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» Incremental Construction of Structured Hidden Markov Models
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BC
2004
98views more  BC 2004»
13 years 10 months ago
A stochastic model for the detection of coherent motion
A computational model is presented for the detection of coherent motion based on template matching and hidden Markov models. The premise of this approach is that the growth in dete...
Jason Lee, Willy Wong
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
14 years 4 months ago
Mining Complex Time-Series Data by Learning Markovian Models
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
NIPS
2008
14 years 3 days ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
ICML
2006
IEEE
14 years 11 months ago
Discriminative unsupervised learning of structured predictors
We present a new unsupervised algorithm for training structured predictors that is discriminative, convex, and avoids the use of EM. The idea is to formulate an unsupervised versi...
Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dal...
ICMCS
2006
IEEE
344views Multimedia» more  ICMCS 2006»
14 years 4 months ago
Pattern Mining in Visual Concept Streams
Pattern mining algorithms are often much easier applied than quantitatively assessed. In this paper we address the pattern evaluation problem by looking at both the capability of ...
Lexing Xie, Shih-Fu Chang