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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 5 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
ICML
2007
IEEE
14 years 8 months ago
Sample compression bounds for decision trees
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
Mohak Shah
ICDM
2006
IEEE
164views Data Mining» more  ICDM 2006»
14 years 1 months ago
Unsupervised Learning of Tree Alignment Models for Information Extraction
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...
Philip Zigoris, Damian Eads, Yi Zhang
RIVF
2008
13 years 9 months ago
Unsupervised learning for image classification based on distribution of hierarchical feature tree
The classification image into one of several categories is a problem arisen naturally under a wide range of circumstances. In this paper, we present a novel unsupervised model for ...
Thach-Thao Duong, Joo-Hwee Lim, Hai-Quan Vu, Jean-...
CVPR
2008
IEEE
14 years 9 months ago
Learning stick-figure models using nonparametric Bayesian priors over trees
We present a fully probabilistic stick-figure model that uses a nonparametric Bayesian distribution over trees for its structure prior. Sticks are represented by nodes in a tree i...
Edward Meeds, David A. Ross, Richard S. Zemel, Sam...