Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Clérot Fabrice"'
Autor:
Vallee Emmanuel, Charlet Delphine, Galassi Francesca, Marzinotto Gabriel, Clérot Fabrice, Meyer Frank
Publikováno v:
Open Computer Science, Vol 9, Iss 1, Pp 136-144 (2019)
Addressing Answer Selection (AS) tasks with complex neural networks typically requires a large amount of annotated data to increase the accuracy of the models. In this work, we are interested in simple models that can potentially give good performanc
Externí odkaz:
https://doaj.org/article/41d341f503bd4cbe8da95b1adc3f2635
Variable selection or importance measurement of input variables to a machine learning model has become the focus of much research. It is no longer enough to have a good model, one also must explain its decisions. This is why there are so many intelli
Externí odkaz:
http://arxiv.org/abs/2307.16718
Publikováno v:
Advances in Knowledge Discovery and Management, 834, Springer International Publishing, pp.23-41, 2019, Studies in Computational Intelligence
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 homogeneous blocks. Most of those techniques are limited to variables o
Externí odkaz:
http://arxiv.org/abs/2212.11728
Publikováno v:
Advances in Knowledge Discovery and Management, 834, Springer International Publishing, pp.3-22, 2019, Studies in Computational Intelligence
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 shown their capacity to extract such structures in continuous, binary or
Externí odkaz:
http://arxiv.org/abs/2212.11725
Autor:
Bondu, Alexis, Achenchabe, Youssef, Bifet, Albert, Clérot, Fabrice, Cornuéjols, Antoine, Gama, Joao, Hébrail, Georges, Lemaire, Vincent, Marteau, Pierre-François
More and more applications require early decisions, i.e. taken as soon as possible from partially observed data. However, the later a decision is made, the more its accuracy tends to improve, since the description of the problem to hand is enriched o
Externí odkaz:
http://arxiv.org/abs/2204.13111
Publikováno v:
Extraction et gestion des connaissances 2018, Jan 2018, Paris, France. Revue des Nouvelles Technologies de l'Information, RNTI-E-34, pp.275-280, 2018, Actes de la 18{\`e}eme Conf{\'e}rence Internationale Francophone sur l'Extraction et gestion des connaissances (EGC'2018)
We propose a MAP Bayesian approach to perform and evaluate a co-clustering of mixed-type data tables. The proposed model infers an optimal segmentation of all variables then performs a co-clustering by minimizing a Bayesian model selection cost funct
Externí odkaz:
http://arxiv.org/abs/1902.02056
We leverage the Minimum Description Length (MDL) principle as a model selection technique for Bernoulli distributions and compare several types of MDL codes. We first present a simplistic crude two-part MDL code and a Normalized Maximum Likelihood (N
Externí odkaz:
http://arxiv.org/abs/1608.05522
Publikováno v:
The 32nd International Conference on Machine Learning, Jul 2015, Lille, France. 37, pp.218-227, Proceedings of The 32nd International Conference on Machine Learning
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 selected pairs of arms. We propose a new algorithm called Relative Expon
Externí odkaz:
http://arxiv.org/abs/1601.03855
We suggest a novel method of clustering and exploratory analysis of temporal event sequences data (also known as categorical time series) based on three-dimensional data grid models. A data set of temporal event sequences can be represented as a data
Externí odkaz:
http://arxiv.org/abs/1505.01300
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 optimal decision stump. Then, the decision stumps are assembled in a r
Externí odkaz:
http://arxiv.org/abs/1504.06952