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DASFAA
2004
IEEE
135views Database» more  DASFAA 2004»
13 years 11 months ago
Semi-supervised Text Classification Using Partitioned EM
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Gao Cong, Wee Sun Lee, Haoran Wu, Bing Liu
ECCV
2010
Springer
14 years 5 days ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
IVC
2010
128views more  IVC 2010»
13 years 6 months ago
Online kernel density estimation for interactive learning
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...
Matej Kristan, Danijel Skocaj, Ales Leonardis
SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
13 years 9 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
NIPS
2008
13 years 9 months ago
Implicit Mixtures of Restricted Boltzmann Machines
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
Vinod Nair, Geoffrey E. Hinton