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» Iterative Improvement of Neural Classifiers
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TNN
2008
93views more  TNN 2008»
14 years 9 months ago
Towards the Optimal Design of Numerical Experiments
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
S. Gazut, J.-M. Martinez, Gérard Dreyfus, Y...
ICANN
2010
Springer
14 years 10 months ago
A Learned Saliency Predictor for Dynamic Natural Scenes
Abstract. We investigate the extent to which eye movements in natural dynamic scenes can be predicted with a simple model of bottom-up saliency, which learns on different visual re...
Eleonora Vig, Michael Dorr, Thomas Martinetz, Erha...
PR
2008
85views more  PR 2008»
14 years 9 months ago
Quadratic boosting
This paper presents a strategy to improve the AdaBoost algorithm with a quadratic combination of base classifiers. We observe that learning this combination is necessary to get be...
Thang V. Pham, Arnold W. M. Smeulders
BMCBI
2005
122views more  BMCBI 2005»
14 years 9 months ago
A neural strategy for the inference of SH3 domain-peptide interaction specificity
Background: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that gen...
Enrico Ferraro, Allegra Via, Gabriele Ausiello, Ma...
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IWANN
2009
Springer
15 years 4 months ago
Efficient Exact Pattern-Matching in Proteomic Sequences
Abstract. This paper proposes a novel algorithm for complete exact patternmatching focusing the specificities of protein sequences (alphabet of 20 symbols) but, also highly efficie...
Sérgio A. D. Deusdado, Paulo M. M. Carvalho