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ICASSP
2010
IEEE
13 years 8 months ago
2010
IEEE
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...
ESANN
2000
13 years 9 months ago
2000
We present a binocular robot that learns compensatory camera movements for image stabilization purposes. Most essential in achieving satisfactory image stabilization performance i...
ACL
2012
11 years 10 months ago
2012
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
CVPR
2012
IEEE
11 years 10 months ago
2012
IEEE
Metric learning is a fundamental problem in computer vision. Different features and algorithms may tackle a problem from different angles, and thus often provide complementary inf...