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NIPS
2000
14 years 11 months ago
A New Approximate Maximal Margin Classification Algorithm
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
Claudio Gentile
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
15 years 1 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
ESWA
2006
122views more  ESWA 2006»
14 years 9 months ago
Transmembrane segments prediction and understanding using support vector machine and decision tree
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...
ECCC
2007
185views more  ECCC 2007»
14 years 9 months ago
Trapdoors for Hard Lattices and New Cryptographic Constructions
We show how to construct a variety of “trapdoor” cryptographic tools assuming the worst-case hardness of standard lattice problems (such as approximating the length of the sho...
Craig Gentry, Chris Peikert, Vinod Vaikuntanathan
MP
2006
137views more  MP 2006»
14 years 9 months ago
New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds
There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximat...
Yu-Hong Dai, Roger Fletcher