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ESSEC-SUPELEC Research Workshop Series on “PLS (Partial Least Squares) Developments” - 10-11 May 2010

posted Feb 25, 2010, 4:09 AM by Marie KRATZ   [ updated Mar 26, 2010, 3:48 PM by Vincenzo ESPOSITO VINZI ]

PLS and Related Methods for cutting-edge Research
in Experimental Sciences
Methodological Advances and Challenging Applications

SUPELEC (Gif-sur-Yvette, France)

10-11 May 2010


REGISTRATION is free but compulsory before 26 April 2010
Fill in the registration form, downloadable (as a PDF file) at the bottom of this page, and send it to:

Scientific Program

10 May 2010

9h30 Arrival of participants: Welcome Coffee & Croissants

9h50 Welcome address

Facing the Real World: Recent Advances and Critical Issues of PLS Methods

Chair: Vincenzo Esposito Vinzi

 10h00-10h45             Johan Trygg (Institute of Chemistry - Umeå University, Sweden)

Role of Chemometrics and PLS methods in Personalized medicine - Opportunities and methodological challenges to transform the delivery of healthcare

 10h45-11h30            Gilbert Saporta (Chaire de Statistique appliquée - CEDRIC-CNAM, France)

PLS Regression for functional data

 11h30-12h15            Anne Laure Boulesteix (IBE - University of Munich, Germany)

PLS for prediction with high-dimensional -omics data: overview and critical issues 

12h15-14h00       Lunch (served at the SUPELEC Cantine)


                        SPARSE Partial Least Squares Regression

Chair: Arthur Tenenhaus

14h00-14h45            Sunduz Keles (University Of Wisconsin, USA)

Sparse Partial Least Squares: Theory and Applications

14h45-15h30            Kim-Anh Le Cao (The University of Queensland, Australia)

PLS extensions for integration and variable selection, application to high throughput biological data

 15h30-16h00            Edouard Duchesnay (NEUROSPIN, CEA-Saclay Center, France)

Bridging the gap between imaging and genetics with sparse PLS 

16h00-16h30       Coffee Break 

Further Topics in Causal Networks: Categorical Data and Bayesian Networks

Chair: Laura Trinchera 

16h30-17h10            Giorgio Russolillo (Chaire de Statistique appliquée - CEDRIC-CNAM, France)

The Non-Metric Partial Least Squares Approach 

17h10-17h50            Lionel Jouffe (Bayesia, France)

                                        Probabilistic Structural Equations with Bayesian Belief Networks - Principles and Applications 

11 May 2010

9h30 Arrival of participants: Welcome Coffee & Croissants


PLS Path Modeling as a General Framework for Multi-block Data Analysis

Chair: Arthur Tenenhaus

10h00-10h45            Michel Tenenhaus (HEC Paris, France)

A PLS approach to regularized generalized canonical correlation analysis

 10h45-11h30            Vincenzo Esposito Vinzi (ESSEC Business School, France)

Giorgio Russolillo  (Chaire de Statistique appliquée - CEDRIC-CNAM, France)

Laura Trinchera (SUPELEC, France)

An integrated PLS Regression-based approach for multidimensional blocks in PLS Path Modeling

 11h30-12h15            Mohamed Hanafi (ENITIAA-INRA, France)

Some Computational Results related to PLS PM and Multiblock methods


12h15-14h00       Lunch (served at the SUPELEC Cantine)


Kernel Partial Least Squares

Chair: Michel Tenenhaus

14h00-14h45            Nicole Kramer (Weierstrass-Institute Berlin, Germany)

Conjugate Gradient Regularization – a Statistical Framework for Partial Least Squares Regression

14h45-15h30            Arthur Tenenhaus (SUPELEC, France)

Kernel Generalized Canonical Correlation Analysis


15h30-16h00       Coffee Break


16h00-16h40            Philippe Bastien (L’Oréal Research, France)

Some algorithmic aspects of PLS and Kernel PLS regression with extension to PLS Cox regression


The PLS World in the XLSTAT Data Analysis Environment

16h40-17h10            Emmanuel Jakobowicz (XLSTAT - Addinsoft, France)

Advanced topics in PLS Path Modeling using XLSTAT


17h10                  Closing address and ….. see you in 2011 for the Workshop #5!!!

This workshop is run under the scientific sponsorship of the Société Française de Statistique and its Group on Data Mining et Apprentissage