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» Measuring Complexity of Intelligent Machines
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BMCBI
2010
161views more  BMCBI 2010»
13 years 4 months ago
Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers
Background: The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of ...
Mohammed Dakna, Keith Harris, Alexandros Kalousis,...
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
14 years 8 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
ECAL
2005
Springer
14 years 28 days ago
A Self-organising, Self-adaptable Cellular System
Abstract. Inspired by the recent advances in evolutionary biology, we have developed a self-organising, self-adaptable cellular system for multitask learning. The main aim of our p...
Lucien Epiney, Mariusz Nowostawski
MICRO
2003
IEEE
125views Hardware» more  MICRO 2003»
14 years 20 days ago
WaveScalar
Silicon technology will continue to provide an exponential increase in the availability of raw transistors. Effectively translating this resource into application performance, how...
Steven Swanson, Ken Michelson, Andrew Schwerin, Ma...
IDEAL
2003
Springer
14 years 18 days ago
Detecting Distributed Denial of Service (DDoS) Attacks through Inductive Learning
As the complexity of Internet is scaled up, it is likely for the Internet resources to be exposed to Distributed Denial of Service (DDoS) flooding attacks on TCP-based Web servers....
Sanguk Noh, Cheolho Lee, Kyunghee Choi, Gihyun Jun...