This book constitutes the thoroughly refereed post-proceedings
of the PASCAL (pattern analysis, statistical modelling and
computational learning) Statistical and Optimization Perspectives
Workshop on Subspace, Latent Structure and Feature Selection
techniques, SLSFS 2005. The 9 revised full papers presented
together with 5 invited papers reflect the key approaches that have
been developed for subspace identification and feature selection
using dimension reduction techniques, subspace methods, random
projection methods, among others.
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