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JMLR
2012
13 years 4 days ago
On Nonparametric Guidance for Learning Autoencoder Representations
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
14 years 9 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...
IJDMMM
2010
128views more  IJDMMM 2010»
14 years 8 months ago
Graphical models based hierarchical probabilistic community discovery in large-scale social networks
: Real-world social networks, while disparate in nature, often comprise of a set of loose clusters (a.k.a. communities), in which members are better connected to each other than to...
Haizheng Zhang, Ke Ke, Wei Li, Xuerui Wang
IPSN
2003
Springer
15 years 2 months ago
Maximum Mutual Information Principle for Dynamic Sensor Query Problems
In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and sh...
Emre Ertin, John W. Fisher, Lee C. Potter
TASLP
2008
141views more  TASLP 2008»
14 years 9 months ago
Unsupervised Pattern Discovery in Speech
We present a novel approach to speech processing based on the principle of pattern discovery. Our work represents a departure from traditional models of speech recognition, where t...
A. S. Park, J. R. Glass