BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Aurore Archimbaud (Toulouse Business School) Invariant Coordinate 
 Selection for Identifying the Structure of Multivariate Datasets:  An Ove
 rview and Recent Developments
DTSTART:20260401T083000Z
DTEND:20260401T093000Z
DTSTAMP:20260411T231000Z
UID:indico-event-15434@indico.math.cnrs.fr
DESCRIPTION:Many classical multivariate statistical methods have been esta
 blished for decades. Among more recent developments\, Invariant Coordinate
  Selection (ICS) has emerged as a powerful and unifying framework. ICS joi
 ntly diagonalizes two scatter matrices\, encompassing various traditional 
 methods as special cases. It has evolved into a comprehensive multivariate
  technique\, applied in descriptive statistics and dimension reduction\, a
 nd used as a transformation-retransformation procedure. ICS is particularl
 y effective for dimension reduction in tasks such as outlier detection and
  clustering\, as it can recover Fisher's linear discriminant subspace with
 out requiring prior knowledge of class labels. Within the independent comp
 onent analysis (ICA) framework\, ICS also serves as a tool for identifying
  independent components. This review provides an overview of ICS\, includi
 ng its diverse applications\, recent extensions\, and available software f
 or practical implementation...\n\nhttps://indico.math.cnrs.fr/event/15434/
URL:https://indico.math.cnrs.fr/event/15434/
END:VEVENT
END:VCALENDAR