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» Using Problems to Learn Service-Oriented Computing
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CVPR
2007
IEEE
16 years 6 months ago
Joint Optimization of Cascaded Classifiers for Computer Aided Detection
The existing methods for offline training of cascade classifiers take a greedy search to optimize individual classifiers in the cascade, leading inefficient overall performance. W...
Murat Dundar, Jinbo Bi
ECCV
2008
Springer
15 years 6 months ago
Multiple Instance Boost Using Graph Embedding Based Decision Stump for Pedestrian Detection
Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints...
Junbiao Pang, Qingming Huang, Shuqiang Jiang
PERCOM
2004
ACM
16 years 4 months ago
A User-Guided Cognitive Agent for Network Service Selection in Pervasive Computing Environments
Connectivity is central to pervasive computing environments. We seek to catalyze a world of rich and diverse connectivity through technologies that drastically simplify the task o...
George Lee, Peyman Faratin, Steven Bauer, John Wro...
FOCS
2004
IEEE
15 years 8 months ago
Learning with Errors in Answers to Membership Queries
We study the learning models defined in [AKST97]: Learning with equivalence and limited membership queries and learning with equivalence and malicious membership queries. We show ...
Laurence Bisht, Nader H. Bshouty, Lawrance Khoury
JIIS
2006
73views more  JIIS 2006»
15 years 4 months ago
Using KCCA for Japanese-English cross-language information retrieval and document classification
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm b...
Yaoyong Li, John Shawe-Taylor