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» Learning from General Label Constraints
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CVPR
2012
IEEE
11 years 11 months ago
The Shape Boltzmann Machine: A strong model of object shape
A good model of object shape is essential in applications such as segmentation, object detection, inpainting and graphics. For example, when performing segmentation, local constra...
S. M. Ali Eslami, Nicolas Heess, John M. Winn
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 9 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
ICML
2009
IEEE
14 years 9 months ago
Multi-view clustering via canonical correlation analysis
Clustering data in high dimensions is believed to be a hard problem in general. A number of efficient clustering algorithms developed in recent years address this problem by proje...
Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu,...
ACL
2012
11 years 11 months ago
Crosslingual Induction of Semantic Roles
We argue that multilingual parallel data provides a valuable source of indirect supervision for induction of shallow semantic representations. Specifically, we consider unsupervi...
Ivan Titov, Alexandre Klementiev
KDD
2002
ACM
293views Data Mining» more  KDD 2002»
14 years 9 months ago
Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
Alexander Ypma, Tom Heskes