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SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
12 years 8 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
MICCAI
2000
Springer
13 years 9 months ago
Fusing Speed and Phase Information for Vascular Segmentation in Phase Contrast MR Angiograms
This paper presents a statistical approach to aggregating speed and phase (directional) information for vascular segmentation in phase contrast magnetic resonance angiograms (PC-MR...
Albert C. S. Chung, J. Alison Noble, Paul E. Summe...
ICML
2007
IEEE
14 years 6 months ago
Quadratically gated mixture of experts for incomplete data classification
We introduce quadratically gated mixture of experts (QGME), a statistical model for multi-class nonlinear classification. The QGME is formulated in the setting of incomplete data,...
Xuejun Liao, Hui Li, Lawrence Carin
SETN
2004
Springer
13 years 11 months ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas
UIST
2010
ACM
13 years 3 months ago
Mixture model based label association techniques for web accessibility
An important aspect of making the Web accessible to blind users is ensuring that all important web page elements such as links, clickable buttons, and form fields have explicitly ...
Muhammad Asiful Islam, Yevgen Borodin, I. V. Ramak...