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» A Data Model for Effectively Computable Functions
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ICML
2004
IEEE
15 years 10 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
IJON
2006
109views more  IJON 2006»
14 years 10 months ago
Integrating the improved CBP model with kernel SOM
In this paper, we first design a more generalized network model, Improved CBP, based on the same structure as Circular BackPropagation (CBP) proposed by Ridella et al. The novelty ...
Qun Dai, Songcan Chen
CGF
2008
127views more  CGF 2008»
14 years 10 months ago
Fitting Sharp Features with Loop Subdivision Surfaces
Various methods have been proposed for fitting subdivision surfaces to different forms of shape data (e.g., dense meshes or point clouds), but none of these methods effectively de...
Ruotian Ling, Wenping Wang, Dong-Ming Yan
CVPR
2010
IEEE
15 years 5 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
CIDM
2007
IEEE
15 years 1 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...