Workshop Details

CoClus: Workshop on Coclustering and Applications

Organized by Stéphane Canu, Gérard Govaert and Mohamed Nadif
14:00-18:00
Room: Tintoretto I
https://sites.google.com/site/workshopcoclustering

Co-clustering is an important tool in a variety of scientific areas including document clustering, bioinformatics and information retrieval. Compared with the classical clustering algorithms, co-clustering algorithms have been shown to be more effective in discovering certain hidden clustering structures in data. This workshop intends to provide a forum for researchers in the field of Machine Learning, Statistics, Bioinformatics and Data Mining to discuss the above and other related topics regarding co-clustering and their applications.

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14:00 – 14:15	Welcoming and Introduction Mohamed Nadif	14:00 – 14:15	Welcoming and Introduction Mohamed Nadif	14:00 – 14:15	Welcoming and Introduction	Welcoming and Introduction		14:00 – 14:15	Welcoming and Introduction Mohamed Nadif
14:15-14:45	Biclustering of high-throughput gene expression data with BiclusterMiner Asta Laiho, Andras Kiraly, Janos Abonyi and Attila Gyenesei	14:15-14:45	Biclustering of high-throughput gene expression data with BiclusterMiner Asta Laiho, Andras Kiraly, Janos Abonyi and Attila Gyenesei	14:15-14:45	Biclustering of high-throughput gene expression data with BiclusterMiner	Biclustering of high-throughput gene expression data with BiclusterMiner		14:15-14:45	Biclustering of high-throughput gene expression data with BiclusterMiner Asta Laiho, Andras Kiraly, Janos Abonyi and Attila Gyenesei
14:45-15:15	Mining Local Staircase Patterns in Noisy Data Thanh Le Van, Carolina Fierro, Tias Guns, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt and Kathleen Marchal	14:45-15:15	Mining Local Staircase Patterns in Noisy Data Thanh Le Van, Carolina Fierro, Tias Guns, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt and Kathleen Marchal	14:45-15:15	Mining Local Staircase Patterns in Noisy Data	Mining Local Staircase Patterns in Noisy Data		14:45-15:15	Mining Local Staircase Patterns in Noisy Data Thanh Le Van, Carolina Fierro, Tias Guns, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt and Kathleen Marchal
15:30-16:00	Coffee Break	15:30-16:00	Coffee Break	15:30-16:00	Coffee Break	Coffee Break		15:30-16:00	Coffee Break
16:00-16:30	TeamFinder: A Co-clustering based Framework for Finding an Effective Team of Experts in Social Networks Farnoush Farhadi, Elham Hoseini, Sattar Hashemi and Ali Hamzeh	16:00-16:30	TeamFinder: A Co-clustering based Framework for Finding an Effective Team of Experts in Social Networks Farnoush Farhadi, Elham Hoseini, Sattar Hashemi and Ali Hamzeh	16:00-16:30	TeamFinder: A Co-clustering based Framework for Finding an Effective Team of Experts in Social Networks	TeamFinder: A Co-clustering based Framework for Finding an Effective Team of Experts in Social Networks		16:00-16:30	TeamFinder: A Co-clustering based Framework for Finding an Effective Team of Experts in Social Networks Farnoush Farhadi, Elham Hoseini, Sattar Hashemi and Ali Hamzeh
16:30-17:00	Concept-based Biclustering for Internet Advertisement Dmitry Ignatov, Sergei Kuznetsov and Jonas Poelmans	16:30-17:00	Concept-based Biclustering for Internet Advertisement Dmitry Ignatov, Sergei Kuznetsov and Jonas Poelmans	16:30-17:00	Concept-based Biclustering for Internet Advertisement	Concept-based Biclustering for Internet Advertisement		16:30-17:00	Concept-based Biclustering for Internet Advertisement Dmitry Ignatov, Sergei Kuznetsov and Jonas Poelmans
17:00-17:30	An approximation of the integrated classification likelihood for the latent block model Aurore Lomet, Gérard Govaert, and Yves Grandvalet	17:00-17:30	An approximation of the integrated classification likelihood for the latent block model Aurore Lomet, Gérard Govaert, and Yves Grandvalet	17:00-17:30	An approximation of the integrated classification likelihood for the latent block model	An approximation of the integrated classification likelihood for the latent block model		17:00-17:30	An approximation of the integrated classification likelihood for the latent block model Aurore Lomet, Gérard Govaert, and Yves Grandvalet
17:30-18:00	A Triclustering Approach for Time Evolving Graphs Romain Guigours, Marc Boullé and Fabrice Rossi	17:30-18:00	A Triclustering Approach for Time Evolving Graphs Romain Guigours, Marc Boullé and Fabrice Rossi	17:30-18:00	A Triclustering Approach for Time Evolving Graphs	A Triclustering Approach for Time Evolving Graphs		17:30-18:00	A Triclustering Approach for Time Evolving Graphs Romain Guigours, Marc Boullé and Fabrice Rossi