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» Approximation Methods for Supervised Learning
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BMCBI
2008
155views more  BMCBI 2008»
13 years 10 months ago
Prediction of regulatory elements in mammalian genomes using chromatin signatures
Background: Recent genomic scale survey of epigenetic states in the mammalian genomes has shown that promoters and enhancers are correlated with distinct chromatin signatures, pro...
Kyoung-Jae Won, Iouri Chepelev, Bing Ren, Wei Wang
PRL
2010
158views more  PRL 2010»
13 years 8 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
DIS
2007
Springer
14 years 4 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...
EDBT
2009
ACM
277views Database» more  EDBT 2009»
14 years 2 months ago
G-hash: towards fast kernel-based similarity search in large graph databases
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald ...
IJON
1998
158views more  IJON 1998»
13 years 9 months ago
Bayesian Kullback Ying-Yang dependence reduction theory
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Lei Xu