ML
2002
ACM
14 years 3 days ago
2002
ACM
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
JCB
2000
14 years 7 days ago
2000
A new method for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support...
CG
2002
Springer
14 years 8 days ago
2002
Springer
Convolution surface has the advantage of being crease-free and bulge-free over other kinds of implicit surfaces. Among the various types of skeletal elements, line segments can be...
KES
2008
Springer
14 years 12 days ago
2008
Springer
Abstract. This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting wellfounded kernel methods fo...
NIPS
2001
14 years 1 months ago
2001
A new class of Support Vector Machine (SVM) that is applicable to sequential-pattern recognition such as speech recognition is developed by incorporating an idea of non-linear tim...
IJCAI
2007
14 years 1 months ago
2007
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
AAAI
2010
14 years 1 months ago
2010
We present the design and analysis of an approximately incentive-compatible combinatorial auction. In just a single run, the auction is able to extract enough value information fr...
CDC
2008
IEEE
14 years 2 months ago
2008
IEEE
Abstract-- In this paper, we introduce the class of semiseparable kernel functions for use in constructing Lyapunov functions for distributed-parameter systems such as delaydiffere...
ECML
2004
Springer
14 years 4 months ago
2004
Springer
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...
ICPR
2002
IEEE
14 years 5 months ago
2002
IEEE
Kernel functions can be viewed as a non-linear transformation that increases the separability of the input data by mapping them to a new high dimensional space. The incorporation ...