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ISNN
2005
Springer
14 years 1 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»
13 years 8 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»
13 years 8 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»
13 years 9 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
14 years 1 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-...