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» Dynamically Adapting Kernels in Support Vector Machines
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NIPS
1998
13 years 9 months ago
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This paper proposes an algorithm for training SVMs: Sequential Mi...
John C. Platt
MMM
2006
Springer
133views Multimedia» more  MMM 2006»
14 years 2 months ago
A SVM-based personal recommendation system for TV programs
This paper presents a SVM-based prediction approach for constructing personal recommendation system for TV programs. We have applied Support Vector Machine (SVM) to personal predi...
Jin An Xu, Kenji Araki
ICCV
2009
IEEE
13 years 6 months ago
Realtime background subtraction from dynamic scenes
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
Li Cheng, Minglun Gong
ML
2002
ACM
106views Machine Learning» more  ML 2002»
13 years 8 months ago
Statistical Properties and Adaptive Tuning of Support Vector Machines
Yi Lin, Grace Wahba, Hao Zhang, Yoonkyung Lee
BMCBI
2008
228views more  BMCBI 2008»
13 years 8 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye