Zobrazeno 1 - 10
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pro vyhledávání: '"Duflos, Emmanuel"'
Autor:
Kadri, Hachem, Duflos, Emmanuel, Preux, Philippe, Canu, Stéphane, Rakotomamonjy, Alain, Audiffren, Julien
Publikováno v:
Journal of Machine Learning Research 17 (2016) 1-54
In this paper we consider the problems of supervised classification and regression in the case where attributes and labels are functions: a data is represented by a set of functions, and the label is also a function. We focus on the use of reproducin
Externí odkaz:
http://arxiv.org/abs/1510.08231
Publikováno v:
28th International Conference on Machine Learning (ICML), Seattle : United States (2011)
Although operator-valued kernels have recently received increasing interest in various machine learning and functional data analysis problems such as multi-task learning or functional regression, little attention has been paid to the understanding of
Externí odkaz:
http://arxiv.org/abs/1301.2655
Publikováno v:
2nd International Workshop on Functional and Operatorial Statistics (IWFOS), Santander : Spain (2011)
In this paper we present a nonparametric method for extending functional regression methodology to the situation where more than one functional covariate is used to predict a functional response. Borrowing the idea from Kadri et al. (2010a), the meth
Externí odkaz:
http://arxiv.org/abs/1301.2656
This paper introduces a new approach to solve sensor management problems. Classically sensor management problems can be well formalized as Partially-Observed Markov Decision Processes (POMPD). The original approach developped here consists in derivin
Externí odkaz:
http://arxiv.org/abs/0903.3329
Publikováno v:
FUSION 2007 (2007)
The question tackled here is the time allocation of radars in a multitarget environment. At a given time radars can only observe a limited part of the space; it is therefore necessary to move their axis with respect to time, in order to be able to ex
Externí odkaz:
http://arxiv.org/abs/0903.3100
Publikováno v:
IEEE Transactions on Signal Processing (2006)
Using Kalman techniques, it is possible to perform optimal estimation in linear Gaussian state-space models. We address here the case where the noise probability density functions are of unknown functional form. A flexible Bayesian nonparametric nois
Externí odkaz:
http://arxiv.org/abs/math/0702225
Publikováno v:
In Digital Signal Processing December 2014 35:21-36
Autor:
Ben Saïd, Salma, Marzouk, Sihem Bouyahia, Duflos, Emmanuel, Vanheeghe, Philippe, Ellouze, Noureddine
Publikováno v:
In IFAC Proceedings Volumes 2010 43(8):337-340
Akademický článek
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Publikováno v:
In International Journal of Approximate Reasoning 2008 48(2):419-436