
Understanding the population structure correction regression
Although genomewide association studies (GWAS) on complex traits have a...
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Deviation inequalities for stochastic approximation by averaging
We introduce a class of Markov chains, that contains the model of stocha...
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Tight Risk Bound for High Dimensional Time Series Completion
Initially designed for independent datas, lowrank matrix completion was...
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Metastrategy for Learning Tuning Parameters with Guarantees
Online gradient methods, like the online gradient algorithm (OGA), often...
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A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix
Continual learning (CL) is a setting in which an agent has to learn from...
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Estimation of copulas via Maximum Mean Discrepancy
This paper deals with robust inference for parametric copula models. Est...
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Nonexponentially weighted aggregation: regret bounds for unbounded loss functions
We tackle the problem of online optimization with a general, possibly un...
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Universal Robust Regression via Maximum Mean Discrepancy
Many datasets are collected automatically, and are thus easily contamina...
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Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
Many works in statistics aim at designing a universal estimation procedu...
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MMDBayes: Robust Bayesian Estimation via Maximum Mean Discrepancy
In some misspecified settings, the posterior distribution in Bayesian st...
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High dimensional VAR with low rank transition
We propose a vector autoregressive (VAR) model with a lowrank constrai...
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A Generalization Bound for Online Variational Inference
Bayesian inference provides an attractive onlinelearning framework to a...
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Matrix factorization for multivariate time series analysis
Matrix factorization is a powerful data analysis tool. It has been used ...
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Exponential inequalities for nonstationary Markov Chains
Exponential inequalities are main tools in machine learning theory. To p...
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Consistency of Variational Bayes Inference for Estimation and Model Selection in Mixtures
Mixture models are widely used in Bayesian statistics and machine learni...
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Regret Bounds for Lifelong Learning
We consider the problem of transfer learning in an online setting. Diffe...
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Simpler PACBayesian Bounds for Hostile Data
PACBayesian learning bounds are of the utmost interest to the learning ...
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1bit Matrix Completion: PACBayesian Analysis of a Variational Approximation
Due to challenging applications such as collaborative filtering, the mat...
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An Oracle Inequality for QuasiBayesian NonNegative Matrix Factorization
The aim of this paper is to provide some theoretical understanding of Ba...
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On the properties of variational approximations of Gibbs posteriors
The PACBayesian approach is a powerful set of techniques to derive non...
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PACBayesian AUC classification and scoring
We develop a scoring and classification procedure based on the PACBayes...
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Bayesian methods for lowrank matrix estimation: short survey and theoretical study
The problem of lowrank matrix estimation recently received a lot of att...
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PACBayesian Bounds for Randomized Empirical Risk Minimizers
The aim of this paper is to generalize the PACBayesian theorems proved ...
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Pierre Alquier
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