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» A selective sampling approach to active feature selection
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PAKDD
2004
ACM
143views Data Mining» more  PAKDD 2004»
14 years 2 months ago
Compact Dual Ensembles for Active Learning
Generic ensemble methods can achieve excellent learning performance, but are not good candidates for active learning because of their different design purposes. We investigate how...
Amit Mandvikar, Huan Liu, Hiroshi Motoda
CVPR
2004
IEEE
14 years 23 days ago
Face Localization via Hierarchical CONDENSATION with Fisher Boosting Feature Selection
We formulate face localization as a Maximum A Posteriori Probability(MAP) problem of finding the best estimation of human face configuration in a given image. The a prior distribu...
Jilin Tu, ZhenQiu Zhang, Zhihong Zeng, Thomas S. H...
PCM
2004
Springer
106views Multimedia» more  PCM 2004»
14 years 2 months ago
An Immunological Approach to Raising Alarms in Video Surveillance
Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three ty...
Lukman Sasmita, Wanquan Liu, Svetha Venkatesh
ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 9 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
MICRO
2002
IEEE
164views Hardware» more  MICRO 2002»
14 years 1 months ago
A quantitative framework for automated pre-execution thread selection
Pre-execution attacks cache misses for which conventional address-prediction driven prefetching is ineffective. In pre-execution, copies of cache miss computations are isolated fr...
Amir Roth, Gurindar S. Sohi