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» Evaluating Usefulness for Dynamic Classification
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AAAI
2006
15 years 6 months ago
A Direct Evolutionary Feature Extraction Algorithm for Classifying High Dimensional Data
Among various feature extraction algorithms, those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale an...
Qijun Zhao, David Zhang, Hongtao Lu
ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
15 years 5 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
EMNLP
2009
15 years 2 months ago
Supervised Learning of a Probabilistic Lexicon of Verb Semantic Classes
The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Yusuke Miyao, Jun-ichi Tsujii
CVPR
2012
IEEE
13 years 8 months ago
Contextual Boost for Pedestrian Detection
Pedestrian detection from images is an important and yet challenging task. The conventional methods usually identify human figures using image features inside the local regions. In...
Yuanyuan Ding, Jing Xiao
JPDC
2006
146views more  JPDC 2006»
15 years 5 months ago
A semi-static approach to mapping dynamic iterative tasks onto heterogeneous computing systems
Minimization of the execution time of an iterative application in a heterogeneous parallel computing environment requires an appropriate mapping scheme for matching and scheduling...
Yu-Kwong Kwok, Anthony A. Maciejewski, Howard Jay ...