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» Learning to learn with the informative vector machine
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CIVR
2006
Springer
121views Image Analysis» more  CIVR 2006»
14 years 1 months ago
Finding Faces in Gray Scale Images Using Locally Linear Embeddings
The problem of face detection remains challenging because faces are non-rigid objects that have a high degree of variability with respect to head rotation, illumination, facial exp...
Samuel Kadoury, Martin D. Levine
ICONIP
2008
13 years 10 months ago
A Hybrid Fuzzy Approach for Human Eye Gaze Pattern Recognition
Abstract. Face perception and text reading are two of the most developed visual perceptual skills in humans. Understanding which features in the respective visual patterns make the...
Dingyun Zhu, B. Sumudu U. Mendis, Tom Gedeon, Aksh...
APBC
2004
138views Bioinformatics» more  APBC 2004»
13 years 10 months ago
Whole-Genome Functional Classification of Genes by Latent Semantic Analysis on Microarray Data
Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. The resulti...
See-Kiong Ng, Zexuan Zhu, Yew-Soon Ong
ACL
2003
13 years 10 months ago
Fast Methods for Kernel-Based Text Analysis
Kernel-based learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinatio...
Taku Kudo, Yuji Matsumoto
NIPS
2004
13 years 10 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...