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ISNN
2005
Springer
15 years 3 months ago
Scaling the Kernel Function to Improve Performance of the Support Vector Machine
Abstract. The present study investigates a geometrical method for optimizing the kernel function of a support vector machine. The method is an improvement of the one proposed in [4...
Peter Williams, Sheng Li, Jianfeng Feng, Si Wu
NN
2000
Springer
192views Neural Networks» more  NN 2000»
14 years 9 months ago
A new algorithm for learning in piecewise-linear neural networks
Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consistin...
Emad Gad, Amir F. Atiya, Samir I. Shaheen, Ayman E...
EOR
2008
103views more  EOR 2008»
14 years 9 months ago
New complexity analysis of IIPMs for linear optimization based on a specific self-regular function
Primal-dual Interior-Point Methods (IPMs) have shown their ability in solving large classes of optimization problems efficiently. Feasible IPMs require a strictly feasible startin...
Maziar Salahi, M. Reza Peyghami, Tamás Terl...
SECRYPT
2007
121views Business» more  SECRYPT 2007»
14 years 11 months ago
Using Steganography to Improve Hash Functions' Collision Resistance
Lately, hash function security has received increased attention. Especially after the recent attacks that were presented for SHA-1 and MD5, the need for a new and more robust hash...
Emmanouel Kellinis, Konstantinos Papapanagiotou
PPSN
2004
Springer
15 years 2 months ago
An Improved Evaluation Function for the Bandwidth Minimization Problem
This paper introduces a new evaluation function, called δ, for the Bandwidth Minimization Problem for Graphs (BMPG). Compared with the classical β evaluation function used, our Î...
Eduardo Rodriguez-Tello, Jin-Kao Hao, Jose Torres-...