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A. Editorships (books/special issues)
1. Magoulas
G.D., E-Infrastructures and Technologies for Lifelong Learning, IGI Global, forthcoming
2. Roussos
G., Musolesi M., Magoulas G., Human Behaviour in Ubiquitous Environments, special issue of Pervasive and Mobile Computing
Journal, forthcoming
3. Magoulas
G.D. AI Tools for HCI Modeling, special issue of the International Journal on Artificial Intelligence Tools, forthcoming
4.
Magoulas
G.D., and Dounias G., Computational
Intelligence in Medicine and Biology, special
issue of the journal Applied Intelligence: The International
Journal of Artificial Intelligence, Neural Networks, and Complex
Problem-Solving Technologies, vol. 27(3), December, 2007 pp.
189-192.
5.
Magoulas
G. D., and Ghinea G., Intelligence-based Adaptation for
Ubiquitous Multimedia Communications, special issue of the Journal of Network
and Computer Applications, vol. 30(3), August 2007, pp.
955-1083.
6.
Magoulas
G.D., Lepouras G, and Vassilakis C., Virtual Reality in the e-Society,
special Issue of the journal Virtual Reality,
vol. 11(2-3), June, 2007, pp. 71-184.
7.
Magoulas
G.D, and Chen Y., Human Factors in
Personalised Systems and Services, special
issue of the journal Interacting with
Computers, vol. 18(3), May 2006, pp 327-506.
8.
Magoulas
G.D, and Chen S., Advances in Web-based
Education: Personalized Learning Environments, Information Science
Publishing, 2006 (ISBN: 1-59140-691-9).
9.
Magoulas
G.D., and Dounias G., Intelligent
Technologies in Bioinformatics and Medicine, special issue of
the journal Computers in
Biology and Medicine, vol. 36(10), October 2006, pp.
1045-1184.
10. Magoulas G.D., Dounias G. Linkens
D.A., Intelligent Tools for Problem Solving
in Bioinformatics and Medicine, special issue of the International
Journal of Artificial Intelligence Tools, vol. 15(3), June
2006, pp. 331-432.
11. Chen S., and Magoulas G.D., Adaptable and
Adaptive Hypermedia Systems, IRM Press,
2005 (ISBN: 1-59140-567-X).
12. Dounias G., Magoulas G. and Linkens
D., Intelligent Technologies in Bioinformatics and Medicine (Workshop
Proceedings) Published by the Univ. of the Aegean and the European Network on
Intelligent Technologies (EUNITE) for Smart Adaptive Systems, 2004 (ISBN:
960-7475-28-3).
Home - Teaching - Research - Publications - Bio - Department
B. Journal papers
1.
Cocea
M., Magoulas G.D., Hybrid Model for Learner Modelling and Feedback
Prioritisation in Exploratory Learning, International Journal of Hybrid
Intelligent Systems, 6(4), 211-230, 2009.
2.
Dimakopoulos
D.N. and Magoulas G. D., Interface design and
evaluation of a personal information space for mobile learners,
International Journal of Mobile Learning and Organisation, vol.3(4), 440 –
463, 2009.
3.
Peng
C.-C. and Magoulas G.D., Advanced Adaptive Nonmonotone Conjugate Gradient Training
Algorithm for Recurrent Neural Networks, International Journal of Artificial
Intelligence Tools, vol. 17(5), 963-984, 2008.
4.
Anastasiadis
A.D., Magoulas G.D., Particle Swarms and
Nonextensive Statistics for Nonlinear Optimisation, The Open
Cybernetics and Systemics Journal, vol. 2, 173-179, 2008.
5.
de
Freitas S., Harrison I., Magoulas G.D., Mee A., Mohamad F., Oliver M., Papamarkos
G., Poulovassilis A., The Development of a System for
Supporting the Lifelong Learner, British Journal of Educational Technology,
37(6), pp 867-880, 2006.
6.
Anastasiadis
A. and Magoulas G.D., Analysing the Localisation Sites
of Proteins through Neural Networks Ensembles, Neural
Computing & Applications, vol. 15(3), 277 – 288, 2006.
7.
Anastasiadis
A., Magoulas G.D., and Vrahatis M.N, Improved sign-based learning algorithm
derived by the composite nonlinear Jacobi process, Journal of Computational and
Applied Mathematics, vol. 191, 166 – 178, 2006.
8.
Anastasiadis
A. and Magoulas G.D., Evolving Stochastic
Learning Algorithm based on Tsallis Entropic index, The
European Physical Journal B, vol. 50, 277–283, 2006.
9.
Frias-Martinez
E., Magoulas G. D., Chen S. Y., Macredie R. D., Automated User
Modeling for Personalized Digital Libraries, International
Journal of Information Management, vol. 26(3), 179-260, 2006.
10. Magoulas G.D., Anastasiadis A.D., Approaches to
Adaptive Stochastic Search Based on the Nonextensive q-Distribution,
International Journal of Bifurcation and Chaos, Vol. 16, No. 7, 2081-2091,
2006.
11. Magoulas G. D., Neuronal networks
and textural descriptors for automated tissue classification in endoscopy,
Oncology Reports, vol. 15, 997-1000, 2006.
12. Magoulas G. and Vrahatis M.N., Adaptive Algorithms
for Neural Network Supervised Learning: A Deterministic Optimization Approach,
International Journal of Bifurcation and Chaos, vol. 16(7), 1929–1950, 2006.
13. Plagianakos, V. P., Magoulas G. D.
and Vrahatis M. N., Evolutionary
training of hardware realizable
multilayer perceptrons, Neural Computing & Applications, vol. 15(1), 33-40, 2006.
14. Plagianakos, V. P., Magoulas G. D.
and Vrahatis M. N., Distributed Computing
Methodology for Training Neural Networks in an Image-guided Diagnostic
Application, Computer Methods and Programs in Biomedicine,
vol. 81(3), 228-235, 2006.
15. Anastasiadis A., Magoulas G.D., and
Vrahatis M.N., New Globally
Convergent Training Scheme Based on the Resilient Propagation Algorithm,
Neurocomputing, vol. 64, 253-270, March, 2005.
16. Anastasiadis A., Magoulas G. D., and
Vrahatis M.N, Sign-based Learning
Schemes for Pattern Classification, Pattern Recognition
Letters, vol. 26, 1926–1936, 2005.
17. Chen S.Y., Magoulas G.D., and
Dimakopoulos D., A Flexible Interface Design for Web
Directories to Accommodate Different Cognitive Styles,
Journal of the American Society for Information Science and Technology, vol.
56(1), 70-83, 2005.
18. Frias-Martinez E., Magoulas G., Chen
S., Macredie R. , Modeling Human Behavior in User-Adaptive Systems: Recent
Advances Using Soft Computing Techniques, Expert Systems with
Applications, vol. 29(2), 320–329, 2005.
19. Ghinea G., Magoulas G.D., and
Siamitros C., Multi-criteria Decision Making for
Enhanced Perception-based Multimedia Communication, IEEE Tr.
Systems, Man and Cybernetics: part A, vol. 35(6), 855-866, 2005.
20. Ghinea G., Magoulas G.D., and
Siamitros C., Intelligent Synthesis Mechanism for
Deriving Streaming Priorities of Multimedia Content, IEEE Tr.
Multimedia, vol. 7(6), 1047-1053, 2005.
21. Ghinea G., Thomas J. P., Magoulas
G.D., and Heravi S., Adaptation as a premise for perceptual-based multimedia
communications, Int. J. Information Technology and Management, vol. 4(4),
405-422, 2005.
22. Stathacopoulou R., Magoulas G. D.,
Grigoriadou M. and Samarakou M., Neuro-fuzzy
knowledge processing in intelligent learning environments for improved student
diagnosis, Information Sciences, vol. 170(2), 273-307, 2005.
23. Anastasiadis A., and Magoulas G.D., Nonextensive
statistical mechanics for hybrid learning of neural networks,
Physica A: Statistical Mechanics and its Applications, vol. 344, 372-382, 2004.
24. Chen S., Magoulas G.D. and Macredie
R. Cognitive
Styles and Users’ Reponses to Structured Information Representation,
International Journal on Digital Libraries, vol. 4(2), 93-107, 2004.
25. Ghinea G., Magoulas G. D. and Frank
A.O. Intelligent
protocol adaptation in a medical e-collaboration environment,
International Journal of Artificial Intelligence Tools, Vol. 13(1), 199-218,
2004.
26. Ghinea G., Magoulas G. D., and Frank
A. O., Intelligent Multimedia
Communication for Enhanced Medical e-Collaboration in Back Pain Treatment,
Transactions of Institute Measurement Control, vol. 26(3), 223-244, 2004.
27. Magoulas G.D., Karkanis
28. Magoulas G.D., Plagianakos V.P., and
Vrahatis M.N., Neural
Network-based Colonoscopic Diagnosis Using On-line Learning and Differential
Evolution, Applied Soft Computing, Vol. 4(4), 369-379, 2004.
29. Hossain S., Pouloudi A., Magoulas
G.D. and Grigoriadou M., IT Adoption in British and Greek Secondary Education:
Issues and Reflections, Themes in Education, vol. 4(2), 123-154, 2003.
30. Magoulas G.D., Papanikolaou K.A.,
and Grigoriadou M., Adaptive web-based learning:
accommodating individual differences through system’s adaptation,
British Journal of Educational Technology, vol. 34(4), 511 – 527, 2003.
31. O’Neill P., Magoulas G. D., and Liu
X., Improved Processing of
Microarray Data using Image Reconstruction Techniques, IEEE
Tr. Nanobioscience, vol. 2(4), 176-183, 2003.
32. Papanikolaou K., Grigoriadou M.,
Kornilakis H., and Magoulas G.D., Personalising the Interaction in a
Web-based Educational Hypermedia System: the case of INSPIRE,
User-Modeling and User-Adapted Interaction, vol. 13, 213-267, 2003.
33. Vrahatis M.N., Magoulas G.D. and
Plagianakos V.P., From linear to nonlinear iterative methods,
Applied Numerical Mathematics, vol. 45(1), 59 - 77, 2003.
34. Magoulas G.D., Plagianakos V.P., and
Vrahatis M.N., Globally convergent algorithms with
local learning rates, IEEE Tr. Neural Networks, vol. 13(3),
774-779, 2002.
35. Papanikolaou K., Grigoriadou M.,
Magoulas G.D., and Kornilakis H., Towards New Forms
of Knowledge Communication: the Adaptive Dimension of a Web-based Learning
Environment, Computers and Education, vol. 39,
333-360, 2002.
36. Plagianakos V. P., Magoulas G.D.,
and Vrahatis M.N., Deterministic
Nonmonotone Strategies for Effective Training of Multi-layer Perceptrons,
IEEE Tr. Neural Networks, vol. 13(6), 1268-1284, 2002.
37. Magoulas G.D. , Papanikolaou K.A.,
and Grigoriadou M. Neurofuzzy
Synergism for Planning the Content in a Web-based Course,
Informatica, vol. 25, 39-48, 2001.
38. Magoulas G.D., Plagianakos G.D.,
Androulakis G.S. and Vrahatis M.N., A Framework for the Development of
Globally Convergent Adaptive Learning Rate Algorithms,
International Journal of Computer Research, vol. 10(1), 1-10, 2001.
39. Magoulas G.D., Plagianakos V.P. and
Vrahatis M.N., Adaptive stepsize algorithms for
on-line training of neural networks, Nonlinear Analysis:
Theory, Methods and Applications, vol. 47, 3425-3430, 2001.
40. Parsopoulos K.E. , Plagianakos V.P.
, Magoulas G.D. and Vrahatis M.N., Objective function ``stretching’’ to
alleviate convergence to local minima, Nonlinear Analysis: Theory, Methods and Applications, vol. 47,
3419-3424, 2001.
41. Plagianakos V.P. , Magoulas G.D. and
Vrahatis M.N. , Learning in multilayer perceptrons
using global optimization strategies, Nonlinear Analysis:
Theory, Methods and Applications, vol. 47, 3431-3436, 2001.
42. Karkanis S., Magoulas G.D. and
Theofanous N., Image Recognition and Neuronal
Networks: Intelligent Systems for the Improvement of Imaging Information,
Minimally Invasive Therapy and Allied Technologies, vol. 9(3-4), 225-230,
August 2000.
43. Magoulas G.D. and Vrahatis M.N., A Class of Adaptive
Learning Rate Algorithms Derived by One-Dimensional Subminimization Methods,
Neural, Parallel and Scientific Computations, vol. 8, 147-168, 2000.
44. Pouloudi A. and Magoulas G.D. , Neural Expert
Systems in Medical Image Interpretation: Development, Use and Ethical Issues,
Journal of Intelligent Systems, vol.10 (5-6), 451-471, 2000.
45. Vrahatis M.N., Androulakis G.S.,
Lambrinos J.N. and Magoulas G.D., A class of gradient unconstrained
minimisation algorithms with adaptive stepsize, Journal of
Computational and Applied Mathematics, vol. 114, 367-386, 2000.
46. Vrahatis M.N., Magoulas G.D. and
Plagianakos V.P., Globally convergent modification of
the Qprop method, Neural Processing Letters, vol. 12(2),
159-170, October 2000.
47. Magoulas G.D., Vrahatis M.N. and
Androulakis G.S., Improving the convergence of the
back-propagation algorithm using learning rate adaptation methods,
Neural Computation, vol. 11, 1769-1796, 1999.
48. Androulakis G.S., Magoulas G.D. and
Vrahatis M.N., Geometry of learning: visualizing the
performance of neural network supervised training methods,
Nonlinear Analysis: Theory, Methods and Applications, vol. 30, 4539-4544, 1997.
49. Magoulas G.D., Vrahatis M.N. and
Androulakis G.S., Effective back-propagation training
with variable stepsize, Neural Networks, vol.10, 69-82, 1997.
50. Magoulas G.D., Vrahatis M.N. and
Androulakis G.S., On the alleviation of the problem of
local minima in back-propagation, Nonlinear Analysis: Theory,
Methods and Applications, vol. 30, 4545-4550, 1997.
51. Vrahatis M.N., Androulakis G.S. and
Magoulas G.D., On the acceleration of the
back-propagation training algorithm, Nonlinear Analysis:
Theory, Methods and Applications, vol. 30, 4551-4554, 1997.
52. King R.E., Magoulas G.D. and
Stathaki A.A., Multivariable fuzzy controller design, Control Engineering
Practice, vol.2, 431-437, 1993.
53. Magoulas G.D., King R.E. and
Stathaki A.A., Design of industrial multivariable fuzzy controllers, Studies in
Informatics and Control, vol.2, 253-261, 1993.
Home - Teaching - Research - Publications - Bio - Department
C. Articles in books and edited volumes
1.
Van
Labeke N., Magoulas G.D. and Poulovassilis A., Searching for “People Like Me”
in a Lifelong Learning System, Learning in the Synergy of Multiple Disciplines,
Proceedings of the 4th European Conference on Technology Enhanced Learning
(EC-TEL 2009) Nice, France, Sept 29–Oct 2, 2009, U. Cress, V. Dimitrova, M.
Specht (Eds.), Lecture Notes in Computer Science, Volume 5794, Springer, pp.
106-111, 2009.
2.
Van
Labeke N., Poulovassilis A. and Magoulas G.D., Using Similarity Metrics for Matching
Lifelong Learners, Intelligent Tutoring Systems, Lecture Notes
in Computer Science, vol. 5091, Proceedings of the 9th International Conference
on Intelligent Tutoring Systems (ITS 2008), B. P.Woolf, E. Aďmeur, R. Nkambou,
S. Lajoie (Eds.), Springer, pp. 142-151, 2008.
3.
Dimakopoulos
D. and Magoulas G.D., An architecture for a personalised mobile environment to
facilitate contextual lifelong learning, H. Ryu and D. Parsons (eds.),
Innovative Mobile Learning, chapter 12, 2009.
4.
Peng
C.-C. and Magoulas G.D., Sequence Processing with Recurrent Neural Networks,
Encyclopedia of Artificial Intelligence, forthcoming.
5.
de
Freitas S., Harrison I., Magoulas G.D., Papamarkos G., Poulovassilis A., Van
Labeke N., Mee A., and Oliver M., L4All: a
Web-Service Based System for Lifelong Learners, S. Salerno, M.
Gaeta, P. Ritrovato, N. Capuano, F. Orciuoli, S. Miranda and A. Pierri (eds.), The Learning Grid
Handbook: Concepts, Technologies and Applications, Volume 2: The
Future of Learning, IOS Press, 2008, ISBN: 978-1-58603-829-8.
6.
Magoulas
G.D., User Modeling in Information Portals, Encyclopedia of Portal Technologies and Applications, Arthur Tatnall (ed.), vol II,
Information Science Reference, ISBN: 978-1-59140-989-2, April 2007.
7.
Peng
C.-C. and Magoulas G.D., Adaptive Self-scaling Non-monotone BFGS Training
Algorithm for Recurrent Neural Networks, Artificial Neural Networks, J. Marques
de Sá et al. (eds.), Proceedings of the 17th ICANN 2007, Part I, Lecture Notes
in Computer Science vol. 4668, pp. 259–268, 2007.
8.
Plagianakos
V.P., Magoulas G.D. and Vrahatis M.N., Improved learning of neural nets through
global search, Global Optimization
- Scientific and Engineering Case Studies, János D. Pintér
(ed.), Series: Nonconvex Optimization and Its Applications, Vol. 85,
Springer-Verlag New York Inc, pp. 361- 388, 2006 (ISBN: 0-387-30408-8).
9.
Magoulas
G.D, Web-based instructional systems, Encyclopedia of
Human Computer Interaction, Claude Ghaoui (ed.), IDEA
publishing, ISBN: 1-59140-562-9, pp. 729-738, 2005.
10. Magoulas G.D. and Vrahatis M.N., Parameter
optimization algorithm with improved convergence properties for adaptive
learning, In the Frontiers of Computational Science, Lecture
Series on Computer and Computational Sciences, Vol. 3, G. Maroulis and Th. Simos
(eds.), Brill Academic Publishers, Leiden, The Netherlands, pp.384-398, 2005
(ISBN 90-6764-442-0).
11. Vrahatis M.N. and Magoulas G.D.,
Computational Approaches to Artificial Intelligence: Theory, Methods,
Applications. Lecture Series on Computer and Computational Sciences, Advances
in Computational Methods in Sciences and Engineering 2005, Selected papers from
the International Conference of Computational Methods in Sciences and
Engineering (ICCMSE 2005), Th. Simos, G. Maroulis, (eds.), Volume 4B, 2005, pp.1413-1415,
VSP/Brill Academic Publishers, The Netherlands, (ISBN: 9067644447).
12. Vrahatis, M.N. and Magoulas G.D,
Advances in Computational Intelligence: Theory, Methods, Applications. Selected
papers from the International Conference of Numerical Analysis and Applied
Mathematics (ICNAAM), Lecture Series on Computer and Computational Sciences, T.
Simos, G. Psihoyios, G. Tsitouras (eds), Wiley-Vch, 869-871, 2005 (ISBN:
3-527-40652-2).
13. Dounias G., Magoulas G. and Linkens
D., Intelligent Technologies in Bioinformatics and Medicine: An Introduction to
the Present Edition, in G. Dounias, G. Magoulas and D. Linkens (eds.),
Intelligent Technologies in Bioinformatics and Medicine, Published by the Univ.
of the Aegean and EUNITE (2004), pp. 1-4.
14. Frias-Martinez E., Magoulas G.D.,
Chen S., and Macredie R. Recent Soft Computing Approaches to User Modeling in
Adaptive Hypermedia. Lecture Notes in Computer Science, vol. 3137, Adaptive
Hypermedia and adaptive web-based systems, Proceedings of 3rd Int Conf Adaptive
Hypermedia, Paul De Bra, Wolfgang Nejdl (eds), Springer, pp. 104-113, 2004.
15. Magoulas, G. D., Chen, S. Y., and
Dimakopoulos, D. A Personalised Interface for Web Directories based on
Cognitive Styles. Lecture Notes in Computer Science, vol. 3196, User-Centered
Interaction Paradigms for Universal Access in the Information Society: Revised
Selected Papers of the 8th ERCIM Workshop on User Interfaces for All,
Springer-Verlag, pp. 159-166, 2004, ISBN: 3-540-23375-X.
16. Stathacopoulou R., Grigoriadou M.,
Samarakou M., Magoulas G.D., Using Simulated Students for Machine Learning.
Lecture Notes in Computer Science, vol. 3220, Proceedings of the 7th
International Conference on Intelligent Tutoring Systems (ITS 2004), James C.
Lester, Rosa Maria Vicari, Fabio Paraguau, Springer, pp. 889-891, 2004.
17. Anastasiadis A.D., Magoulas G.D.,
and Liu X. Classification of Protein Localisation Patterns via Supervised
Neural Network Learning. Lecture Notes in Computer Science, vol. 2810, Advances
in Intelligent Data Analysis V, Proceedings of the 5th International Symposium
on Intelligent Data Analysis, M. Berthold, H.-J. Lenz, E. Bradley et al.
(eds.),
18. O’Neill P., Magoulas G. D., and Liu
X. Obtaining Quality Microarray Data via Image Reconstruction. Lecture Notes in
Computer Science, vol. 2810, Advances in Intelligent Data Analysis V,
Proceedings of the 5th International Symposium on Intelligent Data Analysis, M.
Berthold, H.-J. Lenz, E. Bradley et al. (eds.),
19. Grigoriadou, M., Kornilakis, H.,
Papanikolaou, K.A., and Magoulas, G.D. Fuzzy Inference for Student Diagnosis in
Adaptive Educational Systems. Lecture Notes in Artificial Intelligence, vol.
2308, Methods and Applications of Artificial Intelligence: Proceedings of the
2nd Hellenic Conference on AI, SETN2002, Vlahavas and C.D. Spyropoulos (eds.),
20. Papanikolaou K.A., Grigoriadou M.,
Kornilakis H., and Magoulas G.D. INSPIRE: an INtelligent System for
Personalized Instruction in a Remote Environment. Lecture Notes in Computer
Science, vol. 2266, Hypermedia: Openess, Structural Awareness, and Adaptivity,
S. Reich. M. Tzagarakis, P.M.E.
21. Ghinea G. and Magoulas G. D.,
Perceptual considerations for quality of service management: an integrated
architecture. Lecture Notes in Computer Science, Proceedings of the User
Modeling Conference, Springer, 234-236, 2001.
22. Magoulas G.D. and Prentza A., Machine learning in
medical applications, in Machine Learning and its
Applications: Advanced Lectures, G. Paliouras, V. Karkaletsis and C.D.
Spyropoulos (Eds.), Lecture Notes in Artificial Intelligence, vol. 2049,
Springer-Verlag, pp. 300-307, 2001.
23. Parsopoulos, K., Plagianakos, V.P.,
Magoulas, G.D., and Vrahatis M.N., Improving the particle swarm
optimizer by function “stretching”, in Advances in convex
analysis and global optimization, Hadjisavvas N. and Pardalos P. (ed.), vol.
54, Noncovex Optimization and its Applications, Kluwer Academic Publishers,
Dordrecht, The Netherlands, 2001, Chapter 28, pp.445-457, ISBN 0-7923-6942-4.
24. Plagianakos V.P., Magoulas G.D. and
Vrahatis M.N., Supervised training using global
search methods, in Advances in convex analysis and global
optimization, Hadjisavvas N. and Pardalos P. (ed.), vol. 54, Noncovex Optimization
and its Applications, Kluwer Academic Publishers, Dordrecht, The Netherlands,
2001, Chapter 26, pp.421-432, ISBN 0-7923-6942-4.
25. Plagianakos V.P., Magoulas G.D. and
Vrahatis M.N., Learning rate adaptation in
stochastic gradient descent, in Advances in convex analysis
and global optimization, vol. 54, Noncovex Optimization and its Applications,
Hadjisavvas N. and Pardalos P. (ed.), Kluwer Academic Publishers, Dordrecht,
The Netherlands, 2001, Chapter 27, pp.433-444, ISBN 0-7923-6942-4.
26. Papanikolaou K., Magoulas G.D., and
Grigoriadou M., A connectionist approach for supporting personalized learning
in a web-based learning environment. Lecture Notes in Computer Science, vol. 1892,
Proceedings of the International Conference on Adaptive Hypermedia and Adaptive
Web-based Systems, Springer, pp. 189-201, 2000.
27. Magoulas G.D., Plagianakos V.P.,
Androulakis G.S. and Vrahatis M.N., A framework for the development of globally
convergent adaptive learning rate algorithms. Advances in Intelligent Systems
and Computer Science, N.E. Mastorakis ed., World Scientific and Engineering
Society Press, pp.207-212, 1999.
28. Magoulas G.D., Plagianakos V.P.,
Androulakis G.S. and Vrahatis M.N., A framework for the development of globally
convergent adaptive learning rate algorithms, in Advances in Intelligent
Systems and Computer Science, N.E. Mastorakis ed., World Scientific and
Engineering Society Press, 1999, pp.207-212.
29. Plagianakos V.P., Magoulas G.D.,
Androulakis G.S. and Vrahatis M.N., Global search methods for neural network
training. Advances in Intelligent Systems and Computer Science, N.E. Mastorakis
ed., World Scientific and Engineering Society Press, pp.47-52, 1999.
30. Magoulas G.D. and Vrahatis M.N., A
model for local convergence analysis of batch-type training algorithms with
adaptive learning rates, in Recent Advances in Circuits and Systems,
Mastorakis, N. E. (ed.), World Scientific, pp. 321-326, 1998.
31. Magoulas G.D., Vrahatis M.N., Grapsa
T. N. and Androulakis G.S., A training method for discrete multilayer neural
networks, in Mathematics of Neural Networks: Models, Algorithms &
Applications, Ellacot, S. W., Mason J. C. and I. J. Anderson (eds.), Kluwer
Academic Publishers, Operations Research/Computer Science Interfaces series,
chapter 41, pp. 245-249, 1997.
32. Magoulas G.D., Vrahatis M.N., Grapsa
T. N. and Androulakis G.S., Neural network supervised training based on a
dimension reducing method, in Mathematics of Neural Networks: Models, Algorithms
& Applications, Ellacot, S. W., Mason, J. C. and Anderson, I. J. (eds.),
Kluwer Academic Publishers, Operations Research/Computer Science Interfaces
series, chapter 42, pp. 250-254, 1997.
33. Androulakis G.S., Magoulas G.D. and
Vrahatis M.N., Minimization techniques in neural network supervised training,
In Selected Works of the 6th International Colloquium on Differential
Equations, VSP International Science Publishers, pp. 9-16, 1996.
Home - Teaching - Research - Publications - Bio - Department
D. Conference and workshop papers
1.
Cocea,
M, Gutierrez-Santos, S. Magoulas, G.D. Enhancing Modelling
of Users’ Strategies in Exploratory Learning through Case-base Maintenance.
In Proceedings of 14th UK Workshop on Case-Based Reasoning, 2009, pp. 2-13.
2.
Lewis
T.E., Magoulas G.D. Strategies to Minimise the Total Run
Time of Cyclic Graph Based Genetic Programming with GPUs, The
ACM Genetic and Evolutionary Computation Conference (GECCO-2009), pp.
1379-1386.
3.
Cocea
M., Magoulas G., Context-dependent
Personalised Feedback Prioritisation in Exploratory Learning for Mathematical
Generalisation. Proceedings of the 17th International Conference
User Modelling, Adaptation and Personalisation Conference, UMAP 2009 (formerly
UM and AH), pp. 271-282.
4.
Cocea,
M., Magoulas, G. Identifying
strategies in users exploratory learning behaviour for mathematical
generalisation. In Proc. 14th International Conference on
Artificial Intelligence in Education (AIED 2009), Building Learning Systems
that Care: From Knowledge Representation to Affective Modelling, vol. 200
Frontiers in Artificial Intelligence and Applications, V. Dimitrova, R.
Mizoguchi, B. Du Boulay and A. Graesser (eds.), July 2009, pp 626-628.
5.
Cocea,
M., Magoulas, G. Task-oriented
modeling of learner behaviour in exploratory learning for mathematical
generalisation. In Proceedings of the 2nd International Workshop on Intelligent Support
for Exploratory Environments (ISEE’09), in conjunction with the 14th
International Conference on Artificial Intelligence in Education (AIED
2009), pp. 16-24.
6.
de
Freitas, S. Rebolledo-Mendez, G., Liarokapis, F., Magoulas, G., Poulovassilis,
A. Developing an evaluation methodology
for immersive learning experiences in a virtual world. In
Rebolledo-Mendez, G., Liarokapis, F., de Freitas, S. (Eds) Proceedings of 2009
Conference in Games and Virtual Worlds for Serious Applications, IEEE, pp
43-50.
7.
Cocea
M., Gutierrez-Santos S. and Magoulas G., Challenges for Intelligent Support in
Exploratory Learning: the case of ShapeBuilder. In Proceedings of the
1st International Workshop on Intelligent Support for Exploratory Environments
(ISEE08), in conjunction with the third European Conference on
Technology-Enhanced Learning (EC-TEL ’08).
8.
Cocea
M. and Magoulas G., Combining intelligent methods for
learner modelling in exploratory learning environments, in
Proceedings of the 1st International Workshop on Combinations of Intelligent Methods
and Applications (CIMA 2008), in conjunction with the 18th European Conference
on Artificial Intelligence (ECAI-08), pp. 13–18.
9.
Lewis
T. E and Magoulas G.D., TREAD: A New Genetic
Programming Representation Aimed at Research of Long Term Complexity Growth, The ACM Genetic and Evolutionary
Computation Conference (GECCO’08), July 12–16, 2008, Atlanta, Georgia, USA, pp.
1339-1340.
10.
Voulgaris
Z. and Magoulas G. D., A
discernibility-based approach to feature selection for microarray data,
Proceedings of IEEE International Conference of Intelligent Systems, Varna,
Bulgaria, Sept. 2008, vol.3, pp.
21.2-21.7.
11.
Voulgaris
Z. and Magoulas G. D., Dimensionality
reduction for feature and pattern selection in classification problems.
Proceeding of The Third International Multi-Conference on Computing in the
Global Information Technology, Athens, Greece, July 2008, pp. 160-165.
12.
Voulgaris
Z. and Magoulas G.D., Extensions of the k
Nearest Neighbour Methods for Classification Problems, Proc. of
the 26th IASTED International Conference on Artificial Intelligence
and Applications, AIA 2008, Innsbruck, Austria, February 11 – 13, 2008, pp.
23-28.
13.
Anastasiadis
A.D., Georgoulas G., Magoulas G.D., and Tzes A., Adaptive Particle Swarm Optimizer
with Nonextensive Schedule, Proceedings of the Genetic and Evolutionary
Computation Conference 2007 (GECCO’07), July 7–11, 2007, London, UK, pp. 168.
14.
Anastasiadis
A.D., Magoulas, G.D., Georgoulas G., and Tzes A., Nonextensive Particle Swarm
Optimization Methods, Proceedings of the Conference in Numerical Analysis
(NumAn2007), September 3-7, Kalamata, pp. 15-18.
15.
Baajour
H., Magoulas G. D., and Poulovassilis A., Modelling the
lifelong learner in a services-based environment, Proceedings of
the 2nd International Conference on Internet Technologies and
Applications (ITA 07), Wrexham, North East Wales, UK 4-7 September 2007, pp.
191-201.
16.
Baajour
H., Magoulas G. D., and Poulovassilis A., Designing
services-enabled personalisation for planning of lifelong learning based on
individual and group characteristics, Proceedings of the
Workshop on Personalisation in E-Learning Environments at Individual and Group
Level, 11th International Conference on User Modeling (UM 2007), Corfu, Greece,
25-29 June 2007, pp. 8-15.
17.
Peng
C.-C., and Magoulas G.D. Effective Modification of the BFGS Method for Training
Recurrent Neural Networks, Proceedings of the Conference in Numerical Analysis
(NumAn2007), September 3-7, Kalamata, pp. 113-117.
18.
Peng
C.-C. and Magoulas G.D., Adaptive Nonmonotone Conjugate Gradient Training
Algorithm for Recurrent Neural Networks, Proc. 19th IEEE International
Conference on Tools with Artificial Intelligence 2007 (ICTAI’07), 29-31 October
2007, Patras, Greece, pp. 374-381.
19.
Dimakopoulos,
D.N. and Magoulas, G.D. A personalised
mobile environment for lifelong learners, Proceedings of
IADIS International Conference on WWW/Internet 2006, October 5-8, 2006, Murcia,
Spain, 31-38.
20.
Magoulas,
G.D. and Dimakopoulos, D. An Adaptive Fuzzy Model for Personalization with
Evolvable User Profiles, Proceedings of IEEE 2nd International Symposium on
Evolving Fuzzy Systems, September 7-9, 2006, Ambelside, Lake District, UK,
336-341.
21.
Magoulas
G.D., Papamarkos G., Poulovassilis A., A Services-enabled Environment for Personalising Lifelong
Learning Pathways, Proceedings of Workshops held at the 4th
International Conference on Adaptive Hypermedia and Adaptive Web-based Systems,
Dublin, Ireland, June 20, 2006, Lecture Notes in Learning and Teaching,
Weibelzahl, S., Cristea, A., editors, Dublin: National College of Ireland,
2006. (ISSN 1649-8623), 140-147.
22.
de
Freitas S., Magoulas G.D., Oliver M., Papamarkos G., Poulovassilis A., Harrison
I, Mee A., L4All - a web-service based system for Lifelong Learners,
Proceedings of eChallenges'2006, Workshop on Next Generation in Technology
Enhanced Learning, October 25-27, 2006, Barcelona, IOS Press, pp 1477-1484.
23.
Magoulas
G.D. and Anastasiadis A., A nonextensive probabilistic model for global
exploration of the search space. In T. Simos, G. Psihoyios, G. Tsitouras,
Proceedings of International Conference of Numerical Analysis and Applied
Mathematics (ICNAAM), 16-20 September 2005, Rhodes, Greece, Wiley-Vch, 878-881
(ISBN: 3-527-40652-2).
24.
Magoulas
G.D. and Dimakopoulos D.N. Designing
Personalised Information Access to Structured Information Spaces,
Proceedings of the Workshop on New Technologies for Personalized Information
Access, 10th International conference on User Modeling, July 24-29, 2005,
Edinburgh, Scotland, UK, 64-73.
25.
Magoulas,
G.D. and Dimakopoulos, D. Personalisation in e-learning: an approach based on services,
Proceedings of IADIS International Conference on WWW/Internet 2005, October
19-22, 2005, Lisbon, Portugal, 312-316.
26.
Anastasiadis
A.D., and Magoulas G.D., Nonextensive
Entropy and Regularization for Adaptive Learning, Proc. of
the IEEE International Joint Conference on Neural Networks (IJCNN-04),
Budapest, Hungary, 25-29 July, 2004, vol. 2, 1067-1072.
27.
Anastasiadis
A.D., Magoulas G.D., and Vrahatis M.N., A New Learning
Rates Adaptation Strategy for the Resilient Propagation Algorithm.
In M. Verleysen (ed.), Proceedings of the 12th European Symposium on Neural
Networks (ESANN-04), April 28-30, Bruges, Belgium, D-side Publications: Evere,
1-6, 2004.
28.
Magoulas
G.D., Plagianakos V.P., Tasoulis D.K., and Vrahatis M.N., Tumor detection in
colonoscopy using the unsupervised k-windows clustering algorithm and neural
networks. In Proceedings of the Fourth European Symposium on
Biomedical Engineering, Session 3, June 25-27, 2004, Patras, Greece.
29.
Ghinea
G. and Magoulas G. Integrating Perceptech Requirements through Intelligent
Computation of Priorities in Multimedia Streaming, Lecture Series on Computer
and Computational Sciences, Vol. 1, Proceedings of the International Conference
of Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004), VSP
International Science Publishers, Zeist, The Netherlands, 2004,pp.856-859.
30.
Anastasiadis
A.D., Magoulas G.D. and Vrahatis M.N., A globally convergent Jacobi-bisection
method for neural network training, Lecture Series on Computer and
Computational Sciences, Vol. 1, Proceedings of the International Conference of
Computational Methods in Sciences and Engineering 2004 (ICCMSE 2004), VSP
International Science Publishers, Zeist, The Netherlands, 2004, pp.843-848.
31.
Stathacopoulou
R., Samarakou M., Grigoriadou M., Magoulas G.D., A Neuro-Fuzzy Approach to
Detect Student's Motivation. In Kinshuk, Chee-Kit Looi, Erkki Sutinen,
Demetrios G. Sampson, Ignacio Aedo, Lorna Uden and Esko Kahkonen, Proceedings
of the IEEE International Conference on Advanced Learning Technologies (ICALT
2004), 30 August-1 September 2004, Joensuu, Finland, 71-75, IEEE Computer
Society.
32.
O'Neill
P., Magoulas G.D., Liu X., Quality Processing of Microarray Image Data through
Image Inpainting and Texture Synthesis. In Proceedings of the 2004 IEEE
International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2004),
Arlington, VA, USA, 15-18 April 2004, vol. 1, 117-120.
33.
Magoulas
G.D., Building diverse neural ensembles for bioinformatics applications,
Proceedings of the Workshop on Intelligent Technologies in Bioinformatics and
Medicine, European Symposium on Intelligent Technologies, Hybrid Systems and
their Implementation on Smart Adaptive Systems (EUNITE 2004), Aachen, Germany,
June 10-12, 2004.
34.
Chen,
S. Y. and Magoulas, G. D. The Relationships between Cognitive Styles and Information
Representation in Web Directories. In Proceedings of the LIDA Conference 2003,
Libraries in the Digital Age, May 26-30, 2003.
35.
Ghinea
G., Magoulas G. D. and Frank A.O. Intelligent Protocol Adaptation for Enhanced
Medical e-Collaboration. In Proceedings of the International FLAIRS Conference,
May 12-14, 2003 St. Augustine, Florida.
36.
Ghinea
G., Magoulas G. D. and Thomas J.P., Intelligent Management of QoS requirements
for Perceptual Benefit. In Proceedings 3rd Conference on Intelligent Systems
Design and Applications, pp. 437-446, Tulsa, USA, 2003.
37.
Anastasiadis
A. and Magoulas G.D. Neural Network-based Prediction of Proteins Localisation
Sites. In Proceedings of European Symposium on Intelligent Technologies, Hybrid
Systems and their implementation on Smart Adaptive Systems, 10-12 July 2003,
Oulu, Finland, 318 – 325.
38.
Anastasiadis
A.D., Magoulas G.D., and Vrahatis M.N., An efficient
improvement of the Rprop algorithm. In M. Gori and S. Marinai
(eds.), Artificial Neural Networks in Pattern Recognition, Proceedings of the
1st Int Association of Pattern Recognition-TC3 Workshop, Florence, Italy,
September 2003, 197-201. Firenze: Stampa Digitale.
39.
Magoulas,
G. D., Chen, S. Y., and Papanikolaou , K. A. Integrating Layered
and Heuristic Evaluation for Adaptive Learning Environments.
In Proceedings of the Second Workshop on Empirical Evaluation of Adaptive
Systems, 9th International Conference on User Modeling UM2003, June 22-26,
2003.
40.
Plagianakos
V .P .,Magoulas G .D .and Vrahatis M .N ., On-line neural network training (in
Greek), Order and Chaos in Nonlinear Dynamical Systems Vol .8, Proc. of the 9th
Panhellenic Conference /14th Summer School on Non -linear dynamics chaos and
complexity, Patras , July 23 –August 2, 2001, T .Bountis S .Ichtiaroglou and S
.Pnevmatikos (eds.).,K . Sfakianaki Editions, Thessaloniki, pp .329 –340,
2003.[SET 960-7258-16-9 ][ISBN 960-87136-2-5 ].
41.
Magoulas,
G.D., Eldabi, T., and Paul R.J., Adaptive Stochastic
Search Methods for Parameter Adaptation of Simulation Models,
in Proceedings of the IEEE International Symposium on Intelligent Systems,
Varna, Bulgaria, Sept. 10-12, 2002, vol. 2, 23-27.
42.
Ghinea
G., Magoulas G.D., and Frank A.O., Intelligent
Multimedia Transmission for Back Pain Treatment, in
Proceedings of European Symposium on Intelligent Technologies, Hybrid Systems
and their Implementation on Smart Adaptive Systems (EUNITE 2002), Session
"Intelligent E-health Applications in Medicine", 19-21 September
2002, Albufeira, Portugal, 309-316.
43.
Magoulas
G.D., Eldabi T., and Paul R.J., Global search strategies for simulation
optimization, in E. Yücesan, C.-H. Chen, J. L. Snowdon, and J. M. Charnes,
eds., Proceedings of the Winter Simulation Conference, December 8-11, 2002, San
Diego, California, vol. 2, 1978-1985.
44.
Vrahatis
M .N .,Magoulas G .D .and Plagianakos V .P ., Introduction to artificial neural
networks (in Greek), Order and Chaos in Nonlinear Dynamical Systems Vol .7,
Proceedings of the 8th Panhellenic Conference /13th Summer School on Non-linear
dynamics chaos and complexity, Patras July 17 –28, 2000, T .Bountis D .Ellinas
and I .Grispolakis (eds.), Pnevmatikos publications Athens pp .225 –247, 2002.
45.
Plagianakos
V .P .,Magoulas G .D .and Vrahatis M .N .,Tumor detection in colonoscopic
images using hybrid methods for on –line neural network training, Proc. Neural
Networks and Expert Systems in Medicine and Healthcare ,(NNESMED 2001), G .M
.Papadourakis (ed.), Technological Educational Institute of Crete Heraklion 2001,
pp .59 –64 [ISBN 9608531659].
46.
Ghinea
G. and Magoulas G. D., A novel application of the analytic hierarchy process in
“perceived” quality of service management, in Proceedings of IASTED
International Conference on Applied Informatics, Innsbruck, Austria, February
19-22, 2001, pp. 43-47.
47.
Grigoriadou
M., Papanikolaou K., Kornilakis H., and Magoulas G., Towards new forms of
communication of knowledge in educational hypermedia systems, in Proceedings of
the Computer-Aided Learning Conference (CAL2001), April 2-4, 2001, University
of Warwick, Coventry, UK.
48.
Pouloudi
A., Magoulas G. D., Grigoriadou M., Hossain S., and Kanidis V., IT supported
learning in schools: insights from the british and greek experience, in
Proceedings of the Computer-Aided Learning Conference (CAL2001), April 2-4,
2001, University of Warwick, Coventry, UK.
49.
Parsopoulos,
K., Plagianakos, V.P., Magoulas, G.D., and Vrahatis M.N., Stretching
technique for obtaining global minimizers through particle swarm optimization, in Proceedings of the Particle
Swarm Optimization Workshop, April 6-7, 2001, Indiana, USA, pp. 22-29.
50.
Stathacopoulou
R., Magoulas G.D., Grigoriadou M., and Mitropoulos D., Neural network-based
fuzzy modeling of the diagnostic process, in Proceedings of the 10th
International Conference on Artificial Intelligence in Education (AI-ED 2001),
San Antonio, Texas, May 19-23 2001, USA.
51.
Grigoriadou
M., Papanikolaou K., Kornilakis H., and Magoulas G., INSPIRE: an INtelligent
System for Personalized Instruction in a Remote Environment, in P. De Bra, P.
Brusilovsky & A. Kobsa (eds), Pre-Workshop Proceedings: Third Workshop on
Adaptive Hypertext and Hypermedia, 8th International Conference on User
Modeling (UM2001), Sonthofen, Germany, July 13, 2001, 31-40.
52.
Magoulas
G.D. and Ghinea G., Neural network-based interactive
multicriteria decision making in a quality of perception-oriented management
scheme, in Proceedings of the INNS-IEEE International Joint
Conference on Neural Networks, Washington DC, 15-19 July 2001, USA, vol. 4,
2536-2541.
53.
Plagianakos
V.P., Magoulas G.D., Nousis N.K., and Vrahatis M.N., Training
multilayer networks with discrete activation functions, in Proceedings of the
INNS-IEEE International Joint Conference on Neural Networks, Washington DC,
15-19 July 2001, USA, vol. 4, 2805-2810.
54.
Plagianakos
V.P., Magoulas G.D., Nousis N.K., and Vrahatis M.N., PVM-based
training of large neural architectures, in Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington DC, 15-19 July
2001, USA, vol. 4, 2584-2589.
55.
Magoulas
G.D., Plagianakos V.P., and Vrahatis M.N., Hybrid methods using evolutionary
algorithms for on-line training, in Proceedings of the
INNS-IEEE International Joint Conference on Neural Networks, Washington DC,
15-19 July 2001, USA, vol. 3, 2218-2223.
56.
Ghinea
G. and Magoulas G.D., Quality of Service
for Perceptual Considerations: An Integrated Perspective, in
Proceedings of 2001 IEEE International Conf. on Multimedia & Expo
(ICME2001), 22-25 August 2001, Tokyo, Japan, 571-574.
57.
Ghinea
G., Magoulas G. D. and Siamitros C., Perceptual considerations in a QoS
framework: a fuzzy logic formulation, in Proceedings of the 4th IEEE Workshop
on Multimedia Signal Processing, October 3-5, 2001, Cannes, France,
353-358.
58.
Karkanis
S.A., Magoulas G.D., Iakovidis D.K., Karras D.A. and Maroulis D.E., Evaluation of textural feature extraction schemes for
neural network-based interpetation of regions in medical images, in Proceedings of IEEE
International Conference on Image Processing (ICIP-2001), October 7-10, 2001,
Thessaloniki, Greece, vol. 1, 281-284.
59.
Magoulas
G.D., Plagianakos V.P. and Vrahatis M.N., Improved Neural
Network-based Interpretation of Colonoscopy Images Through On-line Learning and
Evolution, in Proceedings of European Symposium on
Intelligent Technologies, Hybrid Systems and their Implementation on Smart
Adaptive Systems (EUNITE 2001), 12-14 December 2001, Tenerife, Spain,
402-407. Also in Adaptive Systems and Hybrid Computational Intelligence in
Medicine G .D .Dounias and D .A .Linkens (eds.),European Network of Excellence
on Intelligent Technologies for Smart Adaptive Systems Published by the
University of the Aegean Chios Greece 2001,pp .38 –43,[ISBN 960-7475-19-4 ].
60.
Papanikolaou
K., Magoulas G.D., and Grigoriadou M., The role of the educational material for
personalised learning in a web-based course, in Proceedings of the 1st Research
Workshop of the European Distance Education Network (EDEN-2000): Research and
Innovation in Open and Distance Learning, Prague, Czech Republic, 16-17 March
2000, 151-154.
61.
Magoulas,
G.D., Plagianakos, V.P., and Vrahatis, M.N., Global learning rate adaptation in
on-line neural network training, in Proceedings of the 2nd International ICSC
Symposium on Neural Computation, May 23-26, 2000, Technical University of
Berlin, Germany.
62.
Vrahatis,
M.N., Magoulas, G.D., and Plagianakos, V.P., Neural
network supervised training as minimization problem (in
Greek), Dymamical Systems Vol. 6, Proc. of the 7th Panhellenic Conference/12th
Summer School on Non-linear dynamics, chaos and complexity, Patras, July 14-24,
1999, Pnevmatikos publications, Athens, pp. 243-262, 2000.
63.
Papanikolaou
K., Magoulas G.D., and Grigoriadou M., Computational intelligence in
adaptive educational hypermedia, in Proceedings of the INNS-IEEE International
Joint Conference on Neural Networks, 24-27 July 2000, Como, Italy, vol. 6,
629-634.
64.
Magoulas,
G.D., Plagianakos, V.P., and Vrahatis, M.N., Development and convergence analysis
of training algorithms with local learning rate adaptation, in Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, 24-27 July 2000, Como,
Italy, vol. 1, 21-26.
65.
Karkanis,
S.A., Magoulas, G.D., Iakovidis, D.K., Maroulis, D.E., and Schurr, M.O., On the
importance of feature descriptors for the characterisation of texure, in
Proceedings of the World Multi-conference on Systemics, Cybernetics and
Informatics, July 23-26, 2000, Orlando, Florida, U.S.A.
66.
Karkanis,
S.A., Iakovidis, D.K., Maroulis, D.E., Magoulas, G.D., and Theofanous, N.G., Tumor recognition
in endoscopic video images using artificial neural network architectures, Proceedings of the 26th Euromicro
Conference, Workshop on Medical Informatics, 5th-7th 5-7 September, 2000,
Maastricht, the Netherlands, vol. 2, 423-429.
67.
Hossain
S., Pouloudi A., and Magoulas G. D., Issues of IT adoption in schools, in
Proceedings of the Business Information Technology Conference- BIT 2000,
November 1-2, 2000, Manchester, U.K.
68.
Vrahatis
M .N .,Magoulas G .D .,Parsopoulos K .E .and Plagianakos V .P ., Introduction
to artificial neural network training and applications, Proceedings of the 15th
Annual Conference of Hellenic Society for Neuroscience (Neuroscience 2000),
October 27 –29, 2000, Patras Greece.
69.
Magoulas
G. D. , Papanikolaou K. and Grigoriadou M., Adaptive lesson presentation based
on connectionist knowledge representation, in Proceedings of the International
Conference in Technology and Education, Edinbrough, March 1999.
70.
Grigoriadou
M., Magoulas G. D. and Panagiotou M., A hybrid decision making model for
intelligent tutoring systems, in Proceedings of the 5th International
Conference of the Decision Sciences Institute, 195-197, Athens, Greece, July
1999.
71.
Magoulas
G.D. and Vrahatis M.N., Analysis and synthesis of a class of neural network training
algorithms derived by one-dimensional subminimization methods, in Integrating
Technology and Human Decisions: Global Bridges into the 21 ST Century,
Proceedings of the5th International Conference of the Decision Sciences
Institute, D .K .Despotis and C .Zopounidis eds ., Athens, Greece, July 1999,
vol. 1, pp .512 –514. 512-514, 1999.
72.
Magoulas
G.D., A new sign-method in neural network training for embedded control
applications, Proceedings of the 5th International Conference of the Decision
Sciences Institute, 2001-2003, Athens, Greece, July 1999.
73.
Stathacopoulou
R. , Magoulas G.D. and Grigoriadou M., Neural network-based fuzzy
modeling of the student in intelligent tutoring systems, Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington, U.S.A., 10-16
July 1999, vol. 5, 3517-3521.
74.
Papanikolaou
K., Magoulas G.D., and Grigoriadou M., A connectionist approach for
adaptive lesson presentation in a distance learning course, Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington, U.S.A., 10-16
July 1999, vol. 5, 3522-3526.
75.
Magoulas
G. D., Plagianakos V., and Vrahatis M. N., Sign-methods for training with
imprecise error function and gradient values, Proceedings of the INNS-IEEE International
Joint Conference on Neural Networks, Washington, U.S.A., 10-16 July 1999, vol.
3, 1768-1773.
76.
Plagianakos
V., Vrahatis M. N. and Magoulas G. D., Nonmonotone methods for backpropagation
training with adaptive learning rate, Proceedings of the INNS-IEEE
International Joint Conference on Neural Networks, Washington, U.S.A., 10-16
July 1999, vol. 3, 1762-1767.
77.
Vrahatis
M. N., Magoulas G. D., and Plagianakos V., Convergence analysis of the
quickprop method, in Proceedings of the INNS-IEEE International Joint Conference on
Neural Networks, Washington, U.S.A., 10-16 July 1999, vol. 2, 1209-1214.
78.
Karkanis,
S.A., Magoulas, G.D., Grigoriadou, M. and Schurr, M., Detecting abnormalities
in colonoscopic images by textural description and neural networks, in Proceedings of the Workshop
"Machine Learning in Medical Applications", 59-62, Chania, Greece,
July 1999.
79.
Plagianakos
V., Magoulas G. D. and Vrahatis M. N., Nonmonotone learning rules for
backpropagation networks, Proceedings of the 6th IEEE International Conference on Electronics,
Circuits and Systems, vol. 1, 291-294, Paphos, Cyprus, 5-8 September 1999.
80.
Magoulas
G. D., Plagianakos V., and Vrahatis M. N., Effective neural network training
with a different learning rate for each weight, Proceedings of the 6th IEEE
International Conference on Electronics, Circuits and Systems, Paphos, Cyprus,
5-8 September 1999, vol. 1, 591-594, 1999.
81.
Karkanis,
S., Magoulas, G.D., Karras, D. and Grigoriadou, M., Neural network-based
textural labeling of images in multimedia applications, in Proceedings of the
25th Euromicro Conference, 8-10 September 1999, Milan, Italy, vol. 2, 392-396.
82.
Plagianakos,
V.P., Magoulas, G.D., Androulakis, G.S., and Vrahatis, M.N., Global search
methods for neural network training, in Proceedings of the 3rd IEEE-IMACS World
Multiconference on Circuits, Systems, Communications and Computers, vol. 1,
3651-3656, Athens, Greece, July 1999. Also in Advances in Intelligent Systems
and Computer Science N.E. Mastorakis ed .,World Scientific and Engineering
Society Press, pp .47 –52, 1999.
83.
Magoulas,
G.D., Plagianakos, V.P., Androulakis, G.S., and Vrahatis, M.N., A framework for the
development of globally convergent batch training algorithms, in Proceedings of the 3rd
IEEE-IMACS World Multiconference on Circuits, Systems, Communications and
Computers, vol. 1, 3641-3646, Athens, Greece, July 1999. Also in Advances in
Intelligent Systems and Computer Science N .E .Mastorakis ed., World Scientific
and Engineering Society Press, pp .207 –212, 1999.
84.
Magoulas,
G.D., Karkanis, S., Karras, D. and Vrahatis, M.N., Comparison study of
textural descriptors for training neural network classifiers, in Proceedings of the 3rd
IEEE-IMACS World Multiconference on Circuits, Systems, Communications and
Computers, vol. 1, 6221-6226, Athens, Greece, July 1999. Also in Computers and
Computational Engineering in Control N .E .Mastorakis (ed.),World Scientific
and Engineering Society Press 1999,pp. 193 –198.
85.
Magoulas
G. D., Papanikolaou K. and Grigoriadou M., Towards a computationally
intelligent lesson adaptation for a distance learning course, in Proceedings of the 11th IEEE
International Conference on Tools with Artificial Intelligence, Chicago, 9-11
November 1999, pp. 5-11.
86.
Magoulas
G. D. and Pouloudi A., Ethical issues in the use of neural network-based
methodologies for image interpretation in medicine, in Proceedings of
ETHICOMP99 - The 5th International Conference on the Social and
Ethical Impacts of Information and Communication Technologies, LUISS Guido
Carli University, Rome, Italy, October 1999.
87.
Plagianakos,
V.P., Magoulas, G.D., and Vrahatis, M.N., Optimization strategies and
backpropagation neural networks, in Proceedings of the 7th Hellenic Conference
on Informatics, D.I. Fotiadis and S.D. Nikolopoulos (eds.), Ioannina Greece
August 26 –29, 1999, pp .V .88 –V .95.
88.
Magoulas
G.D. and Vrahatis M.N., A model for local convergence analysis of batch-type
training algorithms with adaptive learning rates, In Proceedings of the 2nd
IMACS International Conference on Circuits Systems & Computers, vol. 1,
86-91, Athens, Greece, 1998. Also In Recent Advances in Circuits and Systems N
.E. Mastorakis ed., World Scientific Publishing Co .Pte .Ltd, 1998, pp .321
–326.
89.
Magoulas
G.D. and Vrahatis M.N., New optimization algorithms for efficient neural
network training, in Lipitakis E.A. (ed.) Proceedings of the 4th
Hellenic-European Research Conference on Computational Mathematics and
Applications, Athens, Greece, Sept. 24-26, p. 209-216, 1998 [ISBN
960-85176-7-2].
90.
Papaspyridis
A., Janetis J. Berger R. and Magoulas G. D., Designing mixed fuzzy logic and
PID embedded automotive control systems with FLDE Autostudio&trade, in
Proceedings of the 6th European Congress on Intelligent Techniques and Soft
Computing-EUFIT'98, 1998.
91.
Androulakis
G.S., Magoulas G.D. and Vrahatis M.N., Minimization techniques in neural
network supervised training, In Proceedings of the 6th International Colloquium
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microarray image processing, IEEE Transactions on NanoBioscience, 3(4),
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Journal of Medical Informatics, vol. 73(1), 1-23, 2004.
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On the Computation of all global minimizers through particle swarm
Optimization, IEEE Transactions on Evolutionary Computation, 8 (3), pp.
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Home - Teaching - Research - Publications - Bio - Department
In
books, edited volumes and PhD dissertations
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Tzafestas
S.G. and Anthopoulos Y., Supervised learning in multilayer perceptrons: the
back-propagation algorithm. In Soft Computing in Systems and Control
Technology, World Scientific Series in Robotics and Intelligent Systems, Vol.
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Alexopoulos
S., Μια κλάση
αλγορίθµων
µε την ιδιότητα της
συζυγίας
για τη
βελτιστοποίηση µη
γραµµικών
συναρτήσεων
χωρίς
περιορισµούς (A class of algorithms with the conjugate property for unconstrained
optimization of nonlinear functions), PhD dissertation, Department of
Mathematics,
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Gallagher
M. R., Multi-layer Perceptron Error Surfaces: Visualization, Structure and
Modelling, PhD dissertation, Department of Computer Science and Electrical
Engineering, University of Queensland, St Lucia 4072, Australia, January, 2000.
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van
den Bergh F., An analysis of particle swarm optimisers, PhD dissertation,
University of Pretoria, November 2001.
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Manioudakis
G., Αλγόριθµοι µάθησης
µε εφαρµογή σε αναγνώριση δυναµικών συστη µάτων (Learning algorithms with
application to dynamic systems recognition), PhD dissertation,
Department of Computer Engineering and Informatics,
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Skurichina
M .,Stabilizing weak classifiers PhD thesis Quantitative Imaging Group
Department of Imaging Science and Technology Faculty of Applied Sciences Delft
University of Technology Delft The Netherlands, October 15, 2001.
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Buendia
F. and Diaz P. A Framework for Educational Adaptive Hypermedia Applications.
Ιn: P. De Bra, P. Brusilovsky, and R. Conejo (eds.): Adaptive Hypermedia
and Adaptive Web-based Systems. Lecture Notes in Computer Science, Vol. 2347,
476-479. Berlin Heidelberg: Springer-Verlag, 2002.
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Carlisle,
A.J., Applying the Particle Swarm Optimizer to Non-Stationary Environments, PhD
thesis, Auburn University, USA, 2002.
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Coello
Coello, C.A., Van Veldhuizen, D.A., Lamont, G.B., Evolutionary Algorithms for
Solving Multi-Objective Problems, Springer, 2002, ISBN: 0306467623.
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Chen
Z .,Li J .,Yue Y .,Gao Q .,Zhao H .and Xu Z ., A neural network online training
algorithm based on compound gradient vector. In R.I .McKay and J. Slaney (Eds
.):AI 2002, Lecture Notes in Computer Science (LNAI), vol. 2557, pp .374-384,Springer-Verlag
Berlin Heidelberg 2002.
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Fukuyama,
Y., Fundamentals of Particle Swarm Techniques. In Lee K.Y. and El-Sharkawi M.A.
(eds.), Modern Heuristic Optimization techniques with Applications to Power
Systems, chapter 5, pp. 45-51, IEEE Power Engineering Society (PES) 2002. Also
available on-line at
http://homepage2.nifty.com/fukuyama-yoshikazu/ECTutorial.htm
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Buckner,
M.A., Learning from Data with Localized Regression and Differential Evolution,
Ph.D. Thesis, University of Tennessee, Knoxville, USA, 2003.
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Tasoulis
D.K., Spyridonos P., Pavlidis N.G., Cavouras D., Ravazoula P., Nikiforidis G.
and Vrahatis M.N., Urinary bladder tumor grade diagnosis using on-line trained
neural networks, Lecture Notes in Computer Science (LNAI), 2773, October 2003,
pp.199-206.
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Chen
Z., Dong Ch., Zhou Q. and Zhang Sh., An improved compound gradient vector based
neural network on-line training algorithm P .W. H. Chung C .J .Hinde M .Ali
(eds .), IEA /AIE 2003, Lecture Notes in Computer Science, (LNAI) 2718 pp
316-325, Springer-Verlag Berlin Heidelberg 2003.
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Khosrowpour
M. (ed.), Information Technology and Organizations: Trends, Issues, Challenges
and Solutions , Idea Group Publishing, April 29, 2003 [ISBN :159140066 X ]
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Sirlantzis
K .,Algorithmic synthesis in neural network training for pattern recognition.
In Pattern Recognition and String Matching Series :Combinatorial Optimization
vol 13, D. Chen and X. Cheng (eds.), Kluwer Academic Publishers Dordrecht, pp
.703–739, 2003 [ISBN :1-4020-0953-4 ].
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Tasoulis
D.K., Vladutu L., Plagianakos V.P., Bezerianos A., and Vrahatis M.N., On-line
neural network training for automatic ischemia episode detection. In Leszek
Rutkowski, Jörg H. Siekmann, Ryszard Tadeusiewicz, and Lotfi A. Zadeh, editors,
Lecture Notes in Computer Science, 3070:1062-1068. Springer-Verlag, 2004.
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Fieldsend,
J.E., Novel Algorithms for Multi-Objective Search and their Application in
Multi-Objective Evolutionary Neural Network Training, PhD thesis, University of
Exeter, U.K, 2004.
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Mendes,
R., Population Topologies and their Influence in Particle Swarm Performance,
PhD thesis, Departamento de Informatica, Escola de Engenharia, Universidade do
Minho, Portugal, 2004.
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Krusienski,
D.J., Enhanced Structured Stochastic Global Optimization Algorithms for IIR and
Nonlinear Adaptive Filtering, PhD thesis, Department of Electrical Engineering,
The Pennsylvania State University, USA, August 2004.
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Chen
Z., Chen X., Zhang J. and Liu L., Convergence analysis of a neural network
based on generalised compound gradient vector, B. Orchard, Ch. Yang, M. Ali
(eds.): IEA /AIE 2004, Lecture Notes in Computer Science (LNAI ), vol. 3029,
pp. 1174–1183, Springer-Verlag Berlin Heidelberg, 2004.
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Petalas,
Y.G., Tasoulis, D.K., Vrahatis, M.N., Dynamic search trajectory methods for
neural network training, Lecture Notes in Artificial Intelligence, vol. 3070,
pp. 241-246, 2004.
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Vladutu
L., Computational intelligence methods on biomedical signals analysis and data
mining in medical records, PhD thesis, Department of Medical Physics School of
Medicine University of Patras, Patras, Greece, 2004.
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Zhang
X.-J., An effective design method for components made of a multiphase perfect
material, PhD thesis, Department of Mechanical Engineering, The University of
Hong Kong, Hong Kong, 2004.
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Encheva,
S., Tumin, S., Cooperative shared learning objects in an intelligent web-based
tutoring environment, Lecture Notes in
Computer Science, vol. 3675, pp. 227-234, 2005.
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Lee,
J., Jun, W., Design and implementation of a web-board system for the adaptive
school web site construction, Lecture Notes in Computer Science, vol. 3807, pp.
94-103, 2005.
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Engelbrecht,
A.P., Fundamentals of Computational Intelligence, Wiley, 2005 [ISBN:
0-470-09191-6].
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Schmitt
S., The diamond operator implementation of exact real algebraic numbers,
Lecture Notes in Computer Science, 3718, pp. 355-366, 2005.
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Schoeman,
L., Engelbrecht, A.P., A Parallel Vector-Based Particle Swarm Optimizer, in
Adaptive and Natural Computing Algorithms, Proc. International Conference on
Artificial Neural Networks and Genetic Algorithms (ICANNGA 2005), Portugal, B
.Ribeiro R.F., Albrecht A .Dobnikar D .W .Pearson and N .C. Steele (eds .),
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Anastasiadis
A, Neural network training and applications using biological data, PhD thesis,
Birkbeck College, University of London, 2006.
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Brusilovsky,
P., Sosnovsky, S., Yudelson, M., Addictive links: The motivational value of
adaptive link annotation in educational hypermedia, Lecture Notes in Computer
Science, vol. 4018, pp. 51-60, 2006.
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Bull,
S., Mabbott, A., 20000 inspections of a domain-independent open learner model
with individual and comparison views, Lecture Notes in Computer Science, vol.
4053, pp. 422-432, 2006.
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Herrera
B.M., Ribas L., dos Santos Coelho L. Nonlinear identification method of a yo-yo
system using fuzzy model and fast particle swarm optimization. In Applied Soft
Computing Technologies: The Challenge of Complexity, Ajith Abraham, Bernard de
Baets, Mario Köppen and Bertram Nickolay, (eds.), Advances in Soft Computing
Series, Springer, pp. 303-314, 2006.
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Kelly,
D., Tangney, B., Using multiple intelligence informed resources in an adaptive
system, Lecture Notes in Computer Science, vol. 4053, pp. 412-421, 2006.
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Li
J., Learning Reactive Behaviors with Constructive Neural Networks in Mobile
Robotics, PhD thesis, Orebro University, Orebro Studies in Technology 23,
Sweden 2006 [ISSN 1651-8896] [ISBN 91-7668-490-3]. Available online at:
www.diva-portal.org/diva/getDocument?urn_nbn_se_oru_diva-629-2__fulltext.pdf
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