
Optimal ChangePoint Detection and Localization
Given a times series Y in ℝ^n, with a piecewise contant mean and indepe...
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Benign overfitting in the large deviation regime
We investigate the benign overfitting phenomenon in the large deviation ...
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Aggregated HoldOut
Aggregated holdout (Agghoo) is a method which averages learning rules s...
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Lecture Notes: Selected topics on robust statistical learning theory
These notes gather recent results on robust statistical learning theory....
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A quantitative Mc Diarmid's inequality for geometrically ergodic Markov chains
We state and prove a quantitative version of the bounded difference ineq...
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Pair Matching: When bandits meet stochastic block model
The pairmatching problem appears in many applications where one wants t...
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Robust high dimensional learning for Lipschitz and convex losses
We establish risk bounds for Regularized Empirical Risk Minimizers (RERM...
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Median of means principle as a divideandconquer procedure for robustness, subsampling and hyperparameters tuning
Many learning methods have poor risk estimates with large probability un...
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A Bayesian nonparametric approach for generalized BradleyTerry models in random environment
This paper deals with the estimation of the unknown distribution of hidd...
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Robust classification via MOM minimization
We present an extension of Vapnik's classical empirical risk minimizer (...
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Density estimation for RWRE
We consider the problem of nonparametric density estimation of a random...
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MONK  OutlierRobust Mean Embedding Estimation by MedianofMeans
Mean embeddings provide an extremely flexible and powerful tool in machi...
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Robust machine learning by medianofmeans : theory and practice
We introduce new estimators for robust machine learning based on median...
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Matthieu Lerasle
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