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» On Weak Markov's Principle
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ICML
2007
IEEE
14 years 8 months ago
Spectral clustering and transductive learning with multiple views
We consider spectral clustering and transductive inference for data with multiple views. A typical example is the web, which can be described by either the hyperlinks between web ...
Dengyong Zhou, Christopher J. C. Burges
ICML
2002
IEEE
14 years 8 months ago
Pruning Improves Heuristic Search for Cost-Sensitive Learning
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
Valentina Bayer Zubek, Thomas G. Dietterich
WWW
2005
ACM
14 years 8 months ago
TruRank: taking PageRank to the limit
PageRank is defined as the stationary state of a Markov chain depending on a damping factor that spreads uniformly part of the rank. The choice of is eminently empirical, and in...
Sebastiano Vigna
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 8 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
RECOMB
2003
Springer
14 years 8 months ago
Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals
We propose a framework for modeling sequence motifs based on the maximum entropy principle (MEP). We recommend approximating short sequence motif distributions with the maximum en...
Gene W. Yeo, Christopher B. Burge