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NIPS
2008
13 years 11 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
ICCV
2009
IEEE
6637views Computer Vision» more  ICCV 2009»
15 years 2 months ago
A Markov Clustering Topic Model for Mining Behaviour in Video
This paper addresses the problem of fully automated mining of public space video data. A novel Markov Clustering Topic Model (MCTM) is introduced which builds on existing Dynami...
Timothy Hospedales, Shaogang Gong, Tao Xiang
CIKM
2008
Springer
13 years 12 months ago
Intra-document structural frequency features for semi-supervised domain adaptation
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
Andrew Arnold, William W. Cohen
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 10 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
TKDE
2012
245views Formal Methods» more  TKDE 2012»
12 years 8 days ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung