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» On learning with dissimilarity functions
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AAIP
2009
14 years 11 months ago
Automated Method Induction: Functional Goes Object Oriented
The development of software engineering has had a great deal of benefits for the development of software. Along with it came a whole new paradigm of the way software is designed a...
Thomas Hieber, Martin Hofmann 0008
ECAI
2010
Springer
14 years 11 months ago
Bayesian Monte Carlo for the Global Optimization of Expensive Functions
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
Perry Groot, Adriana Birlutiu, Tom Heskes
IJON
1998
163views more  IJON 1998»
14 years 9 months ago
Normalized Gaussian Radial Basis Function networks
: The performances of Normalised RBF (NRBF) nets and standard RBF nets are compared in simple classification and mapping problems. In Normalized RBF networks, the traditional roles...
Guido Bugmann
ICCV
2009
IEEE
14 years 7 months ago
Local distance functions: A taxonomy, new algorithms, and an evaluation
We present a taxonomy for local distance functions where most existing algorithms can be regarded as approximations of the geodesic distance defined by a metric tensor. We categor...
Deva Ramanan, Simon Baker
ICDAR
2011
IEEE
13 years 9 months ago
Functional-Based Table Category Identification in Digital Library
– Better understanding the document logical components is crucial to many applications, e.g., document classification or data integration. As the development of digital libraries...
Seongchan Kim, Ying Liu