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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 6 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
ICCV
2011
IEEE
12 years 6 months ago
Probabilistic Group-Level Motion Analysis and Scenario Recognition
This paper addresses the challenge of recognizing behavior of groups of individuals in unconstraint surveillance environments. As opposed to approaches that rely on agglomerative ...
Ming-Ching Chang, Nils Krahnstoever, Weina Ge
ICML
2004
IEEE
14 years 7 months ago
Automated hierarchical mixtures of probabilistic principal component analyzers
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
Ting Su, Jennifer G. Dy
CIKM
2011
Springer
12 years 6 months ago
Probabilistic near-duplicate detection using simhash
This paper offers a novel look at using a dimensionalityreduction technique called simhash [8] to detect similar document pairs in large-scale collections. We show that this algo...
Sadhan Sood, Dmitri Loguinov
PRL
2007
146views more  PRL 2007»
13 years 5 months ago
Neighbor number, valley seeking and clustering
This paper proposes a novel nonparametric clustering algorithm capable of identifying shape-free clusters. This algorithm is based on a nonparametric estimation of the normalized ...
Chaolin Zhang, Xuegong Zhang, Michael Q. Zhang, Ya...