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TCBB
2010
176views more  TCBB 2010»
13 years 3 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
EMNLP
2011
12 years 5 months ago
Entire Relaxation Path for Maximum Entropy Problems
We discuss and analyze the problem of finding a distribution that minimizes the relative entropy to a prior distribution while satisfying max-norm constraints with respect to an ...
Moshe Dubiner, Yoram Singer
WWW
2007
ACM
14 years 6 months ago
Modeling user behavior in recommender systems based on maximum entropy
We propose a model for user purchase behavior in online stores that provide recommendation services. We model the purchase probability given recommendations for each user based on...
Tomoharu Iwata, Kazumi Saito, Takeshi Yamada
RECOMB
2003
Springer
14 years 5 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
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
14 years 5 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...