403 search results - page 3 / 81 » Metric and Kernel Learning Using a Linear Transformation |
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
NIPS
2004
13 years 6 months ago
2004
We describe a framework for learning an object classifier from a single example. This goal is achieved by emphasizing the relevant dimensions for classification using available ex...
NIPS
2007
13 years 6 months ago
2007
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
COMPGEOM
2011
ACM
12 years 8 months ago
2011
ACM
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
In this paper, we consider a smoothing kernelbased classification rule and propose an algorithm for optimizing the performance of the rule by learning the bandwidth of the smoothi...