clustering via the NMF-EM algorithm.
Adv. Data Anal. Classif., 2021

Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
High-dimensional VAR with low-rank transition.
Stat. Comput., 2020

Approximate Bayesian Inference.
Entropy, 2020

2019
Informed sub-sampling MCMC: approximate Bayesian inference for large datasets.
Stat. Comput., 2019

Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence.
CoRR, 2019

A Generalization Bound for Online Variational Inference.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy.
Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019

2018
1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation.
Mach. Learn., 2018

Simpler PAC-Bayesian bounds for hostile data.
Mach. Learn., 2018

Exponential inequalities for nonstationary Markov Chains.
CoRR, 2018

2017
Concentration of tempered posteriors and of their variational approximations.
CoRR, 2017

Non-negative matrix factorization as a pre-processing tool for travelers temporal profiles clustering.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Regret Bounds for Lifelong Learning.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels.
Stat. Comput., 2016

On the properties of variational approximations of Gibbs posteriors.
J. Mach. Learn. Res., 2016

2014
PAC-Bayesian AUC classification and scoring.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Sparse single-index model.
J. Mach. Learn. Res., 2013

Bayesian Methods for Low-Rank Matrix Estimation: Short Survey and Theoretical Study.
Proceedings of the Algorithmic Learning Theory - 24th International Conference, 2013

2012
Prediction of Quantiles by Statistical Learning and Application to GDP Forecasting.
Proceedings of the Discovery Science - 15th International Conference, 2012

2010
An Algorithm for Iterative Selection of Blocks of Features.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010


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