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» Learning Mixtures of Gaussians
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COLT
1999
Springer
15 years 4 months ago
Covering Numbers for Support Vector Machines
—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...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
ECML
2006
Springer
15 years 4 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
ICPR
2010
IEEE
15 years 3 months ago
Vehicle Recognition As Changes in Satellite Imagery
Over the last several years, a new probabilistic representation for 3-d volumetric modeling has been developed. The main purpose of the model is to detect deviations from the norm...
Ozge Can Ozcanli, Joseph Mundy
113
Voted
TIT
2002
164views more  TIT 2002»
15 years 3 days ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini
109
Voted
IEICET
2010
80views more  IEICET 2010»
14 years 11 months ago
Theoretical Analysis of Density Ratio Estimation
Density ratio estimation has gathered a great deal of attention recently since it can be used for various data processing tasks. In this paper, we consider three methods of densit...
Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama