Pierre Alquier

43 papers A* 3A 2B 4C 1Journal 31Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Variational Approximations for Robust Bayesian Inference via Rho-Posteriors. CoRR E. L. Mahdi Khribch, Pierre Alquier
2025	J	`jnl`	Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes. J. Mach. Learn. Res. Charles Riou, Pierre Alquier, Badr-Eddine Chérief-Abdellatif
2025	J	`jnl`	Empirical PAC-Bayes bounds for Markov chains. CoRR Vahe Karagulyan, Pierre Alquier
2025	J	`jnl`	Variance-Aware Estimation of Kernel Mean Embedding. J. Mach. Learn. Res. Geoffrey Wolfer, Pierre Alquier
2024	J	`jnl`	Convergence of Statistical Estimators via Mutual Information Bounds. CoRR E. L. Mahdi Khribch, Pierre Alquier
2024	A*	`conf`	Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning. NeurIPS Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin
2024	J	`jnl`	Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning. CoRR Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin
2024	J	`jnl`	Minimax optimality of deep neural networks on dependent data via PAC-Bayes bounds. CoRR Pierre Alquier, William Kengne
2024	J	`jnl`	User-friendly Introduction to PAC-Bayes Bounds. Found. Trends Mach. Learn. Pierre Alquier
2023	J	`jnl`	Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes. CoRR Charles Riou, Pierre Alquier, Badr-Eddine Chérief-Abdellatif
2023	A*	`conf`	PAC-Bayesian Offline Contextual Bandits With Guarantees. ICML Otmane Sakhi, Pierre Alquier, Nicolas Chopin
2022	J	`jnl`	PAC-Bayesian Offline Contextual Bandits With Guarantees. CoRR Otmane Sakhi, Nicolas Chopin, Pierre Alquier
2022	J	`jnl`	Variance-Aware Estimation of Kernel Mean Embedding. CoRR Geoffrey Wolfer, Pierre Alquier
2021	A	`conf`	A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. AISTATS Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
2021	J	`jnl`	Meta-Strategy for Learning Tuning Parameters with Guarantees. Entropy Dimitri Meunier, Pierre Alquier
2021	J	`jnl`	Meta-strategy for Learning Tuning Parameters with Guarantees. CoRR Dimitri Meunier, Pierre Alquier
2021	A*	`conf`	Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions. ICML Pierre Alquier
2021	J	`jnl`	Simultaneous dimension reduction and clustering via the NMF-EM algorithm. Adv. Data Anal. Classif. Léna Carel, Pierre Alquier
2021	J	`jnl`	User-friendly introduction to PAC-Bayes bounds. CoRR Pierre Alquier
2020	J	`jnl`	A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. CoRR Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
2020	J	`jnl`	Approximate Bayesian Inference. Entropy Pierre Alquier
2020	J	`jnl`	High-dimensional VAR with low-rank transition. Stat. Comput. Pierre Alquier, Karine Bertin, Paul Doukhan, Rémy Garnier
2020	J	`jnl`	Non-exponentially weighted aggregation: regret bounds for unbounded loss functions. CoRR Pierre Alquier
2019	C	`conf`	A Generalization Bound for Online Variational Inference. ACML Badr-Eddine Chérief-Abdellatif, Pierre Alquier, Mohammad Emtiyaz Khan
2019	J	`jnl`	A Generalization Bound for Online Variational Inference. CoRR Badr-Eddine Chérief-Abdellatif, Pierre Alquier, Mohammad Emtiyaz Khan
2019	J	`jnl`	Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence. CoRR Badr-Eddine Chérief-Abdellatif, Pierre Alquier
2019	J	`jnl`	Informed sub-sampling MCMC: approximate Bayesian inference for large datasets. Stat. Comput. Florian Maire, Nial Friel, Pierre Alquier
2019	—	`conf`	MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy. AABI Badr-Eddine Chérief-Abdellatif, Pierre Alquier
2019	J	`jnl`	MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy. CoRR Badr-Eddine Chérief-Abdellatif, Pierre Alquier
2018	J	`jnl`	1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation. Mach. Learn. Vincent Cottet, Pierre Alquier
2018	J	`jnl`	Exponential inequalities for nonstationary Markov Chains. CoRR Pierre Alquier, Paul Doukhan, Xiequan Fan
2018	J	`jnl`	Simpler PAC-Bayesian bounds for hostile data. Mach. Learn. Pierre Alquier, Benjamin Guedj
2017	J	`jnl`	Concentration of tempered posteriors and of their variational approximations. CoRR Pierre Alquier, James Ridgway
2017	B	`conf`	Non-negative matrix factorization as a pre-processing tool for travelers temporal profiles clustering. ESANN Léna Carel, Pierre Alquier
2017	A	`conf`	Regret Bounds for Lifelong Learning. AISTATS Pierre Alquier, The Tien Mai, Massimiliano Pontil
2016	J	`jnl`	Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels. Stat. Comput. Pierre Alquier, Nial Friel, Richard G. Everitt, Aidan Boland
2016	J	`jnl`	On the properties of variational approximations of Gibbs posteriors. J. Mach. Learn. Res. Pierre Alquier, James Ridgway, Nicolas Chopin
2016	J	`jnl`	Regret Bounds for Lifelong Learning. CoRR Pierre Alquier, The Tien Mai, Massimiliano Pontil
2014	—	`conf`	PAC-Bayesian AUC classification and scoring. NIPS James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang
2013	B	`conf`	Bayesian Methods for Low-Rank Matrix Estimation: Short Survey and Theoretical Study. ALT Pierre Alquier
2013	J	`jnl`	Sparse single-index model. J. Mach. Learn. Res. Pierre Alquier, Gérard Biau
2012	B	`conf`	Prediction of Quantiles by Statistical Learning and Application to GDP Forecasting. Discovery Science Pierre Alquier, Xiaoyin Li
2010	B	`conf`	An Algorithm for Iterative Selection of Blocks of Features. ALT Pierre Alquier