Publications

Selected publications of IDEAL’s members since joining the lab

Books
1. Minis, I., V. Zeimpekis, G. Dounias, and N. Ampazis (2011). Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods. pp. 1-338. IGI Global.

Chapters in Books

1. Ampazis, N. (2012). “A Computational Intelligence Approach to Supply Chain Demand Forecasting (Revisited)”. In: Machine Learning: Concepts, Methodologies, Tools and Applications. Ed. by I. M. Association. Hershey-PA, USA: IGI Global, pp.1551–1565.
2. Ampazis, N. (2011). “A Computational Intelligence Approach to Supply Chain Demand Forecasting”. In: Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods. Ed. by I. Minis, V. Zeimpekis, G. Dounias, and N. Ampazis. Hershey-PA, USA: IGI Global, pp.110–124.
3. Ampazis, N. (2010). “Large Scale Problem Solving with Neural Networks: The Netfiix Prize Case”. In: Lecture Notes in Computer Science. Ed. by K. Diamantaras, D. Wlodek, and L. S. Iliadis. Vol. 6354. Springer Berlin Heidelberg, pp.429– 434.
4. Ampazis, N. and N. D. Alexopoulos (2010). “Prediction of Aircraft Aluminum Alloys Tensile Mechanical Properties Degradation Using Support Vector Machines”. In: Artificial Intelligence: Theories, Models and Applications. Ed. by S. Konstantopoulos, S. Perantonis, V. Karkaletsis, C. Spyropoulos, and G. Vouros. Vol. 6040. Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp.9–18.
5. Lalas, S., N. Ampazis, A. Tsakonas, G. Dounias, and K. Vemmos (2008). “Modeling Stroke Diagnosis with the Use of Intelligent Techniques”. In: Artificial Intelligence: Theories, Models and Applications. Ed. by J. Darzentas, G. Vouros, S. Vosinakis, and A. Arnellos. Vol. 5138. Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp.352–358.
6. Minis, I. and N. Ampazis (2006). “Applications of Neural Networks in Supply Chain Management”. In: Handbook of Research on Nature Inspired Computing for Economics and Management – Volume 2. Ed. by J.-P. Rennard. Hershey-PA, USA: Idea Group Reference, pp.589–607.
7. Ampazis, N., G. Dounias, and J. Jantzen (2004). “Pap-Smear Classification Using Efficient Second Order Neural Network Training Algorithms”. In: Methods and Applications of Artificial Intelligence. Ed. by G. A. Vouros and T. Panayiotopoulos. Vol. 3025. Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp.230–245.

Refereed Journal Articles

1. Ampazis, N. (2014). Forecasting Demand in Supply Chain Using Machine Learning Algorithms. Journal of Artificial Life Research accepted.
2. Ampazis, N. and T. Emmanouilidis (2014). FALCON: A Matrix Factorization Framework for Recommender Systems Using Constrained Optimization. Intelligent Decision Technologies – Special issue on Advances in Recommender Systems, accepted.
3. Ampazis, N., S. J. Perantonis, and D. Drivaliaris (2014). Improved Jacobian Eigenanalysis Scheme for Accelerating Learning in Feedforward Neural Networks. Cognitive Computation, accepted.
4. Ampazis, N. and S. J. Perantonis (2013). An Efficient Constrained Learning Algorithm for Stable 2D IIR Filter Factor- ization. Advances in Artificial Neural Systems 2013.
5. Tsourougianni, E. and N. Ampazis (2013). Recommending Who to Follow on Twitter Based on Tweet Contents and Social Connections. Social Networking 2 (4), 165–173.
6. Minis, I., N. Ampazis, and K. Mamasis (2007). Efficient real time management of goods distribution to clustered clients. International Journal of Integrated Supply Management 3(3), 211–227.
7. Dounias, G., B. Bjerregaard, J. Jantzen, A. Tsakonas, N. Ampazis, G. Panagi, and E. Panourgias (2006). Automated identification of cancerous smears using various competitive intelligent techniques. Oncol Rep 15, 1001–1006.
8. Ampazis, N. and I. Minis (2004). Design of cellular manufacturing systems using Latent Semantic Indexing and Self Organizing Maps. Computational Management Science 1(3-4), 275–292.

Refereed Conference Proceedings -Full paper reviewed

1. Ampazis, N. (2010). Large scale problem solving with neural networks: The Netflix prize case. In: Proceedings of the 20th international conference on Artificial neural networks: Part III. ICANN’10. Thessaloniki, Greece, pp.429–434.
2. Ampazis, N. and N. D. Alexopoulos (2010). Prediction of aircraft aluminum alloys tensile mechanical properties degradation using support vector machines. In: Proceedings of the 6th Hellenic conference on Artificial Intelligence: Theories, models and applications. SETN’10. Athens, Greece, pp.9–18.
3. Ampazis, N. (2008). Collaborative Filtering via Concept Decomposition on the Netflix Dataset. In: Proceedings of the 18th IEEE European Conference on Artificial Intelligence. ECAI’08. Patras, Greece, pp.26–30.
4. Lalas, S., N. Ampazis, A. Tsakonas, G. Dounias, and K. Vemmos (2008). Modeling Stroke Diagnosis with the Use of Intelligent Techniques. In: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications. SETN ’08. Syros, Greece, pp.352–358.
5. Ampazis, N., H. Iakovaki, and G. Dounias (2007). Author Identification of E-mail Messages with OLMAM Trained Feedforward Neural Networks. In: Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence. ICTAI’07. Patras, Greece, pp.413–417.
6. Tsakonas, A., N. Ampazis, and G. Dounias (2006). Towards a Comprehensible and Accurate Credit Management Model: Application of Four Computational Intelligence Methodologies. In: International Symposium on Evolving Fuzzy Systems, 2006. Lake District, UK, pp.295–299.
7. Ampazis, N. and H. Iakovaki (2004). Cross-language information retrieval using latent semantic indexing and self- organizing maps. In: Proceedings of IEEE International Joint Conference on Neural Networks. Vol. 1. Budapest, Hungary.
8. Ampazis, N., G. Dounias, and J. Jantzen (2004). Efficient second order neural network training algorithms for the construction of a pap-smear classifier. In: Proceedings of the 4th Hellenic conference on Artificial Intelligence: theories, models and applications. SETN’04. Samos, Greece.
9. Panagi, G., B. Bjerregaard, J. Jantzen, N. Ampazis, A. Tsakonas, E. Panourgias, and G. Dounias (2004). A comparison among different intelligent techniques for the automated identification of cancerous smears. In: 9th World Congress on Advances in Oncology. Crete, Greece.

Refereed Conference Proceedings – Abstract reviewed

1. Minis, I., C. Mamasis, and N. Ampazis (2005). Real-time Distribution Management Models. In: Euro XX 20th Euro- pean Conference on Operational Research. Rhodes, Greece.
2. Ampazis, N. and I. Minis (2003). SOM Clustering Manufacturing Application. In: Proceeding of the Computational Management Science Conference. Crete, Greece.

Submitted Papers

1. Ampazis, N. and T. Emmanouilidis (2014). A Matrix Factorization Technique for Efficient Recommendations in Social Networks Using Constrained Optimization. Journal of Machine Learning Research submitted.
2. Eleftheriadou, T., N. Ampazis, V. Androvitsaneas, I. Gonos, G. Dounias, and I. Stathopulos (2014). Ground Resistance Estimation Using Feed-forward Neural Networks, Linear Regression and Feature Selection Models. In: 8th Hellenic conference on Artificial Intelligence: theories, models and applications. submitted.
3. Sideratos, I., A. Platis, V. Koutras, and N. Ampazis (2014). Reliability analysis of a two-stage Goel-Okumoto and Yamada S-shaped model. In: Dependability and Complex Systems DepCoS-RELCOMEX 2014. submitted.

Invited Talks

1. Ampazis, N. (Mar. 2013). From Startup Idea to Execution: Mind the Gap. Business Week 2013, The American College of Greece. Athens, Greece.
2. Ampazis, N. (May 2010). Deploying an Ubuntu Enterprise Cloud (Live Demonstration). ELLAK 2010 Conference, National Technical University of Athens. Athens, Greece.
3. Ampazis, N. (Apr. 2010). Private clouds for research and education using open source tools. FOSSCOMM 2010. Thessaloniki, Greece.
4. Ampazis, N. (June 2009). Data Mining: Το Πρόβλημα, τα Εργαλεία Ανοιχτού Λογισμικού, οι Εφαρμογές και η Υπόσχεση. ELLAK 2009 Conference, National Technical University of Athens. Athens, Greece.
5. Ampazis, N. (May 2009). Feeds 2.0: A Personalized Web 2.0 RSS Aggregator. Open Coffee Athens XXII. Athens, Greece.
6. Ampazis, N. (Sept. 2006). The Future of RSS: Creating Intelligent RSS Feeds. Online Information Conference 2006, Olympia Grand Hall. London, UK.
7. Ampazis, N. (2002-today). A number of invited talks (more than 10) to Greek organizations and companies.