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» Learning Probabilistic Models of Contours
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ICML
2003
IEEE
15 years 10 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth
ICDM
2007
IEEE
187views Data Mining» more  ICDM 2007»
15 years 4 months ago
Statistical Learning Algorithm for Tree Similarity
Tree edit distance is one of the most frequently used distance measures for comparing trees. When using the tree edit distance, we need to determine the cost of each operation, bu...
Atsuhiro Takasu, Daiji Fukagawa, Tatsuya Akutsu
CVPR
2011
IEEE
14 years 7 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li
ECCV
2008
Springer
15 years 12 months ago
Unsupervised Learning of Skeletons from Motion
Abstract. Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to le...
David A. Ross, Daniel Tarlow, Richard S. Zemel
ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
15 years 3 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong