31 search results - page 2 / 7 » Semi-Supervised Distance Metric Learning by Quadratic Progra... |
KDD
2006
ACM
14 years 7 months ago
2006
ACM
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 ...
ICML
2006
IEEE
14 years 7 months ago
2006
IEEE
Quadratic program relaxations are proposed as an alternative to linear program relaxations and tree reweighted belief propagation for the metric labeling or MAP estimation problem...
KDD
2006
ACM
14 years 7 months ago
2006
ACM
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
JMLR
2012
11 years 9 months ago
2012
The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning a...
ICML
2008
IEEE
14 years 7 months ago
2008
IEEE
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...