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NIPS
2000
14 years 11 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
14 years 8 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
ICIP
2004
IEEE
15 years 11 months ago
Elliptic arc vectorization for 3d pie chart recognition
In this paper, we present a novel approach to vectorize elliptic arcs for 3D pie chart recognition and data extraction. As a preprocessing step, a set of straight line segments ar...
Weihua Huang, Chew Lim Tan, Wee Kheng Leow
GECCO
2005
Springer
146views Optimization» more  GECCO 2005»
15 years 3 months ago
An empirical study of the robustness of two module clustering fitness functions
Two of the attractions of search-based software engineering (SBSE) derive from the nature of the fitness functions used to guide the search. These have proved to be highly robust...
Mark Harman, Stephen Swift, Kiarash Mahdavi
EMMCVPR
2009
Springer
15 years 2 months ago
Complex Diffusion on Scalar and Vector Valued Image Graphs
Complex diffusion was introduced in the image processing literature as a means to achieve simultaneous denoising and enhancement of scalar valued images. In this paper, we present ...
Dohyung Seo, Baba C. Vemuri