2.3 Discriminative clustering for high-dimensional data (Camille Brunet)

Update: 2014-12-03

Description

A new family of 12 probabilistic models, introduced recently, aims to simultaneously cluster and visualize high-dimensional data. It is based on a mixture model which fits the data into a latent discriminative subspace with an intrinsic dimension bounded by the number of clusters. An estimation procedure, named the Fisher-EM algorithm has also been proposed and turns out to outperform other subspace clustering in most situations. Moreover the convergence properties of the Fisher-EM algorithm are discussed; in particular it is proved that the algorithm is a GEM algorithm and converges under weak conditions in the general case. Finally, a sparse extension of the Fisher-EM algorithm is proposed in order to perform a selection of the original variables which are discriminative.

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In Channel

1.1 Dimension reduction based on finite mixture modeling of inverse regression (Luca Scrucca)

2014-12-0301:00:06

1.2 Information Visualization: An Introduction to the Field and Applications for Statistics (Petra Isenberg)

2014-12-0346:33

2.1 Hypothesis Testing and Bayesian Inference: New Applications of Kernel Methods (Arthur Gretton)

2014-12-0357:28

2.2 Functional estimation in high dimensional data : Application to classification (Sophie Dabo-Niang)

2014-12-0346:15

2.3 Discriminative clustering for high-dimensional data (Camille Brunet)

2014-12-0356:08

3.1 Exploring Clustering Structure in Ranking Data (Brendan Murphy)

2014-12-0301:04:11

3.2 Co-clustering under different approaches (Mohamed Nadif)

2014-12-0357:03

3.3 Complexity control in overlapping stochastic block models (Pierre Latouche)

2014-12-0354:08

4.1 Data-driven penalties: heuristics, results and thoughts... (Pascal Massart)

2014-12-0348:32

4.2 A sliced inverse regression approach for block-wise evolving data streams (Jérôme Saracco)

2014-12-0350:11

4.3 Transfer to an Unlabeled Task using kernel marginal predictors (Gilles Blanchard)

2014-12-0351:30

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2.3 Discriminative clustering for high-dimensional data (Camille Brunet)

#box-pro-ellipsis-176627819591284{-webkit-line-clamp:2;}2.3 Discriminative clustering for high-dimensional data (Camille Brunet)

2.3 Discriminative clustering for high-dimensional data (Camille Brunet)

Charles Bouveyron

2.3 Discriminative clustering for high-dimensional data (Camille Brunet)