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» Evolutionary Support Vector Regression Machines
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JMLR
2010
135views more  JMLR 2010»
14 years 10 months ago
Bundle Methods for Regularized Risk Minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
BMCBI
2006
85views more  BMCBI 2006»
14 years 11 months ago
Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy
Background: Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have bee...
Rui Jiang, Hua Yang, Fengzhu Sun, Ting Chen
ICASSP
2008
IEEE
15 years 6 months ago
Learning the kernel via convex optimization
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
Seung-Jean Kim, Argyrios Zymnis, Alessandro Magnan...
MM
2006
ACM
120views Multimedia» more  MM 2006»
15 years 5 months ago
Mapping learning in eigenspace for harmonious caricature generation
This paper proposes a mapping learning approach for caricature auto-generation. Simulating the artist’s creativity based on the object’s facial feature, our approach targets d...
Junfa Liu, Yiqiang Chen, Wen Gao
DATE
2005
IEEE
114views Hardware» more  DATE 2005»
15 years 5 months ago
A Two-Level Modeling Approach to Analog Circuit Performance Macromodeling
In this paper, we present a two-level modeling approach to performance macromodeling based on radial basis function Support Vector Machine (SVM). The two-level model consists of a...
Mengmeng Ding, Ranga Vemuri