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09/06/2023
Generalised Mutual Information: a Framework for Discriminative Clustering
In the last decade, recent successes in deep clustering majorly involved...
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04/14/2023
The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges
Numerical interactions leading to users sharing textual content publishe...
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02/15/2023
Are labels informative in semi-supervised learning? – Estimating and leveraging the missing-data mechanism
Semi-supervised learning is a powerful technique for leveraging unlabele...
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02/07/2023
Sparse GEMINI for Joint Discriminative Clustering and Feature Selection
Feature selection in clustering is a hard task which involves simultaneo...
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10/12/2022
Generalised Mutual Information for Discriminative Clustering
In the last decade, recent successes in deep clustering majorly involved...
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09/19/2022
Embedded Topics in the Stochastic Block Model
Communication networks such as emails or social networks are now ubiquit...
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06/07/2021
Active Speaker Detection as a Multi-Objective Optimization with Uncertainty-based Multimodal Fusion
It is now well established from a variety of studies that there is a sig...
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04/07/2021
Co-clustering of time-dependent data via Shape Invariant Model
Multivariate time-dependent data, where multiple features are observed o...
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02/03/2021
Unobserved classes and extra variables in high-dimensional discriminant analysis
In supervised classification problems, the test set may contain data poi...
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12/08/2020
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering
High-dimensional data clustering has become and remains a challenging ta...
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02/26/2020
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood
In this paper, we introduce a two step methodology to extract a hierarch...
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09/02/2019
Clustering of count data through a mixture of multinomial PCA
Count data is becoming more and more ubiquitous in a wide range of appli...
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03/08/2017
Exact Dimensionality Selection for Bayesian PCA
We present a Bayesian model selection approach to estimate the intrinsic...
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05/19/2016
Bayesian Variable Selection for Globally Sparse Probabilistic PCA
Sparse versions of principal component analysis (PCA) have imposed thems...
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01/12/2011