D
Dimitris K. Tasoulis
Researcher at Imperial College London
Publications - 73
Citations - 2321
Dimitris K. Tasoulis is an academic researcher from Imperial College London. The author has contributed to research in topics: Cluster analysis & Artificial neural network. The author has an hindex of 22, co-authored 72 publications receiving 2119 citations. Previous affiliations of Dimitris K. Tasoulis include University of Patras & Winton Capital Management.
Papers
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Journal ArticleDOI
Exponentially weighted moving average charts for detecting concept drift
TL;DR: A new method for detecting concept drift which uses an exponentially weighted moving average (EWMA) chart to monitor the misclassification rate of an streaming classifier and allows the rate of false positive detections to be controlled and kept constant over time.
Journal ArticleDOI
Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators
Michael G. Epitropakis,Dimitris K. Tasoulis,Nicos G. Pavlidis,Vassilis P. Plagianakos,Michael N. Vrahatis +4 more
TL;DR: This paper incorporates a novel framework based on the proximity characteristics among the individual solutions as they evolve, which incorporates information of neighboring individuals in an attempt to efficiently guide the evolution of the population toward the global optimum.
Proceedings ArticleDOI
Parallel differential evolution
TL;DR: Experimental results indicate that the extent of information exchange among subpopulations assigned to different processor nodes, bears a significant impact on the performance of the algorithm.
Journal ArticleDOI
Nonparametric Monitoring of Data Streams for Changes in Location and Scale
TL;DR: This work considers the general problem of detecting a change in the location and/or scale parameter of a stream of random variables, and adapt several nonparametric hypothesis tests to create a streaming change detection algorithm which uses a test statistic with a null distribution independent of the data.
Proceedings ArticleDOI
Vector evaluated differential evolution for multiobjective optimization
Konstantinos E. Parsopoulos,Dimitris K. Tasoulis,Nicos G. Pavlidis,Vassilis P. Plagianakos,Michael N. Vrahatis +4 more
TL;DR: A parallel, multi-population differential evolution algorithm for multiobjective optimization is introduced, equipped with a domination selection operator to enhance its performance by favouring non-dominated individuals in the populations.