AR Team > Konstantinos I. Diamantaras

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Konstantinos I. Diamantaras

  • Professor
  • Department of Information Technology
  • Alexander Technological Educational Institute (A.TEI) of Thessaloniki, P.O BOX 141 GR T.K 57 400 Thessaloniki, Greece

Short Biography

My research interests are in the areas of machine learning, signal processing, and parallel processing. See my work on pattern recognition and classification, blind signal processing, image and video processing, neural networks, and parallel processing.
I am currently Senior Area Editor for the IEEE Signal Processing Letters, Associate Editor for the IEEE Transactions on Signal Processing, and the Journal of Signal Processing Systems (Springer). From 1999 to 2000 I have also served as Associate Editor for the IEEE Transactions on Neural Networks.
Co-author of the book “Principal Component Neural Networks: Theory and Applications”, (New York: Wiley, 1996).
In 1997, co-recipient of the IEEE Best Paper Award in the area of Neural Networks for Signal Processing for the paper “Adaptive Principal Component Extraction (APEX) and Applications”, (IEEE Trans. Signal Processing, May 1994).

Publications

2017

Adaptive Margin Slack Minimization in RKHS for Classification

Yu, Y., Diamantaras, K. I., McKelvey, T., & Kung, S. Y. (2016, March). Adaptive margin slack minimization in RKHS for classification. In Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on (pp. 2319-2323). IEEE.

Airfare Prices Prediction Using Machine Learning Techniques

Tziridis, K., Kalampokas, T., Papakostas, G. A., & Diamantaras, K. I. (2017, August). Airfare prices prediction using machine learning techniques. In Signal Processing Conference (EUSIPCO), 2017 25th European (pp. 1036-1039). IEEE.

2016

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification

Yu, Y., Diamantaras, K. I., McKelvey, T., & Kung, S. Y. (2016). Class-specific subspace kernel representations and adaptive margin slack minimization for large scale classification. IEEE transactions on neural networks and learning systems.

2017

Efficient Support Vector Machine Classification using Prototype Selection and Generation

Ougiaroglou, S., Diamantaras, K. I., & Evangelidis, G. (2016, September). Efficient Support Vector Machine Classification Using Prototype Selection and Generation. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 328-340). Springer International Publishing.

Exploring the effect of Data Reduction on Neural Network and Support Vector Machine Classification

Kernel subspace methods for pattern classification

Parallel Pattern Classification Utilizing CPU Based Kernelized Slackmin Algorithm

Papakostas, G. A., Diamantaras, K. I., & Papadimitriou, T. (2017). Parallel pattern classification utilizing GPU-based kernelized Slackmin algorithm. Journal of Parallel and Distributed Computing, 99, 90-99.

Sentiment Analysis Leveraging Emotions and Word Embeddings

Giatsoglou, M., Vozalis, M. G., Diamantaras, K., Vakali, A., Sarigiannidis, G., & Chatzisavvas, K. C. (2017). Sentiment analysis leveraging emotions and word embeddings. Expert Systems with Applications, 69, 214-224.

Research Interests

  1. Machine learning
  2. Signal processing
  3. Parallel processing