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» Learning classifiers from only positive and unlabeled data
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ICML
2005
IEEE
14 years 9 months ago
Learning discontinuities with products-of-sigmoids for switching between local models
Sensorimotor data from many interesting physical interactions comprises discontinuities. While existing locally weighted learning approaches aim at learning smooth functions, we p...
Marc Toussaint, Sethu Vijayakumar
ICPR
2006
IEEE
14 years 9 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden
DAGM
2006
Springer
14 years 12 days ago
Handling Camera Movement Constraints in Reinforcement Learning Based Active Object Recognition
In real world scenes, objects to be classified are usually not visible from every direction, since they are almost always positioned on some kind of opaque plane. When moving a cam...
Christian Derichs, Heinrich Niemann
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 9 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
INTERSPEECH
2010
13 years 3 months ago
A classifier-based target cost for unit selection speech synthesis trained on perceptual data
Our goal is to automatically learn a perceptually-optimal target cost function for a unit selection speech synthesiser. The approach we take here is to train a classifier on human...
Volker Strom, Simon King