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» Approximate algorithms for neural-Bayesian approaches
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GD
2006
Springer
15 years 1 months ago
Eigensolver Methods for Progressive Multidimensional Scaling of Large Data
We present a novel sampling-based approximation technique for classical multidimensional scaling that yields an extremely fast layout algorithm suitable even for very large graphs....
Ulrik Brandes, Christian Pich
ICPR
2004
IEEE
15 years 11 months ago
Efficient Model Selection for Kernel Logistic Regression
Kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively reweighted least-squares (IRWLS) algorithm. This approach suggest...
Gavin C. Cawley, Nicola L. C. Talbot
CORR
2011
Springer
220views Education» more  CORR 2011»
14 years 4 months ago
On a linear programming approach to the discrete Willmore boundary value problem and generalizations
We consider the problem of finding (possibly non connected) discrete surfaces spanning a finite set of discrete boundary curves in the three-dimensional space and minimizing (glo...
Thomas Schoenemann, Simon Masnou, Daniel Cremers

Lecture Notes
443views
16 years 7 months ago
Design and Analysis of Computer Algorithms
"This course will consist of a number of major sections. The first will be a short review of some preliminary material, including asymptotics, summations, and recurrences and ...
David M. Mount
ISCAS
2005
IEEE
133views Hardware» more  ISCAS 2005»
15 years 3 months ago
Multiobjective VLSI cell placement using distributed simulated evolution algorithm
— Simulated Evolution (SimE) is a sound stochastic approximation algorithm based on the principles of adaptation. If properly engineered it is possible for SimE to reach nearopti...
Sadiq M. Sait, Ali Mustafa Zaidi, Mustafa I. Ali