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» Learning large margin classifiers locally and globally
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PAMI
2006
187views more  PAMI 2006»
13 years 7 months ago
An Experimental Study on Pedestrian Classification
Detecting people in images is key for several important application domains in computer vision. This paper presents an in-depth experimental study on pedestrian classification; mul...
Stefan Munder, Dariu M. Gavrila
ANTSW
2008
Springer
13 years 9 months ago
Adaptive Particle Swarm Optimization
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perfor...
Zhi-hui Zhan, Jun Zhang
ADMA
2010
Springer
271views Data Mining» more  ADMA 2010»
13 years 2 months ago
Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Alfred Krzywicki, Wayne Wobcke
IJCV
2000
136views more  IJCV 2000»
13 years 7 months ago
A Trainable System for Object Detection
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
Constantine Papageorgiou, Tomaso Poggio
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
13 years 9 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang