290 search results - page 10 / 58 » Learning hierarchical similarity metrics |
KDD
2006
ACM
14 years 8 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...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Correlation is one of the most widely used similarity measures in machine learning like Euclidean and Mahalanobis distances. However, compared with proposed numerous discriminant ...
KDD
2003
ACM
14 years 8 months ago
2003
ACM
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
JMLR
2012
11 years 10 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...
JMLR
2012
11 years 10 months ago
2012
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper...