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AAAI
2008
14 years 3 days ago
Semi-supervised Classification Using Local and Global Regularization
In this paper, we propose a semi-supervised learning (SSL) algorithm based on local and global regularization. In the local regularization part, our algorithm constructs a regular...
Fei Wang, Tao Li, Gang Wang, Changshui Zhang
CVPR
2012
IEEE
12 years 29 days 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
PRL
2008
85views more  PRL 2008»
13 years 9 months ago
Reliability estimation of a statistical classifier
Pattern classification techniques derived from statistical principles have been widely studied and have proven powerful in addressing practical classification problems. In real-wo...
Pandu Ranga Rao Devarakota, Bruno Mirbach, Bjö...
JMLR
2006
132views more  JMLR 2006»
13 years 9 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof
AIPR
2000
IEEE
14 years 2 months ago
Gradient-Oriented Profiles for Unsupervised Boundary Classification
We present a method for unsupervised boundary classijication by producing and analyzing intensity profiles. Each profile is created by sampling an ellipsoidal neighborhood of voxe...
Robert J. Tamburo, George D. Stetten