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NIPS
2008
13 years 7 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
BMCBI
2007
154views more  BMCBI 2007»
13 years 5 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
ICML
2009
IEEE
14 years 6 months ago
MedLDA: maximum margin supervised topic models for regression and classification
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Jun Zhu, Amr Ahmed, Eric P. Xing
CSB
2003
IEEE
111views Bioinformatics» more  CSB 2003»
13 years 11 months ago
A Block Coding Method that Leads to Significantly Lower Entropy Values for the Proteins and Coding Sections of Haemophilus influ
A simple statistical block code in combination with the LZW-based compression utilities gzip and compress has been found to increase by a significant amount the level of compressi...
G. Sampath
JMLR
2010
211views more  JMLR 2010»
13 years 17 days ago
Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Bo Dai, Baogang Hu