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» On the Brittleness of Evolutionary Algorithms
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ICDAR
2009
IEEE
15 years 3 months ago
Learning Bayesian Networks by Evolution for Classifier Combination
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...
Claudio De Stefano, Francesco Fontanella, Alessand...
JDCTA
2010
175views more  JDCTA 2010»
15 years 28 days ago
Evolution Cipher against Differential Power Attack
: Differntial Power Attack (DPA) is one kind of Side Channel Attacks (SCAs). There are two phases in DPA attacks: sample collection and statistical analysis, which can be utilized ...
Shubo Liu, Ming Tang, Si Gao, Huanguo Zhang
CEC
2011
IEEE
14 years 6 months ago
Comparing alternative energy functions for the HP model of protein structure prediction
Abstract—Protein structure prediction is the problem of finding the functional conformation of a protein given only its amino uence. The HP lattice model is an abstract formulat...
Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregor...

Publication
285views
15 years 10 months ago
Center of mass encoding: a self-adaptive representation with adjustable redundancy for real-valued parameters
In this paper we describe a new class of representations for realvalued parameters called Center of Mass Encoding (CoME). CoME is based on variable length strings, it is self-adap...
Claudio Mattiussi, Peter Dürr, Dario Floreano
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 6 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos