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AAAI
2011
12 years 8 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi
IJCV
2007
163views more  IJCV 2007»
13 years 8 months ago
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
In this paper, we present a novel image representation that renders it possible to access natural scenes by local semantic description. Our work is motivated by the continuing effo...
Julia Vogel, Bernt Schiele
AGENTS
1999
Springer
14 years 1 months ago
A Personal News Agent That Talks, Learns and Explains
Most work on intelligent information agents has thus far focused on systems that are accessible through the World Wide Web. As demanding schedules prohibit people from continuous ...
Daniel Billsus, Michael J. Pazzani
CIKM
2008
Springer
13 years 10 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
14 years 9 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn