3 citations · 6 across the 3 of their papers we have counts for
5 papers
Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling
Robin Vogel, Mastane Achab, Stéphan Clémençon +1
We consider statistical learning problems, when the distribution of the training observations differs from the distribution involved in the risk o…
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach
Mastane Achab, Anna Korba, Stephan Clémençon
Whereas most dimensionality reduction techniques (e.g. PCA, ICA, NMF) for multivariate data essentially rely on linear algebra to a certain extent, summarizing ranking data, viewed…
Profitable Bandits
Mastane Achab, Stephan Clémençon, Aurélien Garivier
Originally motivated by default risk management applications, this paper investigates a novel problem, referred to as the profitable bandit problem here. At each step, an agent cho…
Ranking Data with Continuous Labels through Oriented Recursive Partitions
Stephan Clémençon, Mastane Achab
We formulate a supervised learning problem, referred to as continuous ranking, where a continuous real-valued label Y is assigned to an observable r.v. X taking its values in a fea…
Max K-armed bandit: On the ExtremeHunter algorithm and beyond
Mastane Achab, Stephan Clémençon, Aurélien Garivier +2
This paper is devoted to the study of the max K-armed bandit problem, which consists in sequentially allocating resources in order to detect extreme values. Our contribution is two…