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» Objective: In Minimum Context
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ICPR
2004
IEEE
15 years 11 months ago
Learning Spatial Context from Tracking using Penalised Likelihoods
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
Hammadi Nait-Charif, Stephen J. McKenna
PR
2006
93views more  PR 2006»
14 years 9 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
SAC
1996
ACM
15 years 2 months ago
A genetic algorithm for the minimum broadcast time problem using a global precedence vector
The problem of broadcasting a message through a network is considered. The objective is to minimize the number of time steps necessary to complete the broadcast. This problem is k...
Cory J. Hoelting, Dale A. Schoenefeld, Roger L. Wa...
ESANN
2006
14 years 11 months ago
Discriminacy of the minimum range approach to blind separation of bounded sources
The Blind Source Separation (BSS) problem is often solved by maximizing objective functions reflecting the statistical dependency between outputs. Since global maximization may be ...
Dinh-Tuan Pham, Frédéric Vrins
ICRA
2007
IEEE
189views Robotics» more  ICRA 2007»
15 years 4 months ago
Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Georgios Petkos, Sethu Vijayakumar