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CVPR
2012
IEEE
11 years 9 months ago
Learning latent temporal structure for complex event detection
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Kevin Tang, Fei-Fei Li, Daphne Koller
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
14 years 1 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, ...
IJCNN
2006
IEEE
14 years 1 months ago
A Variational EM Approach to Predicting Uncertainty in Supervised Learning
— In many applications of supervised learning, the conditional average of the target variables is not sufficient for prediction. The dependencies between the explanatory variabl...
Markus Harva
PAMI
1998
128views more  PAMI 1998»
13 years 7 months ago
A Hierarchical Latent Variable Model for Data Visualization
—Visualization has proven to be a powerful and widely-applicable tool for the analysis and interpretation of multivariate data. Most visualization algorithms aim to find a projec...
Christopher M. Bishop, Michael E. Tipping
WWW
2009
ACM
14 years 8 months ago
Towards context-aware search by learning a very large variable length hidden markov model from search logs
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...
Huanhuan Cao, Daxin Jiang, Jian Pei, Enhong Chen, ...