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156
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CVPR
2009
IEEE
16 years 9 months ago
Unsupervised Maximum Margin Feature Selection with Manifold Regularization
Feature selection plays a fundamental role in many pattern recognition problems. However, most efforts have been focused on the supervised scenario, while unsupervised feature s...
Bin Zhao, James Tin-Yau Kwok, Fei Wang, Changshui ...
IROS
2007
IEEE
158views Robotics» more  IROS 2007»
15 years 8 months ago
Feature selection in conditional random fields for activity recognition
Abstract— Temporal classification, such as activity recognition, is a key component for creating intelligent robot systems. In the case of robots, classification algorithms mus...
Douglas L. Vail, John D. Lafferty, Manuela M. Velo...
108
Voted
RE
2009
Springer
15 years 6 months ago
A Use Case Based Approach to Feature Models' Construction
In the research of software reuse, feature models have been widely adopted to organize the requirements of a set of applications in a software domain. However, there still lacks a...
Bo Wang, Wei Zhang, Haiyan Zhao, Zhi Jin, Hong Mei
AI
2004
Springer
15 years 2 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
16 years 2 months ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen