157 citations · 179 across the 9 of their papers we have counts for
4 papers · 1 filter
Co-clustering based exploratory analysis of mixed-type data tables
Aichetou Bouchareb, Marc Boullé, Fabrice Clérot +1
Co-clustering is a class of unsupervised data analysis techniques that extract the existing underlying dependency structure between the instances and variables of a data table as h…
Model Based Co-clustering of Mixed Numerical and Binary Data
Aichetou Bouchareb, Marc Boullé, Fabrice Clérot +1
Co-clustering is a data mining technique used to extract the underlying block structure between the rows and columns of a data matrix. Many approaches have been studied and have sh…
A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits
Pratik Gajane, Tanguy Urvoy, Fabrice Clérot
We study the K-armed dueling bandit problem which is a variation of the classical Multi-Armed Bandit (MAB) problem in which the learner receives only relative feedback about the se…
Random Forest for the Contextual Bandit Problem - extended version
Raphaël Féraud, Robin Allesiardo, Tanguy Urvoy +1
To address the contextual bandit problem, we propose an online random forest algorithm. The analysis of the proposed algorithm is based on the sample complexity needed to find the…