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作者:Yiannis Kokkinos , Konstantinos G. Margaritis
来源:[J].Neural Computing and Applications(IF 1.168), 2017, Vol.28 (6), pp.1309-1328Springer
摘要:Local learning algorithms use a neighborhood of training data close to a given testing query point in order to learn the local parameters and create on-the-fly a local model specifically designed for this query point. The local approach delivers breakthrough performance in many a...
作者:Yiannis Kokkinos , Konstantinos G. Margaritis
来源:[J].Neurocomputing(IF 1.634), 2018, Vol.295, pp.29-45Elsevier
摘要:Abstract(#br)The typical model selection strategy applied in most Extreme Learning Machine (ELM) papers depends on a k -fold cross-validation and a grid search to select the best pair { L, C } of two adjustable hyper-parameters, namely the number L of hidden ELM nodes and the reg...
作者:Panagiotis D. Michailidis , Konstantinos G. Margaritis
来源:[J].Applied Numerical Mathematics(IF 1.152), 2016, Vol.104, pp.62-80Elsevier
摘要:Abstract(#br)Numerical linear algebra is one of the most important forms of scientific computation. The basic computations in numerical linear algebra are matrix computations and linear systems solution. These computations are used as kernels in many computational problems. This ...
作者:Yiannis Kokkinos , Konstantinos G. Margaritis
来源:[J].Neurocomputing(IF 1.634), 2015, Vol.150, pp.513-528Elsevier
摘要:Abstract(#br)We consider distributed privacy-preserving data mining in large decentralized data locations which can build several neural networks to form an ensemble. The best neural network classifiers are selected via the proposed confidence ratio affinity propagation in an asy...
作者:Yiannis Kokkinos , Konstantinos G. Margaritis
来源:[J].Information Sciences(IF 3.643), 2014Elsevier
摘要:Abstract(#br)This paper presents a Hierarchical Markovian Radial Basis Function Neural Network (HiMarkovRBFNN) model that enables recursive operations. The hierarchical structure of this network is composed of recursively nested RBF Neural Networks with arbitrary levels of hierar...
作者:Yiannis Kokkinos , Konstantinos G. Margaritis
来源:[J].Artificial Intelligence Review(IF 1.565), 2014, Vol.42 (3), pp.385-402Springer
摘要:Abstract(#br)For distributed data mining in peer-to-peer systems this work describes a completely asynchronous, scalable and privacy-preserving committee machine. Regularization neural networks are used for all the Peer classifiers and the combiner committee in an embedded archit...
作者:Athanasios K. Tsadiras , Konstantinos G. Margaritis
来源:[J].International Journal of Computer Mathematics(IF 0.542), 1998, Vol.67 (1-2), pp.47-75Taylor & Francis
摘要:Fuzzy Cognitive Maps (FCMs) are a class of discrete time Artificial Neural Networks that use the structure of recurrent neural networks to create models and make inferences. Contrary to classical Expert Systems, FCM allow cycles and this increases its inference capability. Positi...
作者:Jason G. Digalakis , Konstantinos G. Margaritis
来源:[J].International Journal of Computer Mathematics(IF 0.542), 2002, Vol.79 (4), pp.403-416Taylor & Francis
摘要:This paper presents a review and experimental results on the major benchmarking functions used for performance control of Genetic Algorithms (GAs). Parameters considered include the effect of population size, crossover probability and pseudo-random number generators (PNGs). The g...
作者:Manolis Vozalis , Konstantinos G. Margaritis
来源:[J].International Journal of Computer Mathematics(IF 0.542), 2004, Vol.81 (9), pp.1077-1096Taylor & Francis
摘要:In this paper, we propose two new filtering algorithms which are a combination of user-based and item-based collaborative filtering schemes. The first one, Hybrid-Ib, identifies a reasonably large neighbourhood of similar users and then uses this subset to derive the item-based r...

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