30 search results - page 2 / 6 » Compression and Machine Learning: A New Perspective on Featu... |
COLT
1999
Springer
13 years 11 months ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
MIR
2004
ACM
14 years 3 days ago
2004
ACM
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...
DCC
2009
IEEE
14 years 7 months ago
2009
IEEE
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
BMCBI
2007
13 years 6 months ago
2007
Background: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression mode...