Amine Echraibi
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View article: Probabilistic graphical models : theory and applications to network diagnosis
Probabilistic graphical models : theory and applications to network diagnosis Open
For any Internet service provider or network operator, it is crucial to quickly and efficiently diagnose the problems that occur on the network. The benefits of a good fault diagnosis system are mainly to minimize the costs of network and …
View article: Stochastic Backpropagation through Fourier Transforms
Stochastic Backpropagation through Fourier Transforms Open
International audience
View article: Deep Infinite Mixture Models for Fault Discovery in GPON-FTTH Networks
Deep Infinite Mixture Models for Fault Discovery in GPON-FTTH Networks Open
International audience
View article: On the Variational Posterior of Dirichlet Process Deep Latent Gaussian Mixture Models
On the Variational Posterior of Dirichlet Process Deep Latent Gaussian Mixture Models Open
Thanks to the reparameterization trick, deep latent Gaussian models have shown tremendous success recently in learning latent representations. The ability to couple them however with nonparamet-ric priors such as the Dirichlet Process (DP)…
View article: An Infinite Multivariate Categorical Mixture Model for Self-Diagnosis of Telecommunication Networks
An Infinite Multivariate Categorical Mixture Model for Self-Diagnosis of Telecommunication Networks Open
International audience
View article: Bayesian Mixture Models For Semi-Supervised Clustering
Bayesian Mixture Models For Semi-Supervised Clustering Open
In most real-world applications of clustering, data is partially labeled by an expert. Classical clustering approaches have been extensively studied in the presence of partial labels, however little work has been done to treat the general …