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» On the Complexity of Function Learning
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ICML
2001
IEEE
16 years 1 months ago
A Unified Loss Function in Bayesian Framework for Support Vector Regression
In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the d...
Wei Chu, S. Sathiya Keerthi, Chong Jin Ong
ICML
2005
IEEE
16 years 1 months ago
Generalized skewing for functions with continuous and nominal attributes
This paper extends previous work on skewing, an approach to problematic functions in decision tree induction. The previous algorithms were applicable only to functions of binary v...
Soumya Ray, David Page
83
Voted
ATAL
2007
Springer
15 years 6 months ago
F-trade: an agent-mining symbiont for financial services
The interaction and integration of agent technology and data mining presents prominent benefits to solve some of challenging issues in individual areas. For instance, data mining ...
Longbing Cao, Chengqi Zhang
78
Voted
ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 5 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
85
Voted
ICML
2005
IEEE
16 years 1 months ago
New kernels for protein structural motif discovery and function classification
We present new, general-purpose kernels for protein structure analysis, and describe how to apply them to structural motif discovery and function classification. Experiments show ...
Chang Wang, Stephen D. Scott