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» Co-Tracking Using Semi-Supervised Support Vector Machines
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ICML
2005
IEEE
16 years 7 months ago
Object correspondence as a machine learning problem
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspo...
Bernhard Schölkopf, Florian Steinke, Volker B...
KDD
1995
ACM
139views Data Mining» more  KDD 1995»
15 years 9 months ago
Extracting Support Data for a Given Task
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
Bernhard Schölkopf, Chris Burges, Vladimir Va...
CEC
2007
IEEE
15 years 10 months ago
Prediction of protein interactions by combining genetic algorithm with SVM method
This paper proposes a novel hybrid GA/SVM method that can predict the interactions between proteins intermediated by the protein-domain relations. Firstly, we represented a protein...
Bing Wang, Lu-Sheng Ge, Wen-You Jia, Li Liu, Fu-Ch...
PKDD
2009
Springer
88views Data Mining» more  PKDD 2009»
16 years 24 days ago
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
Huyen Do, Alexandros Kalousis, Melanie Hilario
CIDM
2007
IEEE
15 years 10 months ago
Identifying Anatomical Phrases in Clinical Reports by Shallow Semantic Parsing Methods
Natural Language Processing (NLP) is being applied for several information extraction tasks in the biomedical domain. The unique nature of clinical information requires the need fo...
Vijayaraghavan Bashyam, Ricky K. Taira