• Clustering of high dimensional data streams 

      Tasoulis, S. K.; Tasoulis, D. K.; Plagianakos, V. P. (2012)
      Clustering of data streams has become a task of great interest in the recent years as such data formats is are becoming increasingly ambiguous. In many cases, these data are also high dimensional and in result more complex ...
    • Density based projection pursuit clustering 

      Tasoulis, S. K.; Epitropakis, M. G.; Plagianakos, V. P.; Tasoulis, D. K. (2012)
      Clustering of high dimensional data is a very important task in Data Mining. In dealing with such data, we typically need to use methods like Principal Component Analysis and Projection Pursuit, to find interesting lower ...
    • Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators 

      Epitropakis, M. G.; Tasoulis, D. K.; Pavlidis, N. G.; Plagianakos, V. P.; Vrahatis, M. N. (2011)
      Differential evolution is a very popular optimization algorithm and considerable research has been devoted to the development of efficient search operators. Motivated by the different manner in which various search operators ...
    • Enhancing principal direction divisive clustering 

      Tasoulis, S. K.; Tasoulis, D. K.; Plagianakos, V. P. (2010)
      While data clustering has a long history and a large amount of research has been devoted to the development of numerous clustering techniques, significant challenges still remain. One of the most important of them is ...
    • Evolutionary principal direction divisive partitioning 

      Tasoulis, S. K.; Tasoulis, D. K.; Plagianakos, V. P. (2010)
      While data clustering has a long history and a large amount of research has been devoted to the development of clustering algorithms, significant challenges still remain. One of the most important challenges in the field ...
    • Projection based clustering of gene expression data 

      Tasoulis, S. K.; Plagianakos, V. P.; Tasoulis, D. K. (2010)
      The microarray DNA technologies have given researchers the ability to examine, discover and monitor thousands of genes in a single experiment. Nonetheless, the tremendous amount of data that can be obtained from microarray ...
    • Random direction divisive clustering 

      Tasoulis, S. K.; Tasoulis, D. K.; Plagianakos, V. P. (2013)
      Projection methods for dimension reduction have enabled the discovery of otherwise unattainable structure in ultra high dimensional data. More recently, a particular method, namely Random Projection, has been shown to have ...
    • Tracking differential evolution algorithms: An adaptive approach through multinomial distribution tracking with exponential forgetting 

      Epitropakis, M. G.; Tasoulis, D. K.; Pavlidis, N. G.; Plagianakos, V. P.; Vrahatis, M. N. (2012)
      Several Differential Evolution variants with modified search dynamics have been recently proposed, to improve the performance of the method. This work borrows ideas from adaptive filter theory to develop an "online" ...
    • Tracking Particle Swarm Optimizers: An adaptive approach through multinomial distribution tracking with exponential forgetting 

      Epitropakis, M. G.; Tasoulis, D. K.; Pavlidis, N. G.; Plagianakos, V. P.; Vrahatis, M. N. (2012)
      An active research direction in Particle Swarm Optimization (PSO) is the integration of PSO variants in adaptive, or self-adaptive schemes, in an attempt to aggregate their characteristics and their search dynamics. In ...