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CVPR
2005
IEEE
14 years 6 months ago
Semi-Supervised Cross Feature Learning for Semantic Concept Detection in Videos
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. But a major obstacle to this is the insufficienc...
Rong Yan, Milind R. Naphade
PR
2010
186views more  PR 2010»
13 years 2 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
13 years 11 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
AIRS
2010
Springer
13 years 2 months ago
Semantic Relation Extraction Based on Semi-supervised Learning
Many tasks of information extraction or natural language processing have a property that the data naturally consist of several views--disjoint subsets of features. Specifically, a ...
Haibo Li, Yutaka Matsuo, Mitsuru Ishizuka
COLING
2008
13 years 5 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li