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288 results on '"MAGOULAS, GEORGE D."'

1. Predicting Seriousness of Injury in a Traffic Accident: A New Imbalanced Dataset and Benchmark

Author

Lagias, Paschalis, Magoulas, George D., Prifti, Ylli, and Provetti, Alessandro

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, I.2.6
Abstract

The paper introduces a new dataset to assess the performance of machine learning algorithms in the prediction of the seriousness of injury in a traffic accident. The dataset is created by aggregating publicly available datasets from the UK Department for Transport, which are drastically imbalanced with missing attributes sometimes approaching 50\% of the overall data dimensionality. The paper presents the data analysis pipeline starting from the publicly available data of road traffic accidents and ending with predictors of possible injuries and their degree of severity. It addresses the huge incompleteness of public data with a MissForest model. The paper also introduces two baseline approaches to create injury predictors: a supervised artificial neural network and a reinforcement learning model. The dataset can potentially stimulate diverse aspects of machine learning research on imbalanced datasets and the two approaches can be used as baseline references when researchers test more advanced learning algorithms in this area.

Published
2022

3. Transfer Learning and Magnetic Resonance Imaging Techniques for the Deep Neural Network-Based Diagnosis of Early Cognitive Decline and Dementia

Author

Herzog, Nitsa J., Magoulas, George D., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chicco, Davide, editor, Facchiano, Angelo, editor, Tavazzi, Erica, editor, Longato, Enrico, editor, Vettoretti, Martina, editor, Bernasconi, Anna, editor, Avesani, Simone, editor, and Cazzaniga, Paolo, editor

Published
2022
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8. Deep Incremental Boosting

Author

Mosca, Alan and Magoulas, George D

Subjects
Statistics - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Learning
Abstract

This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training time and improves generalisation. We draw inspiration from Transfer of Learning approaches to reduce the start-up time to training each incremental Ensemble member. We show a set of experiments that outlines some preliminary results on some common Deep Learning datasets and discuss the potential improvements Deep Incremental Boosting brings to traditional Ensemble methods in Deep Learning.

Published
2017

12. Adapting Resilient Propagation for Deep Learning

Author

Mosca, Alan and Magoulas, George D.

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Learning, Statistics - Machine Learning
Abstract

The Resilient Propagation (Rprop) algorithm has been very popular for backpropagation training of multilayer feed-forward neural networks in various applications. The standard Rprop however encounters difficulties in the context of deep neural networks as typically happens with gradient-based learning algorithms. In this paper, we propose a modification of the Rprop that combines standard Rprop steps with a special drop out technique. We apply the method for training Deep Neural Networks as standalone components and in ensemble formulations. Results on the MNIST dataset show that the proposed modification alleviates standard Rprop's problems demonstrating improved learning speed and accuracy., Comment: Published in the proceedings of the UK workshop on Computational Intelligence 2015 (UKCI)

Published
2015

13. Transfer learning approach for financial applications

Author

Stamate, Cosmin, Magoulas, George D., and Thomas, Michael S. C.

Subjects
Computer Science - Neural and Evolutionary Computing
Abstract

Artificial neural networks learn how to solve new problems through a computationally intense and time consuming process. One way to reduce the amount of time required is to inject preexisting knowledge into the network. To make use of past knowledge, we can take advantage of techniques that transfer the knowledge learned from one task, and reuse it on another (sometimes unrelated) task. In this paper we propose a novel selective breeding technique that extends the transfer learning with behavioural genetics approach proposed by Kohli, Magoulas and Thomas (2013), and evaluate its performance on financial data. Numerical evidence demonstrates the credibility of the new approach. We provide insights on the operation of transfer learning and highlight the benefits of using behavioural principles and selective breeding when tackling a set of diverse financial applications problems.

Published
2015

14. Challenging the Alignment of Learning Design Tools with HE Lecturers’ Learning Design Practice

Author

Celik, Dilek, Magoulas, George D., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Scheffel, Maren, editor, Broisin, Julien, editor, Pammer-Schindler, Viktoria, editor, Ioannou, Andri, editor, and Schneider, Jan, editor

Published
2019
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18. Boosted Residual Networks

Author

Mosca, Alan, Magoulas, George D., Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Boracchi, Giacomo, editor, Iliadis, Lazaros, editor, Jayne, Chrisina, editor, and Likas, Aristidis, editor

Published
2017
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19. An Architecture for Smart Lifelong Learning Design

Author

Karoudis, Konstantinos, Magoulas, George D., Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Popescu, Elvira, editor, Khribi, Mohamed Koutheair, editor, and Sampson, Demetrios G., editor

Published
2017
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21. Evolving Stochastic Learning Algorithm Based on Tsallis Entropic Index

Author

Anastasiadis, Aristoklis D. and Magoulas, George D.

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence
Abstract

In this paper, inspired from our previous algorithm, which was based on the theory of Tsallis statistical mechanics, we develop a new evolving stochastic learning algorithm for neural networks. The new algorithm combines deterministic and stochastic search steps by employing a different adaptive stepsize for each network weight, and applies a form of noise that is characterized by the nonextensive entropic index q, regulated by a weight decay term. The behavior of the learning algorithm can be made more stochastic or deterministic depending on the trade off between the temperature T and the q values. This is achieved by introducing a formula that defines a time--dependent relationship between these two important learning parameters. Our experimental study verifies that there are indeed improvements in the convergence speed of this new evolving stochastic learning algorithm, which makes learning faster than using the original Hybrid Learning Scheme (HLS). In addition, experiments are conducted to explore the influence of the entropic index q and temperature T on the convergence speed and stability of the proposed method., Comment: 12 pages, 11 figures, journal

Published
2005
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22. Design and Evaluation of a Case-Based System for Modelling Exploratory Learning Behavior of Math Generalization

Author

Cocea, Mihaela and Magoulas, George D.

Abstract

Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a variety of learner approaches for constructing models and makes modelling of learner behavior a challenging task. To address this issue, we propose a learner modelling mechanism for monitoring learners' actions when constructing/exploring models by modelling sequences of actions reflecting different strategies in solving a task. This is based on a modified version of case-based reasoning for problems with multiple solutions. In our formulation, approaches to explore the task are represented as sequences of simple cases linked by temporal and dependency relations, which are mapped to the learners' behavior in the system by means of appropriate similarity metrics. This paper presents the development and validation of the modelling mechanism. The model was validated in the context of an ELE for mathematical generalisation using data from classroom sessions and pedagogically-driven learning scenarios.

Published
2017
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24. Approaches to Design for Learning

Author

Celik, Dilek, Magoulas, George D., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chiu, Dickson K.W., editor, Marenzi, Ivana, editor, Nanni, Umberto, editor, Spaniol, Marc, editor, and Temperini, Marco, editor

Published
2016
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25. A Review, Timeline, and Categorization of Learning Design Tools

Author

Celik, Dilek, Magoulas, George D., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chiu, Dickson K.W., editor, Marenzi, Ivana, editor, Nanni, Umberto, editor, Spaniol, Marc, editor, and Temperini, Marco, editor

Published
2016
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38. Context-Dependent Feedback Prioritisation in Exploratory Learning Revisited

Author

Cocea, Mihaela, Magoulas, George D., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Konstan, Joseph A., editor, Conejo, Ricardo, editor, Marzo, José L., editor, and Oliver, Nuria, editor

Published
2011
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40. Adaptive Modelling of Users’ Strategies in Exploratory Learning Using Case-Based Reasoning

Author

Cocea, Mihaela, Gutierrez-Santos, Sergio, Magoulas, George D., Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Goebel, Randy, Siekmann, Jörg, Wahlster, Wolfgang, Setchi, Rossitza, editor, Jordanov, Ivan, editor, Howlett, Robert J., editor, and Jain, Lakhmi C., editor

Published
2010
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41. Group Formation for Collaboration in Exploratory Learning Using Group Technology Techniques

Author

Cocea, Mihaela, Magoulas, George D., Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Goebel, Randy, Siekmann, Jörg, Wahlster, Wolfgang, Setchi, Rossitza, editor, Jordanov, Ivan, editor, Howlett, Robert J., editor, and Jain, Lakhmi C., editor

Published
2010
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43. Searching for 'People Like Me' in a Lifelong Learning System

Author

Van Labeke, Nicolas, Magoulas, George D., Poulovassilis, Alexandra, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Cress, Ulrike, editor, Dimitrova, Vania, editor, and Specht, Marcus, editor

Published
2009
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46. Adaptive Self-scaling Non-monotone BFGS Training Algorithm for Recurrent Neural Networks

Author

Peng, Chun-Cheng, Magoulas, George D., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, de Sá, Joaquim Marques, editor, Alexandre, Luís A., editor, Duch, Włodzisław, editor, and Mandic, Danilo, editor

Published
2007
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48. A Personalised Interface for Web Directories Based on Cognitive Styles

Author

Magoulas, George D., Chen, Sherry Y., Dimakopoulos, Dionisios, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Stary, Christian, editor, and Stephanidis, Constantine, editor

Published
2004
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