Aristidis Likas 

    Professor
    Department of Computer Science and Engineering
    University of Ioannina
    GR-45110 Ioannina, Greece
    Tel     : +30-26510-08810
    Fax     : +30-26510-08882
    e-mail  : arly@cs.uoi.gr

Diploma in Electrical Engineering, National Technical University of Athens, June 1990.

Ph.D. in Electrical and Computer Engineering, National Technical University of Athens, July 1994.

Research Interests

  • Neural Networks
  • Machine Learning
  • Data Mining
  • Image Processing and Analysis
  • Video Analysis and Summarization
  • Text Mining
  • Intelligent Systems in Medicine / Biology
  • Scientific Computing

Courses  (recent)

  • Artificial Intelligence (undergraduate)
  • Computational Intelligence (undergraduate)
  • Data Mining (graduate)
  • Machine Learning (graduate)

Office hours: Tuesday 9.30-11.30

Associate Editor: IEEE Transactions on Neural Networks (2008-2012)

General Co-chair: ECML/PKDD 2011, SETN 2014

 

Miscellaneous

·       The inclusion measure for community detection

·       Clustering based on unimodal projections (pdip-means)

·       Video Summarization (VIDEOSUM)

·       PRotEin S-Sulfenylation Server (PRESS)

·       Multimodality in Data Clustering: Application to Video Summarization (plenary talk at AIAI 2016)

·       Global k-means matlab code

 

Publications

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Journal Publications

·       A. Likas, and A. Stafylopatis, "Multiscaling in Binary Hopfield-type Neural Networks: Application to the Set Partitioning Problem", International Journal of Neural Networks , Vol. 3, No. 2, pp. 55-65, June 1992.

·       A. Stafylopatis and A. Likas, "Pictorial Information Retrieval Using the Random Neural Network", IEEE Transactions on Software Engineering , Vol. 18, No. 7, pp. 590-600, July 1992.

·       D. Kontoravdis, A. Likas and  A. Stafylopatis, "A Path-Finding Technique Based on the Integration of Neural Network Models at Different Levels of Abstraction", Elektrik - Special Issue on Neural Networks , Vol. 2, No. 1, pp. 40-51, April 1994 (invited paper).

·       D. Kontoravdis, A. Likas and A. Stafylopatis, "Enhancing Stochasticity in Reinforcement Learning Schemes: Application to the Exploration of Binary Domains", Journal of Intelligent Systems , Vol. 5, No. 1, pp. 49-77, 1995.

·       A. Likas and A. Stafylopatis, "Differential Association and Operational Equivalence of Discrete Hopfield Networks", Neural Network World , Vol. 5, No. 1, pp. 81-89, 1995.

·       A. Likas and A. Stafylopatis, "A Parallel Algorithm for the Minimum Weighted Vertex Cover Problem", Information Processing Letters , Vol. 53, pp. 229-234, 1995.

·       A. Likas, D. Kontoravdis and A. Stafylopatis, "Discrete Optimization Based on the Combined Use of Reinforcement and Constraint Satisfaction Schemes", Neural Computing and Applications , Vol. 3, pp. 101- 112, 1995.

·       A. Likas, G. Papageorgiou and A. Stafylopatis, "A Parallelizable Operation Scheme of the Boltzmann Machine Optimizer Based on Group Updates", Neural, Parallel and Scientific Computations , Vol. 3, pp. 451-466, 1995.

·       M. Afif, A. Likas and V. Paschos, "A Natural Model and a Parallel Algorithm for Approximately Solving the Maximum Weighted Independent Set Problem", Chaos, Solitons & Fractals , Vol. 5, No. 5, pp. 739-746, 1995.

·       A. Likas and A. Stafylopatis, "Group Updates and Multiscaling: An Efficient Neural Network Approach to Combinatorial Optimization", IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics , Vol. 26, No. 2, pp. 222-232, April 1996.

·       A. Likas, K. Blekas and A. Stafylopatis, "Parallel Recombinative Reinforcement Learning: A Genetic Approach", Journal of Intelligent Systems , vol. 6, no. 2, pp. 145-177, 1996.

·       A. Likas and K. Blekas, "A Reinforcement Learning Approach Based on the Fuzzy Min-Max Neural Network", Neural Processing Letters , vol. 4, no. 3, pp. 167-172, 1996.

·       A. Likas and A. Stafylopatis, "High Capacity Associative Memory Based on the Random Neural Network Model", International Journal of Pattern Recognition and Artificial Intelligence , vol. 10, no. 8, pp. 919-937, 1997.

·       A. Likas, G. Papageorgiou and A. Stafylopatis, "A Connectionist Approach for Solving Large Constraint Satisfaction Problems", Applied Intelligence , vol. 7, pp. 215-225, 1997.

·       I. Lagaris, A. Likas and D. Fotiadis, "Artificial Neural Network Methods in Quantum Mechanics", Computer Physics Communications , vol. 104, pp. 1-14, 1997.

·       A. Likas, D. Karras and I. Lagaris, "Neural Network Training and Simulation Using a Multidimensional Optimization System", International Journal of Computer Mathematics , vol. 67, pp. 33-46, 1998.

·       K. Blekas, A. Stafylopatis, D. Kontoravdis, A. Likas and P. Karakitsos, "Cytological Diagnosis Based on Fuzzy Neural Networks", Journal of Intelligent Systems , vol. 8, pp. 55-79, 1998.

·       G. Papageorgiou, A. Likas and A. Stafylopatis, "A Hybrid Neural Optimization Scheme Based on Parallel Updates", International Journal of Computer Mathematics , vol. 67, pp. 223-237, 1998.

·       G. Papageorgiou, A. Likas and A. Stafylopatis, "Improved exploration in Hopfield Network State-Space through Parameter Perturbation Driven by Simulated Annealing ", European Journal of Operations Research , vol. 108, no. 2, pp. 283-292, 1998.

·       I. Lagaris, A. Likas and D. Fotiadis, "Artificial Neural Networks for Solving Ordinary and Partial Differential Equations", IEEE Trans. on Neural Networks , vol. 9, no. 5, pp. 987-1000, 1998.

·       A. Likas, A. and I. Lagaris, "Training Reinforcement Neurocontrollers Using the Polytope Algorithm ", Neural Processing Letters , vol. 9, no. 2, pp. 119-127, 1999.

·       A. Likas, "A Reinforcement Learning Approach to On-Line Clustering", Neural Computation, vol. 11, no. 8, pp. 1915-1932, 1999.

·       N. Vlassis and A. Likas, "A Kurtosis-Based Dynamic Approach to Gaussian Mixture Modeling ", IEEE Trans. on Systems, Man and Cybernetics: Part A , vol. 29, no. 4, pp. 393-399, July 1999.

·       A. Likas and A. Stafylopatis, "Training the Random Neural Network Using Quasi-Newton Methods ", European Journal of Operations Research , vol. 126, no. 2, pp. 331-339, 2000.

·       I. Lagaris, A. Likas and D. Papageorgiou, "Neural Networks Methods for Boundary Value Problems with Irregular Boundaries", IEEE Trans. on Neural Networks , vol. 11, no. 5, pp. 1041-1049, Sept. 2000.

·       C. Papaloukas, D. Fotiadis, A. Liavas, A. Likas and L. Michalis, "A Knowledge-based Technique for Automated Detection of Ischemic Episodes in Long Duration ECGs", Medical and Biological Engineering and Computing , vol. 39, pp. 105-112, 2001.

·       A. Likas, "Probability Density Estimation Using Artificial Neural Networks", Computer Physics Communications , vol. 135, no. 2, pp. 167-175, 2001.

·       A. Likas, "Reinforcement Learning Using the Stochastic Fuzzy Min-Max Neural Network", Neural Processing Letters, vol. 13, pp. 213-220, 2001.

·       M. Titsias and A. Likas, "Shared Kernel Models for Class Conditional Density Estimation", IEEE Trans. on Neural Networks , vol. 12, no. 5, pp. 987-997, September 2001.

·       N. Vlassis and A. Likas, "A greedy EM algorithm for Gaussian mixture learning" , Neural Processing Letters , vol. 15, pp. 77-87, 2002.

·       A. Likas and V. Paschos, "A note on a new greedy solution representation and a new greedy parallelizable heuristic for the traveling salesman problem", Chaos, Solitons & Fractals , vol. 13, pp. 71-78, 2001.

·       C. Papaloukas, D. Fotiadis, A. Likas and L. Michalis, "Use of a Novel Rule-Based Expert System in the Detection of Changes in the ST Segment and T Wave in Long Duration ECGs", Journal of Electrocardiology , vol. 35, no. 1, pp. 27-34, 2002.

·       C. Papaloukas, D. Fotiadis, A. Likas and L. Michalis, "An Ischemia Detection Method based on Artificial Neural Networks", Artificial Intelligence in Medicine , vol. 24, no. 2, pp. 167-178, February 2002.

·       A. Likas, N. Vlassis and J. Verbeek, "The Global K-Means Clustering Algorithm" , Pattern Recognition , vol. 36, pp. 451-461, 2003.

·       A. Papadopoulos, D. Fotiadis and A. Likas, "An Automatic Microcalcification System based on a Hybrid Neural Network Classifier", Artificial Intelligence in Medicine , vol. 25, no. 2, pp. 149-167, 2002.

·       M. Titsias and A. Likas, "Mixture of Experts Classification Using a Hierarchical Mixture Model" , Neural Computation , vol. 14, no. 9, pp. 2221-2244, 2002.

·       D. Frossyniotis, A. Stafylopatis and A. Likas, "A Divide-and-Conquer Method for Multi-net Classifiers", Pattern Analysis and Applications Journal, vol. 6, no. 1, pp. 32-40, 2003.

·       M. Titsias and A. Likas, "Class Conditional Density Estimation Using Mixtures with Constrained Component Sharing" , IEEE Trans. on Pattern Analysis and Machine Intelligence , vol. 25, no.7, pp. 924-928, 2003.

·       K. Blekas, D. Fotiadis and A. Likas, "Greedy Mixture Learning for Multiple Motif Discovery in Biological Sequences", Bioinformatics , vol. 19, no. 5, pp. 609-617, 2003.

·       K. Blekas, D. Fotiadis and A. Likas, "A Sequential Method for Discovering Probabilistic Motifs in Proteins", Methods of Information in Medicine ,vol. 43, pp. 9-12, 2004.

·       D. Frossyniotis, A. Likas and A. Stafylopatis, "A Clustering Method Based on Boosting", Pattern Recognition Letters , vol. 25, pp. 641-654, 2004.

·       A. Likas and N. Galatsanos,  "A Variational Approach for Bayesian Blind Image Deconvolution", , IEEE Trans. on Signal Processing, Special Issue on Machine Learning Methods in Signal Processing , vol. 52, no. 8, pp. 2222-2233, August 2004.

·       Y. Goletsis, C. Papaloukas, D. Fotiadis, A. Likas, L. Michalis, "Automated Ischemic Beat Classification Using Genetic Algorithms and Multicriteria Decision Analysis", IEEE Trans. on Biomedical Engineering, vol. 51, no. 10, pp. 1717-1725, October, 2004.

·       K. Blekas, D. Fotiadis and A. Likas, "Motif-Based Protein Sequence Classification Using Neural Networks", Journal of Computational Biology, vol. 12, no. 1, pp. 64-82, 2005.

·       I. Tsoulos, I. Lagaris and A. Likas, "Exploiting Parallelism for Function Approximation Using Modular Neural Networks", Neural, Parallel and Scientific Computations, vol. 13, pp. 161-178, 2005.

·       K. Blekas, A. Likas, N. Galatsanos and I. Lagaris, "A Spatially-Constrained Mixture Model for Image Segmentation", IEEE Trans. on Neural Networks, vol. 16, no.2, 2005.

·       A. Papadopoulos, D. Fotiadis and A. Likas, "Characterization of Clustered Microcalcifications in Digitized Mammograms Using Neural Networks and Support Vector Machines", Artificial Intelligence in Medicine,vol. 34, pp. 141-150, 2005.

·       K. Blekas, N. Galatsanos, A. Likas and I. Lagaris, "Mixture Model Analysis for DNA Microarray Images", IEEE Trans. on Medical Imaging, vol 24, no. 7, pp. 901-909, 2005.

·       V. Protopappas, D. Baga, D. Fotiadis, A. Likas, C. Papachristos and K. Malizos, "An Ultrasound Wearable System for the Monitoring and Acceleration of Fracture Healing in Long Bones", IEEE Trans. on Biomedical Engineering,vol. 52, no. 9, pp. 1597-1608, 2005.

·       A. Anagnostakis, M. Tzima, G. Sakellaris, D. Fotiadis and A. Likas, "Semantics-Based Information Modeling for the Health-Care Administration Sector: The Citation Platform", IEEE Trans. on Information Technology in Biomedicine, vol. 9, no. 2, pp. 239-247, 2005.

·       C. Constantinopoulos, M. Titsias and A. Likas, "Bayesian Feature and Model Selection for Gaussian Mixture Models", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 28, no. 6, pp. 1013-1018, June 2006.

·       C. Constantinopoulos and A. Likas, "An Incremental Training Method for the Probabilistic RBF Network", IEEE Trans. on Neural Networks, vol. 17, no.4, pp. 966-974, July 2006.

·       G. Chantas, N. Galatsanos and A. Likas, "Bayesian Image Restoration Using a New Nonstationary Edge-Preserving Image Prior", IEEE Trans. on Image Processing, vol. 15, no. 10, pp. 2987-2997, October 2006.

·       C. Katsis, Y. Goletsis, A. Likas, D. Fotiadis and I. Sarmas, "A Novel Method for Automated EMG Decomposition and MUAP Classification", Artificial intelligence in medicine, vol. 37, no. 1, pp. 55-64, 2006.

·       C. Nikou, N. Galatsanos and A. Likas, "A Class-Adaptive Spatially Variant Mixture Model for Image Segmentation", IEEE Trans. on Image Processing, vol. 16, no. 4, pp. 1121-1130, April 2007.

·       C. Constantinopoulos and A. Likas, "Unsupervised Learning of Gaussian Mixtures Based on Variational Component Splitting", IEEE Trans. on Neural Networks, vol. 18, no. 3, pp. 745-755, 2007.

·       A. Lukic, M. Wernick, D. Tzikas, X. Chen, A. Likas, N. Galatsanos, Y. Yang, F. Zhao and S. Strother, "Bayesian kernel methods for analysis of functional neuroimages", IEEE Trans. on Medical Imaging, vol. 26, no. 12, pp. 1613-1622, 2007.

·       D. Tzikas, A. Likas and N. Galatsanos, "Large scale multikernel relevance vector machine for object detection", International Journal on Artificial Intelligence Tools, vol. 16, no. 6, pp. 967-979, 2007.

·       A. Tzika, L. Astrakas, H. Cao, D. Mintzopoulos, O. Andronesi, M. Mindrinos, J. Zhang, L. Rahme, K. Blekas, A. Likas, N. Galatsanos, R. Carroll and P. Black, "Combination of High-resolution Magic Angle Spinning Proton Magnetic Resonance Spectroscopy and Microscale Genomics to Type Brain Tumor Biopsies", Int. Journal of Molecular Medicine, vol. 20, no. 2, pp. 199-208, 2007.

·       C. Constantinopoulos and A. Likas, "Semi-supervised and Active Learning with the Probabilistic RBF Classifier", Neurocomputing, vol. 71, no. 13-15, pp. 2489-2498, 2008.

·       G. Chantas N. Galatsanos, A. Likas and M. Saunders, "Variational Bayesian Image Restoration Based on a Product of t-Distributions Image Prior", IEEE Transactions on Image Processing, vol. 17, no. 10, pp. 1795-1805, 2008.

·       D. Tzikas, A. Likas and N. Galatsanos, "The Variational approximation for Bayesian inference", IEEE Signal Processing Magazine, vol. 25, no. 6, pp. 131-146, 2008.

·       V. Chassanis, A. Likas and N. Galatsanos, "Simultaneous Detection of Abrupt Cuts and Dissolves in Videos Using Support Vector Machines", Pattern Recognition Letters, vol. 30, no. 1, pp. 55-65, 2009.

·       V. Chassanis, A. Likas and N. Galatsanos, "Scene Detection in Videos Using Shot Clustering and Sequence Alignment", IEEE Trans. on Multimedia, vol. 11, no. 1, pp. 89-100, 2009.

·       A. Marakakis, N. Galatsanos, A. Likas and A. Stafylopatis, "Probabilistic Relevance Feddback Approach for Content-based Image Retrieval Based on Gaussian Mixture Models", IET Image Processing, vol. 3, no. 1, pp. 10-25, 2009.

·       D. Tzikas, A. Likas and N. Galatsanos, "Variational Bayesian sparse kernel-based blind image deconvolution with student's-t priors", IEEE Trans. on Image Processing, vol. 18, no. 4, 2009, pp. 753-764, 2009.

·       D. Gerogiannis, C. Nikou and A. Likas, "The mixtures of Student’s t-distributions as a robust framework for rigid registration", Image and Vision Computing, vol. 27, no. 9, pp. 1285-1294, 2009.

·       D. Tzikas, A. Likas and N. Galatsanos, "Sparse Bayesian Modeling with Adaptive Kernel Learning", IEEE Trans. Neural Networks, vol. 20, no. 6, pp. 926-937, 2009.

·       G. Tzortzis and A. Likas, "The Global Kernel k-Means Clustering Algorithm", IEEE Trans on Neural Networks, vol. 20, no. 7, pp. 1181-1194, 2009.

·       C. Nikou, A. Likas and N. Galatsanos, "A Bayesian framework for image segmentation with spatially varying mixtures", IEEE Transactions on Image Processing, vol. 19, no. 9, pp. 2278-2289, 2010.

·       G. Tzortzis and A. Likas, "Multiple View Clustering Using a Weighted Combination of Exemplar-based Mixture Models", IEEE Trans on Neural Networks, vol. 21, no. 12, pp. 1925-1938, 2010.

·       P. Karvelis, A. Likas and D. Fotiadis, "Identifying touching and overlapping chromosomes using the watershed transform and gradient paths", Pattern Recognition Letters, vol. 31, pp. 2474–2488, 2010.

·       A. Marakakis, G. Siolas, N. Galatsanos, A. Likas and A. Stafylopatis, "A Relevance Feedback Approach for Image Retrieval Combining Support Vector Machines and Adapted Gaussian Mixture Models", IET Image Processing, vol. 5, no. 6, pp. 531-540, 2011.

·       V. Karavasilis, C. Nikou and A. Likas, "Visual tracking using the earth mover’s distance between Gaussian mixtures and Kalman filtering", Image and Vision Computing, vol. 29, no. 5, pp. 295-305, 2011.

·       A. Kalogeratos and A. Likas, "Document Clustering using Synthetic Cluster Prototypes", Data and Knowledge Engineering, vol. 70, no. 3, pp. 284-306, 2011.

·       L. Astrakas, K. Blekas, C. Constantinou, O.C. Andronesi, M. Mindrinos, A. Likas, L. Rahme, P.M. Black, K. Marcus and A. Tzika., "Combining magnetic resonance spectroscopy and molecular genomics offers better accuracy in brain tumor typing and prediction of survival than either methodology alone", Int. Jïurnal of Oncology, vol. 38, no. 4, pp. 1113-1127, 2011.

·       A. Kalogeratos and A. Likas, "Text Document Clustering using Global Term Context Vectors", Knowledge and Information Systems, vol. 31, pp. 455-474, 2012.

·       D. Gerogiannis, C. Nikou and A. Likas, "Registering sets of points using Bayesian regression", Neurocomputing, vol. 89, pp. 122-133, 2012.

·       P. Karvelis and A. Likas, "Fully Unsupervised M-FISH Chromosome Image Characterization", IEEE Journal of Biomedical and Health Informatics, vol. 17, no 6, pp. 1068-1078, 2014.

·       K. Blekas and A. Likas, "Sparse regression mixture modeling with the multi-kernel relevance vector machine", Knowledge and Information Systems, vol. 39, pp. 241-264, 2014.

·       G. Tzortzis and A. Likas, "The MinMax k-Means clustering algorithm", Pattern Recognition, vol. 47, pp. 2505–2516, 2014.

·       D. Gerogiannis, C. Nikou and A. Likas, "Modeling sets of unordered points using highly eccentric ellipses", EURASIP Journal on Advances in Signal Processing, vol. 11, 2014.

·       D. Gerogiannis, C. Nikou and A. Likas, "Elimination of Outliers from 2-D Point Sets Using the Helmholtz Principle", IEEE Signal Processing Letters, vol. 22, no. 10, pp. 1638-1642, 2015.

·       M. Sakka, G. Tzortzis, M. Mantzaris, N. Bekas, T. Kellici, A. Likas, D. Galaris, I. Gerothanassis, A. Tzakos, "PRESS: Protein S-sulfenylation Server", Bioinformatics, vol. 32, no. 17, pp. 2710-2712, 2016.

·       A. Ioannidis A., Chasanis V. and A. Likas, "Weighted Multi-View Key-frame Extraction", Pattern Recognition Letters, vol. 72, 1 pp. 52-61, 2016.

·       V. Karavasilis, C. Nikou and A. Likas. "Real time visual tracking using a spatially weighted von Mises mixture model", Pattern Recognition Letters, vol. 90, pp. 50-57, 2017.

·       P. Spyridonos a, G. Gaitanis, A. Likas and I. Bassukas, "Automatic discrimination of actinic keratoses from clinical photographs", Computers in Biology and Medicine, vol. 88, pp. 50-59, 2017.

·       A. Ioannidis A., Chasanis V. and A. Likas, "Camera Motion Detection Through Frame Splitting and Combination of Region-Based Motion Signals", International Journal of Pattern Recognition and Artificial Intelligence, vol. 32, no. 9, 2018.

 

Conference Publications

·       E. Gelenbe, A. Stafylopatis and A. Likas, "Associative Memory Operation of the Random Network Model", Proc. International Conference on Artificial Neural Networks (ICANN 91) , Vol. 1, pp. 307-312, Espoo, Finland, June 1991, (North-Holland, 1991).

·       A. Likas and A. Stafylopatis, "An Investigation of the Analogy between the Random Network and the Hopfield Network", Proc. 6th International Symposium on Computer and Information Sciences , pp. 849-857, Antalya, Turkey, Nov. 1991.

·       D. Kontoravdis, A. Likas and A. Stafylopatis, "Collision-Free Movement of an Autonomous Vehicle Using Reinforcement Learning", Proc. European Conference on Artificial Intelligence (ECAI 92) , pp. 666-670, Vienna, August 1992.

·       D. Kontoravdis, A. Likas and A. Stafylopatis, "A Reinforcement Learning Algorithm for Networks of Units with Two Stochastic Levels", Proc. International Conference on Artificial Neural Networks (ICANN 92) , pp. 143-146, Brighton, UK, Sep. 1992.

·       D. Kontoravdis, A. Likas and A. Stafylopatis, "Embedding Knowledge into Stochastic Learning Automata for Fast Solution of Binary Constraint Satisfaction Problems", Proc. European Symposium on Artificial Neural Networks (ESANN'93) , pp. 21-26, Brussels, April 1993.

·       A. Likas and A. Stafylopatis, "A Neural Network Technique for Associative Retrieval of Symbolic Pictures", Proc. IEEE Int. Conf. on Neural Network Applications to Signal Processing (NNASP'93) , pp. 204-209, Singapore, August 1993.

·       D. Kontoravdis, A. Likas and A. Stafylopatis, "Efficient Reinforcement Learning Stategies for the Pole Balancing Problem", Proc. International Conference on Artificial Neural Networks (ICANN 94) , Vol. 1, pp. 659-662, Sorento, Italy, May 1994.

·       D. Kontoravdis, A. Likas, K. Blekas and A. Stafylopatis, "A Fuzzy Neural Network Approach to Autonomous Vehicle Navigation", Proc. European Robotics and Intelligent Systems Conference (EURISCON'94) , pp. 243-252, Malaga, Spain, August 1994.

·       A. Likas, K. Blekas and A. Stafylopatis, "Application of Fuzzy Min-Max Neural Network Classifier to Problems with Continuous and Discrete Attributes", Proc. IEEE Int. Workshop on Neural Networks for Signal Processing (NNSP'94) , pp. 163-170, Ermioni, Greece, September 1994.

·       A. Likas, K. Blekas and A. Stafylopatis, "Parallel Recombinative Reinforcement Learning", Proc. 8th European Conference on Machine Learning (ECML-95) , Heraklion, Greece, April 1995, (Lecture Notes in Artificial Intelligence, Vol. 912, pp. 311-314, Springer Verlag, 1995).

·       A. Bouju, J.F. Boyce, C. Dimitropoulos, G. vom Scheidt, J. Taylor, A. Likas, G. Papageorgiou and A. Stafylopatis, "Intelligent Search for the Radio Links Frequency Assignment Problem", Proc. Int. Conference on Digital Signal Processing (DSP95) , pp. 408-414, Limassol, Cyprus, June 1995.

·       K. Blekas, A. Likas and A. Stafylopatis, "A Fuzzy Neural Network Approach Based on Dirichlet Tesselations for Nearest Neighbor Classification of Patterns", Proc. IEEE Int. Workshop on Neural Networks for Signal Processing (NNSP'95) , pp. 153-161, Boston, MA, Aug.-Sep. 1995.

·       I. Lagaris, A. Likas, D. Fotiadis and C. Massalas, "A Hardware Implementable Non-linear Method for the Solution of Ordinary, Partial and Integrodifferential Equations", Workshop on Applied Mathematics in Science and Modern Technology, Metsovo, Greece, July 1997.

·       K. Blekas, A. Likas and A. Stafylopatis, "A Fuzzy Neural Network Approach to Classification Based on Proximity Characteristics of Patterns", Proc. 9th IEEE Int. Conference on Tools with Artificial Intelligence (ICTAI'97) , Newport Beach, CA, November, 1997.

·       A. Likas, "Mutlivalued Parallel Recombinative Reinforcement Learning", Proc. HERCMA'98 Conference, vol. 1, pp. 378-385, Athens, October 1998.

·       I.E. Lagaris, A. Likas and D.G. Papageorgiou, "Neural Network Techniques for Solving Differential Equations", Proc. of CSCC'98, Athens, Greece, 1998.

·       I.E. Lagaris, A. Likas and D.G. Papageorgiou, "Neural Network Methods for Boundary Value Problems Defined in Arbitrarily Shaped Domains", Proc. of CSCC'99, Athens, Greece, 1999.

·       C. Papaloukas, D.I. Fotiadis, A. Likas, A.P. Liavas and L.K. Michalis, "A Robust Knowledge Based Technique for Ischemia Detection in Noisy ECGs", KES'2000, 4th International Conference on Knowledge – Based Intelligent Engineering Systems and Allied Technologies, vol. 2, pp. 768-771, Sussex, U.K, September 2000.

·       M. Titsias and A. Likas, "A Probabilistic RBF Network for Classification", Proc. of the Int. Joint Conference on Neural Networks (IJCNN'2000) , Como, Italy, 2000.

·       M. Titsias, D. Fotiadis and A. Likas, "Estimation of Concrete Characteristics Using Pattern Recognition Methods", 6th National Congress on Mechanics , Thessaloniki, Greece, 2001.

·       C. Papaloukas, D. Fotiadis, A. Likas and L. Michalis, "A Neural Network Methodology for Ischaemia Detection in Long Duration Elec trocardiograms", Neural Networks and Expert Systems in Medicine and Healthcare, NNESMED 2001 , Milos, Greece, June 2001.

·       A. Papadopoulos, D. Fotiadis and A. Likas, "A Hybrid Neural Network Method for Microcalcification Cluster Detection in Mammography", Neural Networks and Expert Systems in Medicine and Healthcare, NNESMED 2001 , Milos, Greece, June 2001.

·       D. Frossyniotis, S. Vrettos, A. Stafylopatis, D. Fotiadis, A. Likas and G. Potamias, "An Intelligent System for the Early Diagnos is of Coronary Artery Disease", Neural Networks and Expert Systems in Medicine and Healthcare, NNESMED 2001 Milos, Greece, June 2001.

·       K. Blekas, D. Fotiadis and A. Likas, "A Sequential Method for Discovering Probabilistic Motifs in Proteins", 4th International Workshop on Biosignal Interpretation , June 2002, Villa Olmo, Como, Italy.

·       K. Valasoulis, D. Fotiadis, I. Lagaris and A. Likas, "Solving Differential Equations with Neural Networks: Implementation on a DSP Platform", 14th International Conference on Digital Signal Processing , Santorini, Greece, July 2002.

·       C. Constantinopoulos, M. Titsias and A. Likas, "A Bayesian Regularization Method for the Probabilistic RBF Network", Proc. 2nd Hellenic Conference on AI, SETN 2002 , pp. 337-345, Springer, 2002.

·       I. Tsoulos,  I. Lagaris and A. Likas, "Piecewise Neural Networks for Function Approximation Cast in a Form Suitable for Parallel Implementation", Proc. 2nd Hellenic Conference on AI, SETN 2002 , pp. 314-324, Springer, 2002.

·       K. Blekas, D. Fotiadis and A. Likas, "Protein Sequence Classification using Probabilistic Motifs and Neural Networks ", Proc. Intern. Conference on Artificial Neural Networks (ICANN/ICONIP 2003) , Istanbul, Turkey, Lecture Notes in Computer Science, vol. 2714, Springer -Verlag, pp. 702-709, 2003.

·       A. Likas and N. Galatsanos, "A Variational Method for Bayesian Blind Image Deconvolution", Proceedings of the IEEE International Conference on Image Processing (ICIP'03), Barcelona, Spain, September 2003.

·       K. Blekas and A. Likas, "Incremental Mixture Learning for Clustering Discrete Data", Proc. 3rd Hellenic Conference on AI, SETN 2004 , pp. 210-219, Springer, 2004.

·       C. Constantinopoulos and A. Likas, "Efficient Training Algorithms for the Probabilistic RBF Network", Proc. 3rd Hellenic Conference on AI, SETN 2004 , pp. 183-190, Springer, 2004.

·       K. Valasoulis and A. Likas, "Probabilistic Shape-Based Image Indexing and Retrieval", Proceedings of the IEEE International Conference on Pattern Recognition (ICPR'04) , Cambridge, UK, August 2004.

·       G. Chantas, N. Galatsanos and A. Likas, "Non Stationary Bayesian Image Restoration", Proceedings of the IEEE International Conference on Pattern Recognition (ICPR'04), Cambridge, UK, August 2004.

·       D. Tzikas, A. Likas, N. Galatsanos, A. Lukic and M. Wernick, "Bayesian Regression of Functional Neuroimages", Proc. EUSIPCO-2004 , Vienna, August 2004.

·       K. Blekas, A. Likas, N. Galatsanos and I. Lagaris, "Mixture Model Based Image Segmentation with Spatial Constraints", Proc. EUSIPCO-2004 , Vienna, August 2004.

·       G. Sfikas, C. Constantinopoulos, A. Likas and N. Galatsanos, "An Analytic Distance Metric for Gaussian Mixture Models with Application in Image Retrieval", Proc. 15th Int. Conf. on Artificial Neural Networks (ICANN’05), Part II, pp. 835-840, Springer, 2005.

·       G. Chantas, N. Galatsanos and A. Likas, "Maximum a Posteriori Image Restoration Based on a New Directional Continuous Edge Image Prior", Proc. IEEE Int. Conf. on Image Processing (ICIP'05), vol. I, pp. 941-944, September 2005.

·       D. Tzikas, A. Likas, and N. Galatsanos, "Large scale multikernel RVM for object detection", Proc. Hellenic Conference on Artificial Intelligence (SETN'06), pp. 389-399, Heraklion, Crete, Greece, Springer, 2006.

·       A. Kalogeratos and A. Likas, "A Significance-Based Graph Model for Clustering Web Documents", Proc. Hellenic Conference on Artificial Intelligence (SETN'06), pp. 516-519, Heraklion, Crete, Greece, Springer, 2006.

·       C. Constantinopoulos and A. Likas,"Active Learning with the Probabilistic RBF Classifier", Proc. 16th Int. Conf. on Artificial Neural Networks (ICANN’06), vol. 1, pp 257-366, Athens, Greece, Springer, 2006.

·       A. Marakakis, N. Galatsanos, A. Likas and A. Stafylopatis, "A Relevance Feedback Approach for Content Based Image Retrieval Using Gaussian Mixture Models", Proc. 16th Int. Conf. on Artificial Neural Networks (ICANN’06), vol. 2, pp. 84-93, Athens, Greece, Springer, 2006.

·       C. Constantinopoulos and A. Likas, "Active Bayesian Mixture Learning for Image Modeling and Segmentation Using Low Level Features", Proc. Machine Learning for Signal Processing (MLSP’06), Ireland, Sept. 2006.

·       D. Tzikas, A. Likas, and N. Galatsanos, "Variational Bayesian blind image deconvolution based on a sparse kernel model for the point spread function", Proc. European Signal Processing Conference (EUSIPCO'06), Florence, Italy, September 2006.

·       D. Tzikas, A. Likas, and N. Galatsanos. Robust variational Bayesian kernel based blind image deconvolution, Proc. Int. Conf. on Computer Vision Theory and Applications (VISAPP’07), pp. 143-150, Barcelona, Spain, March 2007.

·       V. Chasanis, A. Likas and N. Galatsanos, "Scene Detection in Videos Using Shot Clustering and Symbolic Sequence Segmentation", Proc. IEEE Int. Workshop on Multimedia Signal Processing (MMSP’07), pp. 187-190, Chania, Greece, 2007.

·       D. Gerogiannis, C. Nikou and A. Likas, A, "Rigid image registration based on pixel grouping", Proc. 14th Int. Conf. on Image Analysis and Processing (ICIAP’07), pp. 595-602, Modena, Italy, 2007.

·       D. Gerogiannis, C. Nikou and A. Likas, "Robust image registration using mixtures of t-distributions", Proc. 8th IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'07), in conjunction with ICCV'07, Rio, Brazil, 2007.

·       D. Tzikas, M. Kukar, and A. Likas, "Transductive reliability estimation for kernel based classifiers", Proc. Int. Symposium on Intelligent Data Analysis (IDA'07), pp. 37-47, Ljubljana, Slovenia, Springer 2007.

·       G. Chantas, N. Galatsanos, and A. Likas, "Bayesian Image Restoration Based on Variational Inference and a Product of Student-t Priors", Proc. IEEE Int. Conf. on Machine Learning for Signal Processing (MLSP'07), Thessaloniki, Greece, August 2007.

·       C. Constantinopoulos and A. Likas, "Image Modeling and Segmentation using Incremental Bayesian Mixture Models", Proc. 12th Int. Conf. on Computer Analysis of Images and Patterns (CAIP'07), pp. 596-603, Springer, 2007.

·       D. Tzikas, A. Likas, and N. Galatsanos. Bayesian bid based on a kernel model for the point spread function, Proc. IEEE Int. Conf. on Image Processing (ICIP'07), San Antonio, USA, September 2007.

·       G. Tzortzis and A. Likas, "Deep Belief Networks for Spam Filtering", Proc. Int. Conf. on Tools with AI (ICTAI’07), vol. 2, pp. 306-309, Patras, Greece, 2007.

·       G. Tzortzis and A. Likas, "The Global Kernel K-means Clustering Algorithm", Proc. Int. Joint Conf. on Neural Networks (IJCNN’08), pp. 1977-1984, Hong, Kong, June 2008.

·       A. Alivanoglou and A. Likas, "Probabilistic Models Based on the Pi-Sigmoid Distribution", Proc. 3rd IAPR Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR’08), pp. 36-43, Paris, Springer 2008.

·       V. Chasanis, A. Likas and N. Galatsanos, "A Support Vector Machine Approach for Video Shot Detection", Proc. Int. Symposium on Intelligent Interactive Multimedia Systems and Services (IIMSS’08), Piraeus, Greece, pp. 45-54, Springer 2008.

·       V. Chasanis, A. Likas and N. Galatsanos, "Video rushes summarization using spectral clustering and sequence alignment", Proceedings of the 2nd ACM Workshop on Video Summarization (TVS’08), Vancouver, Canada, October 2008.

·       V. Chasanis, A. Likas and N. Galatsanos, "Efficient Video Shot Summarization Using an Enhanced Spectral Clustering Approach", Proc. Int. Conf. on Artificial Neural Networks (ICANN’08), vol. 1 pp. 847-856, Prague, Springer, 2008.

·       K. Blekas, N. Galatsanos and A. Likas, "A Sparse Regression Mixture Model for Clustering Time-Series", Proc. Hellenic Conference on Artificial Intelligence (SETN'08), pp. 64-72, Syros, Greece, Springer 2008.

·       D. Tzikas, A. Likas, and N. Galatsanos, "Incremental relevance vector machine with kernel learning", Proc. Hellenic Conference on Artificial Intelligence (SETN'08), pp. 301-312, Syros, Greece, Springer 2008.

·       A. Marakakis, N. Galatsanos, A. Likas and A. Stafylopatis, "Application of Relevance Feedback in Content Based Image Retrieval Using Gaussian Mixture Models", Proc. Int. Conf. on Tools with AI (ICTAI’08), vol. 1, pp. 141-148, Dayton, Ohio, 2008.

·       V. Chasanis, A. Likas and N. Galatsanos, "Movie Segmentation into Scenes and Chapters Using Locally Weighted Bag of Visual Words", Proc. ACM International Conference on Image and Video Retrieval (CIVR’09), Santorini, Greece, July 2009.

·       D. Tzikas, A. Likas, and N. Galatsanos, "Local Feature Selection for the Relevance Vector Machine using Adaptive Kernel Learning", Proc. Int. Conf. on Artificial Neural Networks (ICANN’09), Limassol, Cyprus, Springer, 2009.

·       A. Marakakis, N. Galatsanos, A. Likas and A. Stafylopatis, "Relevance Feedback for Content-Based Image Retrieval Using Support Vector Machines and Feature Selection", Proc. Int. Conf. on Artificial Neural Networks (ICANN’09), Limassol, Cyprus, Springer, 2009.

·       G. Tzortzis and A. Likas, "Convex Mixture Models for Multi-view Clustering", Proc. Int. Conf. on Artificial Neural Networks (ICANN’09), Limassol, Cyprus, Springer, 2009.

·       A. Marakakis, N. Galatsanos, A. Likas and A. Stafylopatis, "Combining Gaussian Mixture Models and Support Vector Machines for Relevance Feedback in Content Based Image Retrieval", Proc. Artificial Inteligence. Applications and Innovations (AIIA’09), Springer, 2009.

·       V. Chasanis and A. Likas, "Event Detection and Classification in Video Surveillance Sequences", Proc. Hellenic Conference on Artificial Intelligence (SETN'10), Athens, Greece, Springer 2010.

·       V. Karavasilis, C. Nikou and A. Likas, "Visual tracking by adaptive Kalman filtering and mean shift", Proc. Hellenic Conference on Artificial Intelligence (SETN'10), pp. 153-162, Athens, Greece, Springer 2010.

·       D. Tzikas and A. Likas, "An Incremental Bayesian Approach for Training Multilayer Perceptrons", Proc. Int. Conf. on Artificial Neural Networks (ICANN’10), Thessaloniki, Greece, Springer 2010.

·       M. Robnik-Sikonja, A. Likas, C. Constantinopoulos, I. Kononenko and E. Strumbelj, "Efficiently Explaining Decisions of Probabilistic RBF Classification Networks", Proc. ICANNGA 2011, Part. 1, pp. 169-179, Ljubljana, Slovenia, Springer 2011.

·       D. Gerogiannis, C. Nikou and A. Likas, "A split-and-merge framework for 2D shape summarization”, 7th Int. Symp. on Image and Signal Processing and Analysis (ISPA’11), pp. 206-2011, Dubrovnik, Croatia, September 2011.

·       G. Tzortzis and A. Likas, "Greedy Unsupervised Multiple Kernel Learning", Proc. Hellenic Conference on Artificial Intelligence (SETN'12), pp. 73-80, Lamia, Greece, Springer 2012.

·      V. Karavasilis, C. Nikou and A. Likas, "Gaussian Mixture-based Mean Shift for Tracking under Abrupt Illumination Changes", Proc. 8th Int. Conf. on Information Hiding and Multimedia Signal Processing, Piraeus, Greece, 2012.

·      G. Piperagkas, G. Georgoulas, K. Parsopoulos, C. Stylios and A. Likas, "Integrating Particle Swarm Optimization with Reinforcement Learning in Noisy Problems", Proc. Genetic and Evolutionary Computation Conference (GECCO’12), Philadelphia, USA, 2012.

·      D. Gerogiannis, C. Nikou and A. Likas, "Fast and efficient vanishing point detection in indoor images ", Proc. Int. Conf. Pat. Rec. (ICPR’12), Tsukuba, Japan, 2012.

·      V. Karavasilis, C. Nikou and A. Likas, "Visual Tracking by Weighted Likelihood Maximization", Proc. Int. Conf. on AI Tools (ICTAI’12), Piraeus, Greece, 2012.

·      A. Kalogeratos and A. Likas, "Dip-means: an incremental clustering method for estimating the number of clusters", Proc. Neural Information Processing Systems (NIPS’12), Lake Tahoe, Nevada, USA, 2012.

·      K. Blekas and A. Likas, "The mixture of multi-kernel relevance vector machines model", Proc IEEE Int. Conf. Data Mining (ICDM’12), Brussels, 2012.

·      G. Tzortzis and A. Likas, "Kernel-based Weighted Multi-view Clustering", Proc IEEE Int. Conf. Data Mining (ICDM’12), Brussels, 2012.

·      G. Tzortzis and A. Likas, "Ratio-Based Multiple Kernel Clustering", Proc Eur. Conf. Machine Learning (ECML’14), Nancy, France, 2014.

·      A. Ioannidis, V. Chasanis and A. Likas, "Key-frame Extraction using Weighted Multi-View Convex Mixture Models and Spectral Clustering", Proc. Int. Conf. Pattern Recognition (ICPR'14), Stockholm, 2014 (Best Scientific Paper Award).

·      D. Gerogiannis, C. Nikou and A. Likas, "Global Sampling of Image Edges", Proc. Int. Conf. Image Processing (ICIP’14), Paris, 2014.

·      A. Ioannidis A., V. Chasanis V and A. Likas, "An Agglomerative Approach for Shot Summarization Based on Content Homogeneity", Proc. 7th International Conference on Machine Vision (ICMV 2014), Milan, SPIE, 2014.

·      A. Ioannidis A., V. Chasanis V and A. Likas, "Efficient Key-frame Extraction Based on Unimodality of Frame Sequences", Proc. 12th IEEE International Conference on Signal Processing (ICSP 2014), 2014.

·      A. Kalogeratos, P. Zagorisios and A. Likas, "Improving Text Stream Clustering using Term Burstiness and Co-burstiness", Proc. Hellenic Conference on Artificial Intelligence (SETN'16), Thessaloniki, Greece, ACM Press, 2016.

·      S. Adam, A. Likas and M. Vrahatis, "Interval Analysis Based Neural Network Inversion: A Means for Evaluating Generalization", Proc. Int. Conf. on Engineering Applications of Neural Networks (EANN 2017), Athens, Greece, Springer, 2017.

·      T. Chamalis and A. Likas, "Region Merging for Image Segmentation Based on Unimodality Tests", Proc. IEEE Int. Conf. on Control, Automation and Robotics (ICCAR 2017), Nagoya, Japan, 2017.

·      E. Papapetrou and A. Likas, "Cluster-based Replication: a Forwarding Strategy for Mobile Opportunistic Networks", Proc. IEEE Int. Symp. on a World of Wireless Mobile and Multimedia Networks (WoWMoM’18), Chania, Greece, 2018.

·      T. Chamalis and A. Likas, "The Projected Dip-means Clustering Algorithm", Proc. Hellenic Conference on Artificial Intelligence (SETN'18), Patras, Greece, ACM Press, 2018.