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ANNPR
2006
Springer
15 years 8 months ago
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Yusuke Torii, Shigeo Abe
CIVR
2006
Springer
121views Image Analysis» more  CIVR 2006»
15 years 8 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
NCI
2004
141views Neural Networks» more  NCI 2004»
15 years 5 months ago
Estimating the error at given test input points for linear regression
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
Masashi Sugiyama
ACL
1998
15 years 5 months ago
Part of Speech Tagging Using a Network of Linear Separators
We present an architecture and an on-line learning algorithm and apply it to the problem of part-ofspeech tagging. The architecture presented, SNOW, is a network of linear separat...
Dan Roth, Dmitry Zelenko
ICASSP
2010
IEEE
15 years 4 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi