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BMCBI
2010
109views more  BMCBI 2010»
15 years 6 months ago
Predicting gene function using hierarchical multi-label decision tree ensembles
Background: S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challe...
Leander Schietgat, Celine Vens, Jan Struyf, Hendri...
CORR
2010
Springer
152views Education» more  CORR 2010»
15 years 6 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
NPL
2006
137views more  NPL 2006»
15 years 6 months ago
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Chih-Ming Chen, Yung-Feng Lu, Chin-Ming Hong
IJON
2007
88views more  IJON 2007»
15 years 6 months ago
Information maximization in face processing
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
Marian Stewart Bartlett
CVPR
2009
IEEE
17 years 1 months ago
Multiple Instance Feature for Robust Part-based Object Detection
Feature misalignment in object detection refers to the phenomenon that features which re up in some positive detection windows do not re up in other pos- itive detection windo...
Zhe Lin (University of Maryland at College Park), ...