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» The Kernel Trick for Distances
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BMCBI
2007
154views more  BMCBI 2007»
13 years 7 months ago
Classification of heterogeneous microarray data by maximum entropy kernel
Background: There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are c...
Wataru Fujibuchi, Tsuyoshi Kato
METRICS
2005
IEEE
14 years 1 months ago
Metrics of Software Architecture Changes Based on Structural Distance
Software architecture is an important form of abstraction, representing the overall system structure and the relationship among components. When software is modified from one ver...
Taiga Nakamura, Victor R. Basili
ICCV
2009
IEEE
1022views Computer Vision» more  ICCV 2009»
15 years 19 days ago
Kernelized Locality-Sensitive Hashing for Scalable Image Search
Fast retrieval methods are critical for large-scale and data-driven vision applications. Recent work has explored ways to embed high-dimensional features or complex distance fun...
Brian Kulis, Kristen Grauman
ICPR
2010
IEEE
14 years 1 months ago
Online Discriminative Kernel Density Estimation
—We propose a new method for online estimation of probabilistic discriminative models. The method is based on the recently proposed online Kernel Density Estimation (oKDE) framew...
Matej Kristan, Ales Leonardis
ICML
2005
IEEE
14 years 8 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...