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AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
13 years 12 months ago
Preference Networks: Probabilistic Models for Recommendation Systems
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
ISCI
2008
181views more  ISCI 2008»
13 years 5 months ago
Attribute reduction in decision-theoretic rough set models
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Yiyu Yao, Yan Zhao
UAI
2003
13 years 7 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
CORR
2010
Springer
77views Education» more  CORR 2010»
13 years 5 months ago
Pattern Classification In Symbolic Streams via Semantic Annihilation of Information
We propose a technique for pattern classification in symbolic streams via selective erasure of observed symbols, in cases where the patterns of interest are represented as Probabil...
Ishanu Chattopadhyay, Yicheng Wen, Asok Ray
CVPR
2009
IEEE
15 years 26 days ago
Simultaneous Image Classification and Annotation
Image classification and annotation are important problems in computer vision, but rarely considered together. Intuitively, annotations provide evidence for the class label, and...
Chong Wang, David M. Blei, Fei-Fei Li