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» The structure of intrinsic complexity of learning
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ICML
2004
IEEE
14 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
PRL
2000
58views more  PRL 2000»
13 years 7 months ago
Learning mixture models using a genetic version of the EM algorithm
The need to
Aleix M. Martínez, Jordi Vitrià
ICCV
2005
IEEE
14 years 1 months ago
Visual Learning Given Sparse Data of Unknown Complexity
This study addresses the problem of unsupervised visual learning. It examines existing popular model order selection criteria before proposes two novel criteria for improving visu...
Tao Xiang, Shaogang Gong
ICANN
2009
Springer
14 years 3 days ago
Learning Complex Population-Coded Sequences
The sequential structure of complex actions is apparently at an abstract “cognitive” level in several regions of the frontal cortex, independent of the control of the immediate...
Kiran V. Byadarhaly, Mithun Perdoor, Suresh Vasa, ...
ICML
2009
IEEE
14 years 8 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas