403 search results - page 26 / 81 » Metric and Kernel Learning Using a Linear Transformation |
128
click to vote
NIPS
2001
15 years 3 months ago
2001
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
116
click to vote
UAI
2000
15 years 3 months ago
2000
This paper is about the use of metric data structures in high-dimensionalor non-Euclidean space to permit cached sufficientstatisticsaccelerationsof learning algorithms. It has re...
107
Voted
ICML
2003
IEEE
16 years 2 months ago
2003
IEEE
We address the problem of learning distance metrics using side-information in the form of groups of "similar" points. We propose to use the RCA algorithm, which is a sim...
103
Voted
IJCV
2008
15 years 1 months ago
2008
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
2796
click to vote
CVPR
2011
IEEE
14 years 10 months ago
2011
IEEE
Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...