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IJCNN
2006
IEEE
15 years 3 months ago
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
Gavin C. Cawley
ISNN
2005
Springer
15 years 3 months ago
Non-parametric Statistical Tests for Informative Gene Selection
This paper presents two non-parametric statistical test methods, called Kolmogorov-Smirnov (KS) and U statistic test methods, respectively, for informative gene selection of a tumo...
Jinwen Ma, Fuhai Li, Jianfeng Liu
SIGCOMM
2012
ACM
13 years 6 days ago
AutoNetkit: simplifying large scale, open-source network experimentation
We present a methodology that brings simplicity to large and comt labs by using abstraction. The networking community has appreciated the value of large scale test labs to explore...
Simon Knight, Askar Jaboldinov, Olaf Maennel, Iain...
GECCO
2007
Springer
217views Optimization» more  GECCO 2007»
14 years 11 months ago
A quantitative analysis of memory requirement and generalization performance for robotic tasks
In autonomous agent systems, memory is an important element to handle agent behaviors appropriately. We present the analysis of memory requirements for robotic tasks including wal...
DaeEun Kim
JCB
2006
185views more  JCB 2006»
14 years 9 months ago
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
Andrew Golightly, Darren J. Wilkinson