Publications
2012
·
N. Tziortziotis and
K. Blekas. An online kernel-based
clustering approach for value function approximation. SETN 2012 (to
appear)
2011
·
N. Tziortziotis and
K. Blekas. A Bayesian Reinforcement
Learning framework Using Relevant Vector Machines. AAAI 2011
·
N. Tziortziotis and
K. Blekas. Value Function
Approximation for Reinforcement Learning through Sparse Bayesian Modeling.
EWRL 2011.
·
L. Astrakas, K. Blekas, C. Constantinou, et. al. Combining magnetic
resonance spectroscopy and molecular genomics offers better accuracy in brain
tumor typing and prediction of survival than either methodology alone. Int J Oncol. 38(4):1113-27, 2011.
2010
·
V.P. Oikonomou and K. Blekas. A Sparse
Spatial Linear Regression Model for fMRI Data
Analysis. SETN, 203-212, 2010.
2009
·
K. Blekas, K. Christodoulidou, I.E. Lagaris. Newtonian Spectral Clustering. ICANN, pp. 145-154. 2009.
2008
·
K. Blekas, N.P. Galatsanos and A. Likas. A Sparse Regression Mixture Model for Clustering Time-Series.
SETN, 64-72, 2008.
·
E. Voudigari and K.
Blekas. A marginal mixture model
for discovering motifs in sequences. Workshop on ‘Bioinformatics,
Genomics and Proteomics on Artificial Intelligence Approach”, ECAI 2008.
2007
·
D.L. Patiris, K. Blekas and K.G. Ioannides. TRIAC II. A MatLab code for
track measurements from SSNT detectors. Computer Physics Communications
, 177(3), pp.
329-338, 2007.
·
P. Margariti, K. Blekas, F. Katzioti, A. Zikou, M. Tzoufi and M. Argyropoulou. Magnetization transfer ratio and
volumetric analysis of the brain in macrocephalic
patients with neurofibromatosis type 1 . Journal of European Radiology , vol.
17 (2), pp.433-438, 2007.
·
M. Argyropoulou, A.
Zikou, I. Tzovara, A. Nikas, K. Blekas, P. Margariti, N. Galatsanos, and I. Asproudis. Non-arteritic
anterior ischemic optic neuropathy: evaluation of the brain and optic pathway
by conventional MRI and magnetization transfer imaging .
Journal of European Radiology , 17(7), pp. 1669-1674, 2007.
·
K. Blekas and I. E.
Lagaris. Split-Merge Incremental Learning (SMILE) of Mixture Models
. Inter. Conference on Artificial Neural
Networks (ICANN), Porto 2007, Lecture Notes on Artificial Neural Networks,
vol.4669, pp.291-300, 2007.
2006
·
D.L. Patiris, K. Blekas and K.G. Ioannides. TRIAC: A code for track measurements using image analysis tools . Nuclear Instruments and Methods in
Physics Research, Section B ,
Vol. 244(2), pp. 392-396, 2006.
·
A. Kakoliris and K.
Blekas. Incremental training of Markov mixture models . ECML 2006 International Workshop on
Knowledge Discovery from Data Streams (IWKDDS) , pp. 47-56, Berlin, Sep.
2006.
·
C. Nikou, N, Galatsanos, A. Likas and K. Blekas. Image segmentation with a
class-adaptive spatially constrained mixture model. EUSIPCO
2006.
2005
·
K. Blekas, A. Likas, N. Galatsanos and I. E. Lagaris. A Spatially-Constrained Mixture Model for Image Segmentation
. IEEE
Transactions on Neural Networks ,
Vol. 16(2), pp. 494-498, 2005.
·
K. Blekas, N. Galatsanos, A. Likas and I. E. Lagaris. Mixture Model Analysis of DNA
Microarray Images . IEEE Transactions
on Medical Imaging, Vol. 24(7), pp. 901-909, 2005.
2004
·
K. Blekas, D.
Fotiadis and A. Likas. A Sequential Method for Discovering Probabilistic Motifs in Proteins.
Methods of Information in Medicine , vol.
43(1), pp. 9-12, 2004.
·
K. Blekas and A. Likas. Incremental Mixture Learning for Clustering Discrete Data
. Proceedings
of the 3th Hellenic Conference on Artificial Intelligence (SETN'04) Samos,
Greece, May 2004 ,
Lecture Notes in Artificial Intelligence, vol. 3025, pp. 210-219, 2004.
·
K. Blekas, A. Likas, N. P. Galatsanos and I. E.
Lagaris. Mixture model based image
segmentation with spatial constraints. Proceedings of the 12th European Signal
Processing Conference (EUSIPCO 2004) , Vienna, Sep. 2004.
2003
·
K. Blekas, D.
Fotiadis and A. Likas. Protein Sequence Classification using Probabilistic Motifs and Neural
Networks. Proc.
of the 13th International Conference on Artificial Neural Networks (ICANN 2003),
pp. 702-709, Istanbul, 2003.
Before 2003
·
K. Blekas, A. Stafylopatis, D. Kontoravdis, A. Likas and P. Karakitsos. Cytological Diagnosis Based on Fuzzy
Neural Networks. Journal of Intelligent Systems , vol.
8(1/2), pp. 55-79, 1998.
·
S. Pavlopoulos, E. Kyriacoy, D. Koutsouris, K. Blekas, A. Stafylopatis and P. Zoumpoulis. Fuzzy Neural Network Based
Characterization of Diffused Liver Diseases Using Image Texture Techniques on
Ultrasonic Images. . IEEE Engineering in Medicine and Biology
Magazine , vol 19(1), pp.
39-47, 2000.
·
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, Aug. 1994.
·
A. Likas, K. Blekas and A. Stafylopatis. Parallel Recombinative Reinforcement Learning. Proc.
Machine Learning: ECML-95, Heraclion, Crete,
Greece, Apr. 1995. (Lecture notes in Artificial Intelligence,
vol. 912, pp. 311-314, Springer-Verlag, 1995).
·
K. Blekas and A. Stafylopatis. Real-coded Genetic Optimization for Fuzzy
Clustering. European
Congress on Intelligence Techniques and Soft Computing, EUFIT-96 , pp.
461-465, Aachen, Germany, Sep. 1996.
·
K. Blekas, G. Papageorgiou and A. Stafylopatis.
Continuous Optimization Schemes for Fuzzy Classification. Proc. 13th Int. Conference on Digital Signal
Processing, (DSP'97), pp. 265-268, Santorini,
Greece, Jul. 1997.
·
E. Kyriakoy, S. Pavlopoulos, D. Koutsouris, K. Blekas, A. Stafylopatis and P. Zoumpoulis. Fuzzy Neural Network Based Characterization of
Diffused Liver Diseases Using Image Texture Techniques on Ultrasonic Images. VIII Mediterranean
Conference on Biological Engineering and Computing (MEDICON'98),
pp. 180-184, Lemesos, Cyprus, June 1998.
·
K. Blekas, D.
Fotiadis and A. Likas. A Sequential Method for Discovering Probabilistic Motifs in Proteins.
Proc. of the 4th International
Workshop on Biosignal Interpretation (BSI 2002),
pp. 11-14, Como, Italy, June 2002.