Zobrazeno 1 - 10
of 323
pro vyhledávání: '"Ersoy, Okan"'
Publikováno v:
Proceedings of International Conference on Neural Networks (ICNN'96) June 1996
A new technique of global optimization and its applications in particular to neural networks are presented. The algorithm is also compared to other global optimization algorithms such as Gradient descent (GD), Monte Carlo (MC), Genetic Algorithm (GA)
Externí odkaz:
http://arxiv.org/abs/2012.09252
Publikováno v:
Parallel and Distributed Processing Techniques and Applications, July 13-16, 1998
Parallel implementations of distributed global optimization (DGO) [13] on MP-1 and NCUBE parallel computers revealed an approximate O(n) increase in the performance of this algorithm. Therefore, the implementation of the DGO on parallel processors ca
Externí odkaz:
http://arxiv.org/abs/2012.09861
Publikováno v:
Published in IEEE-IJCNN 1999 1225-1228
A new neural network architecture (PSCNN) is developed to improve performance and speed of such networks. The architecture has all the advantages of the previous models such as self-organization and possesses some other superior characteristics such
Externí odkaz:
http://arxiv.org/abs/2008.02067
Autor:
Valencia-Zapata, Gustavo A., Gonzalez-Canas, Carolina, Zentner, Michael G., Ersoy, Okan, Klimeck, Gerhard
Several studies point out different causes of performance degradation in supervised machine learning. Problems such as class imbalance, overlapping, small-disjuncts, noisy labels, and sparseness limit accuracy in classification algorithms. Even thoug
Externí odkaz:
http://arxiv.org/abs/2004.02988
Autor:
Büchel, Julian, Ersoy, Okan
We used the Ladder Network [Rasmus et al. (2015)] to perform Hyperspectral Image Classification in a semi-supervised setting. The Ladder Network distinguishes itself from other semi-supervised methods by jointly optimizing a supervised and unsupervis
Externí odkaz:
http://arxiv.org/abs/1812.01222
Akademický článek
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Publikováno v:
PSI BGD TRANSACTIONS ON INTERNET RESEARCH 13.2 (2017)
Probabilistic mixture models have been widely used for different machine learning and pattern recognition tasks such as clustering, dimensionality reduction, and classification. In this paper, we focus on trying to solve the most common challenges re
Externí odkaz:
http://arxiv.org/abs/1709.01439
Publikováno v:
In Optics Communications 1 June 2021 488
Publikováno v:
In Swarm and Evolutionary Computation June 2020 55