Konstantinos Blekas

发表

A Mixture Model Based Markov Random Field for Discovering Patterns in Sequences

Konstantinos Blekas, K. Blekas, 2006, SETN.

Mixture model based image segmentation with spatial constraints

Nikolas P. Galatsanos, Isaac E. Lagaris, Konstantinos Blekas, 2004, 2004 12th European Signal Processing Conference.

Motion Segmentation by Model-Based Clustering of Incomplete Trajectories

Konstantinos Blekas, Christophoros Nikou, Vasileios Karavasilis, 2011, ECML/PKDD.

Multiagent Reinforcement Learning Methods to Resolve Demand Capacity Balance Problems

George A. Vouros, Konstantinos Blekas, Georgios Chalkiadakis, 2018, SETN.

Autonomous vehicle navigation using evolutionary reinforcement learning

Andreas Stafylopatis, Konstantinos Blekas, K. Blekas, 1998, Eur. J. Oper. Res..

Motif-Based Protein Sequence Classification Using Neural Networks

Dimitrios I. Fotiadis, Konstantinos Blekas, Aristidis Likas, 2005, J. Comput. Biol..

A Bayesian Ensemble Regression Framework on the Angry Birds Game

Konstantinos Blekas, Georgios Papagiannis, Nikolaos Tziortziotis, 2016, IEEE Transactions on Computational Intelligence and AI in Games.

An Online Kernel-Based Clustering Approach for Value Function Approximation

Konstantinos Blekas, Nikolaos Tziortziotis, 2012, SETN.

A Regression Mixture Model with Spatial Constraints for Clustering Spatiotemporal Data

Nikolas P. Galatsanos, Nikolaos V. Tsekos, Konstantinos Blekas, 2008, Int. J. Artif. Intell. Tools.

Autonomous navigation of an over-actuated marine platform using reinforcement learning

Konstantinos Blekas, Kostas Vlachos, Nikolaos Tziortziotis, 2016, SETN.

Linear Bayesian Reinforcement Learning

Christos Dimitrakakis, Konstantinos Blekas, Nikolaos Tziortziotis, 2013, IJCAI.

Editorial

Dimitrios Kalles, Konstantinos Blekas, Aristidis Likas, 2015, Int. J. Artif. Intell. Tools.

A reinforcement learning approach based on the fuzzy min-max neural network

Konstantinos Blekas, Aristidis Likas, 2004, Neural Processing Letters.

Mixture model analysis of DNA microarray images

Nikolas P. Galatsanos, Isaac E. Lagaris, Konstantinos Blekas, 2005, IEEE Transactions on Medical Imaging.

Incremental Mixture Learning for Clustering Discrete Data

Konstantinos Blekas, Aristidis Likas, K. Blekas, 2004, SETN.

Reinforcement learning-based motion planning of a triangular floating platform under environmental disturbances

Konstantinos Blekas, Kostas Vlachos, Konstantinos Tziortziotis, 2016, 2016 24th Mediterranean Conference on Control and Automation (MED).

Revisiting Java Bytecode Compression for Embedded and Mobile Computing Environments

Apostolos V. Zarras, Konstantinos Blekas, George Manis, 2007, IEEE Transactions on Software Engineering.

Newtonian Spectral Clustering

Isaac E. Lagaris, Konstantinos Blekas, K. Christodoulidou, 2009, ICANN.

New Detectors for Watermarks with Unknown Power Based on Student-t Image Priors

Nikolas P. Galatsanos, Yongyi Yang, Konstantinos Blekas, 2007, 2007 IEEE 9th Workshop on Multimedia Signal Processing.

Play Ms. Pac-Man Using an Advanced Reinforcement Learning Agent

Konstantinos Blekas, Nikolaos Tziortziotis, Konstantinos Tziortziotis, 2014, SETN.

Artificial Intelligence: Methods and Applications

Konstantinos Blekas, Aristidis Likas, Dimitris Kalles, 2014, Lecture Notes in Computer Science.

Resting state fMRI analysis using a spatial regression mixture model

Vangelis P. Oikonomou, Konstantinos Blekas, Loukas Astrakas, 2013, 13th IEEE International Conference on BioInformatics and BioEngineering.

An unsupervised artifact correction approach for the analysis of DNA microarray images

Nikolas P. Galatsanos, Konstantinos Blekas, I. Georgiou, 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

Image segmentation with a class-adaptive spatially constrained mixture model

Nikolas P. Galatsanos, Konstantinos Blekas, Aristidis Likas, 2006, 2006 14th European Signal Processing Conference.

RL-based path planning for an over-actuated floating vehicle under disturbances

Konstantinos Blekas, Kostas Vlachos, 2018, Robotics Auton. Syst..

Split-Merge Incremental LEarning (SMILE) of Mixture Models

Isaac E. Lagaris, Konstantinos Blekas, K. Blekas, 2007, ICANN.

Detecting Pornographic Images by Localizing Skin ROIs

Ioannis Pitas, Konstantinos Blekas, Nikos Ntarmos, 2013, Int. J. Digit. Crime Forensics.

Value Function Approximation through Sparse Bayesian Modeling

Konstantinos Blekas, Nikolaos Tziortziotis, 2011, EWRL.

A Sparse Regression Mixture Model for Clustering Time-Series

Nikolas P. Galatsanos, Konstantinos Blekas, Aristidis Likas, 2008, SETN.

Brain tumor classification using a novel H1 HRMAS MRS method and robust algorithmic classifiers

Ovidiu C. Andronesi, Konstantinos Blekas, Loukas G. Astrakas, 2009 .

Cover tree Bayesian reinforcement learning pdf

Christos Dimitrakakis, Konstantinos Blekas, Nikolaos Tziortziotis, 2013, J. Mach. Learn. Res..

A Sparse and Spatially Constrained Generative Regression Model for fMRI Data Analysis

Vangelis P. Oikonomou, Konstantinos Blekas, Loukas Astrakas, 2012, IEEE Transactions on Biomedical Engineering.

Newtonian clustering: An approach based on molecular dynamics and global optimization

Isaac E. Lagaris, Konstantinos Blekas, K. Blekas, 2007, Pattern Recognit..

InFeRno - An Intelligent Framework for Recognizing Pornographic Web Pages

Konstantinos Blekas, Nikos Ntarmos, Sotiris Karavarsamis, 2011, ECML/PKDD.

A Model Based Reinforcement Learning Approach Using On-Line Clustering

Konstantinos Blekas, Nikolaos Tziortziotis, Nikolaos Tziortziotis, 2012, 2012 IEEE 24th International Conference on Tools with Artificial Intelligence.

The Mixture of Multi-kernel Relevance Vector Machines Model

Konstantinos Blekas, Aristidis Likas, K. Blekas, 2012, 2012 IEEE 12th International Conference on Data Mining.

A Bayesian Reinforcement Learning framework Using Relevant Vector Machines

Konstantinos Blekas, Nikolaos Tziortziotis, 2011, AAAI.

Curve Clustering with Spatial Constraints for Analysis of Spatiotemporal Data

Nikolas P. Galatsanos, Nikolaos V. Tsekos, Konstantinos Blekas, 2007, 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007).

Under Consideration for Publication in Knowledge and Information Systems Sparse Regression Mixture Modeling with the Multi-kernel Relevance Vector Machine

Konstantinos Blekas, Aristidis Likas, K. Blekas, 2022 .

A fuzzy neural network approach to classification based on proximity characteristics of patterns

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1997, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence.

An Adaptive Regression Mixture Model for fMRI Cluster Analysis

Vangelis P. Oikonomou, Konstantinos Blekas, K. Blekas, 2013, IEEE Transactions on Medical Imaging.

Parallel Recombinative Reinforcement Learning: A Genetic Approach

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1996 .

Artificial neural networks with an infinite number of nodes

Isaac E. Lagaris, Konstantinos Blekas, K. Blekas, 2017 .

A vector quantization schema for non-stationary signal distributions based on ML estimation of mixture densities

Andreas Stafylopatis, George K. Papakonstantinou, Nikos A. Vlassis, 1998, 9th European Signal Processing Conference (EUSIPCO 1998).

A Spectral Clustering Approach Based on Newton's Equations of Motion

Isaac E. Lagaris, Konstantinos Blekas, K. Blekas, 2013, Int. J. Intell. Syst..

Resource allocation in visual sensor networks using a reinforcement learning framework

Lisimachos P. Kondi, Konstantinos Blekas, Katerina Pandremmenou, 2013, 2013 18th International Conference on Digital Signal Processing (DSP).

Quality optimization of H.264/AVC video transmission over noisy environments using a sparse regression framework

S. Kumar, Lisimachos P. Kondi, Konstantinos Blekas, 2015, Electronic Imaging.

Greedy mixture learning for multiple motif discovery in biological sequences

Dimitrios I. Fotiadis, Konstantinos Blekas, Aristidis Likas, 2003, Bioinform..

A spatially constrained mixture model for image segmentation

Nikolas P. Galatsanos, Isaac E. Lagaris, Konstantinos Blekas, 2005, IEEE Transactions on Neural Networks.

A novel framework for motion segmentation and tracking by clustering incomplete trajectories

Konstantinos Blekas, Christophoros Nikou, Vasileios Karavasilis, 2012, Comput. Vis. Image Underst..

Parallel Recombinative Reinforcement Learning (Extended Abstract)

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1995, ECML.

AI in Greece: The Case of Research on Linked Geospa al Data

George A. Vouros, Vassilis P. Plagianakos, Konstantinos Blekas, 2018, AI Mag..

Curve Clustering with Spatial Constraints for Analysis of Spatiotemporal Data

Nikolaos V. Tsekos, Konstantinos Blekas, Christophoros Nikou, 2007 .

A Sparse Spatial Linear Regression Model for fMRI Data Analysis

Vangelis P. Oikonomou, Konstantinos Blekas, 2010, SETN.

Protein Sequence Classification Using Probabilistic Motifs and Neural Networks

Dimitrios I. Fotiadis, Konstantinos Blekas, Aristidis Likas, 2003, ICANN.

Hand Pose Estimation with Convolutional Networks using RGB-D Data

Evangelos Kazakos, Konstantinos Blekas, K. Blekas, 2017 .

Hierarchical multiagent reinforcement learning schemes for air traffic management

George A. Vouros, Konstantinos Blekas, Christos Spatharis, 2021, Neural Computing and Applications.

TRIAC: A code for track measurements using image analysis tools

Konstantinos Blekas, K. G. Ioannides, K. Blekas, 2006 .

A fuzzy neural network approach based on Dirichlet tesselations for nearest neighbor classification of patterns

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1995, Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing.

Application of the fuzzy min-max neural network classifier to problems with continuous and discrete attributes

Andreas Stafylopatis, Konstantinos Blekas, Aristidis Likas, 1994, Proceedings of IEEE Workshop on Neural Networks for Signal Processing.