A distributed asynchronous and privacy preserving neural network ensemble selection approach for peer-to-peer data mining. - Yiannis Kokkinos; Konstantinos G. Margaritis (BCI, 2012)

A Parallel Radial Basis Probabilistic Neural Network for Scalable Data Mining in Distributed Memory Machines. - Yiannis Kokkinos; Konstantinos G. Margaritis (ICTAI, 2012)

A Regularization Network Committee Machine of Isolated Regularization Networks for Distributed Privacy Preserving Data Mining. - Yiannis Kokkinos; Konstantinos G. Margaritis (AIAI (1), 2012)

Parallelism, Localization and Chain Gradient Tuning Combinations for Fast Scalable Probabilistic Neural Networks in Data Mining Applications. - Yiannis Kokkinos; Konstantinos G. Margaritis (SETN, 2012)

Parallel and local learning for fast probabilistic neural networks in scalable data mining. - Yiannis Kokkinos; Konstantinos G. Margaritis (BCI, 2013)

A Parallel and Hierarchical Markovian RBF Neural Network: Preliminary Performance Evaluation. - Yiannis Kokkinos; Konstantinos G. Margaritis (EANN (1), 2013)

Distributed privacy-preserving P2P data mining via probabilistic neural network committee machines. - Yiannis Kokkinos; Konstantinos G. Margaritis (IISA, 2013)

Breaking Ties of Plurality Voting in Ensembles of Distributed Neural Network Classifiers Using Soft Max Accumulations. - Yiannis Kokkinos; Konstantinos G. Margaritis (AIAI, 2014)

A distributed privacy-preserving regularization network committee machine of isolated Peer classifiers for P2P data mining. - Yiannis Kokkinos; Konstantinos G. Margaritis (Artif. Intell. Rev., 2014)

Multithreaded Local Learning Regularization Neural Networks for Regression Tasks. - Yiannis Kokkinos; Konstantinos G. Margaritis (EANN, 2015)

A fast progressive local learning regression ensemble of generalized regression neural networks. - Yiannis Kokkinos; Konstantinos G. Margaritis (Panhellenic Conference on Informatics, 2015)

Confidence ratio affinity propagation in ensemble selection of neural network classifiers for distributed privacy-preserving data mining. - Yiannis Kokkinos; Konstantinos G. Margaritis (Neurocomputing, 2015)

Topology and simulations of a Hierarchical Markovian Radial Basis Function Neural Network classifier. - Yiannis Kokkinos; Konstantinos G. Margaritis (Inf. Sci., 2015)

Exemplar Selection via Leave-One-Out Kernel Averaged Gradient Descent and Subtractive Clustering. - Yiannis Kokkinos; Konstantinos G. Margaritis (AIAI, 2016)

Large scale data mining via parallel and distributed neural networks and machine learning schemes - Yiannis Kokkinos (2016)

Local learning regularization networks for localized regression. - Yiannis Kokkinos; Konstantinos G. Margaritis (Neural Comput. Appl., 2017)

Big data regression with parallel enhanced and convex incremental extreme learning machines. - Yiannis Kokkinos; Konstantinos G. Margaritis (Comput. Intell., 2018)

Kernel averaged gradient descent subtractive clustering for exemplar selection. - Yiannis Kokkinos; Konstantinos G. Margaritis (Evol. Syst., 2018)

Managing the computational cost of model selection and cross-validation in extreme learning machines via Cholesky, SVD, QR and eigen decompositions. - Yiannis Kokkinos; Konstantinos G. Margaritis (Neurocomputing, 2018)

Simulating parallel scalable probabilistic neural networks via exemplar selection and EM in a ring pipeline. - Yiannis Kokkinos; Konstantinos G. Margaritis (J. Comput. Sci., 2018)