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» Learning with Constrained and Unlabelled Data
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ICML
2007
IEEE
14 years 10 months ago
Discriminative Gaussian process latent variable model for classification
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Raquel Urtasun, Trevor Darrell
IJSI
2008
156views more  IJSI 2008»
13 years 10 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
CVPR
2004
IEEE
14 years 12 months ago
Improving Object Classification in Far-Field Video
Object classification in far-field video sequences is a challenging problem because of low resolution imagery and projective image distortion. Most existing far-field classificati...
Biswajit Bose, W. Eric L. Grimson
AAAI
2006
13 years 11 months ago
A Simple and Effective Method for Incorporating Advice into Kernel Methods
We propose a simple mechanism for incorporating advice (prior knowledge), in the form of simple rules, into support-vector methods for both classification and regression. Our appr...
Richard Maclin, Jude W. Shavlik, Trevor Walker, Li...
CVPR
2005
IEEE
14 years 12 months ago
Hybrid Models for Human Motion Recognition
Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
Claudio Fanti, Lihi Zelnik-Manor, Pietro Perona