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检索条件"主题词=Multiobjective training algorithms"
4 条 记 录,以下是1-10 订阅
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Regularized online sequential learning algorithm for single-hidden layer feedforward neural networks
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PATTERN RECOGNITION LETTERS 2011年 第14期32卷 1930-1935页
作者: Hieu Trung Huynh Won, Yonggwan HoChiMinh City Univ Ind Fac Informat Technol Ho Chi Minh City Vietnam Chonnam Natl Univ Dept Comp Engn Kwangju 500757 South Korea Chonnam Natl Univ Korea Bio IT Foundry Ctr Gwangju Kwangju 500757 South Korea Nguyen Tat Thanh Univ NTT Inst Hitechnol Ho Chi Minh City Vietnam
Online learning algorithms have been preferred in many applications due to their ability to learn by the sequentially arriving data. One of the effective algorithms recently proposed for training single hidden-layer f... 详细信息
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Noise Reduction in a Non-Homogenous Ground Penetrating Radar Problem by multiobjective Neural Networks
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IEEE TRANSACTIONS ON MAGNETICS 2009年 第3期45卷 1454-1457页
作者: Travassos, X. L., Jr. Vieira, D. A. G. Palade, V. Nicolas, A. SENAI Ctr Integrado Manufatura & Tecnol BR-41650010 Salvador BA Brazil Univ Fed Minas Gerais Dept Elect Engn BR-31270901 Belo Horizonte MG Brazil Univ Oxford Dept Comp Oxford OX1 3QD England Ecole Cent Lyon Ampere Lab F-69134 Ecully France
This paper applies artificial neural networks (ANNs) trained with a multiobjective algorithm to preprocess the ground penetrating radar data obtained from a finite-difference time-domain (FDTD) model. This preprocessi... 详细信息
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The Q-norm complexity measure and the minimum gradient method:: A novel approach to the machine learning structural risk minimization problem
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IEEE TRANSACTIONS ON NEURAL NETWORKS 2008年 第8期19卷 1415-1430页
作者: Vieira, D. A. G. Takahashi, Ricardo H. C. Palade, Vasile Vasconcelos, J. A. Caminhas, W. M. Univ Fed Minas Gerais Dept Elect Engn BR-31270010 Belo Horizonte MG Brazil Univ Fed Minas Gerais Dept Math BR-31270010 Belo Horizonte MG Brazil Univ Oxford Comp Lab Oxford OX1 3QD England
This paper presents a novel approach for dealing with the structural risk minimization (SRM) applied to a general setting of the machine learning problem. The formulation is based on the fundamental concept that super... 详细信息
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Filtering noise in regression problems using a multiobjective Leaning Algorithm
Filtering noise in regression problems using a Multiobjectiv...
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20th IEEE International Conference on Tools with Artificial Intelligence
作者: Vieira, D. A. G. Travassos, X. L., Jr. Palade, Vasile Saldanha, R. R. Univ Fed Minas Gerais Dept Elect Engn Minas Gerais Brazil Univ Oxford Dept Comp Oxford OX1 2JD England
This paper applies a Neural Networks (NN) multiobjective learning algorithm called the Minimum Gradient Method (MGM) to filter noise in regression problems. This method is based on the concept that the learning is a b... 详细信息
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