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ICPR
2004
IEEE
16 years 8 months ago
Relevant Linear Feature Extraction Using Side-information and Unlabeled Data
"Learning with side-information" is attracting more and more attention in machine learning problems. In this paper, we propose a general iterative framework for relevant...
Changshui Zhang, Fei Wu, Yonglei Zhou
ICASSP
2009
IEEE
16 years 2 months ago
Testing fractal connectivity in multivariate long memory processes
Within the framework of long memory multivariate processes, fractal connectivity is a particular model, in which the low frequencies (coarse scales) of the interspectrum of each p...
Herwig Wendt, Antoine Scherrer, Patrice Abry, Soph...
ICRA
2008
IEEE
136views Robotics» more  ICRA 2008»
16 years 1 months ago
Toward a multi-disciplinary model for bio-robotic systems
Abstract— The design of robotic systems involves contributions from several areas of science and engineering. Electrical, mechanical and software components must be integrated to...
Richard Primerano, David Wilkie, William Regli
COMPSAC
2003
IEEE
16 years 16 days ago
Protecting Distributed Software Upgrades that Involve Message-Passing Interface Changes
We present in this paper an extension of the messagedriven confidence-driven framework that we developed for onboard guarded software upgrading. The purpose of this work is to pr...
Ann T. Tai, Kam S. Tso, William H. Sanders
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
16 years 10 days ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...