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330 results on '"Tarantino Ernesto"'

1. Can Different Impacts of Covid-19 on Different Countries Be Explained? a Preliminary Machine Learning Experiment

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Scafuri, Umberto, Tarantino, Ernesto, Chatterjee, Prasenjit, Series Editor, Awasthi, Anjali, Series Editor, Tiwari, Manoj Kumar, Series Editor, Chakraborty, Shankar, Series Editor, Yazdani, Morteza, Series Editor, Kose, Utku, editor, Watada, Junzo, editor, Deperlioglu, Omer, editor, and Marmolejo Saucedo, Jose Antonio, editor

Published
2022
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2. Distributed Processor Load Balancing Based on Multi-objective Extremal Optimization

Author

De Falco, Ivanoe, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, 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, Montella, Raffaele, editor, Ciaramella, Angelo, editor, Fortino, Giancarlo, editor, Guerrieri, Antonio, editor, and Liotta, Antonio, editor

Published
2019
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3. Multi-Objective Extremal Optimization in Processor Load Balancing for Distributed Programs

Author

De Falco, Ivanoe, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, 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, Wyrzykowski, Roman, editor, Dongarra, Jack, editor, Deelman, Ewa, editor, and Karczewski, Konrad, editor

Published
2018
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7. A Multiobjective Evolutionary Algorithm for Personalized Tours in Street Networks

Author

De Falco, Ivanoe, Scafuri, Umberto, Tarantino, Ernesto, 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, Mora, Antonio M., editor, and Squillero, Giovanni, editor

Published
2015
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8. Parallel Extremal Optimization with Guided State Changes Applied to Load Balancing

Author

De Falco, Ivanoe, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, 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, Mora, Antonio M., editor, and Squillero, Giovanni, editor

Published
2015
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10. Extremal Optimization Applied to Task Scheduling of Distributed Java Programs

Author

Laskowski, Eryk, Tudruj, Marek, De Falco, Ivanoe, Scafuri, Umberto, Tarantino, Ernesto, Olejnik, Richard, 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, Di Chio, Cecilia, editor, Brabazon, Anthony, editor, Di Caro, Gianni A., editor, Drechsler, Rolf, editor, Farooq, Muddassar, editor, Grahl, Jörn, editor, Greenfield, Gary, editor, Prins, Christian, editor, Romero, Juan, editor, Squillero, Giovanni, editor, Tarantino, Ernesto, editor, Tettamanzi, Andrea G. B., editor, Urquhart, Neil, editor, and Uyar, A. Şima, editor

Published
2011
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11. Impact of the Topology on the Performance of Distributed Differential Evolution

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Maisto, Domenico, Scafuri, Umberto, Tarantino, Ernesto, 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, Esparcia-Alcázar, Anna I., editor, and Mora, Antonio M., editor

Published
2014
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12. Improving Extremal Optimization in Load Balancing by Local Search

Author

De Falco, Ivanoe, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, 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, Esparcia-Alcázar, Anna I., editor, and Mora, Antonio M., editor

Published
2014
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15. Adding Chaos to Differential Evolution for Range Image Registration

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Maisto, Domenico, Scafuri, Umberto, Tarantino, Ernesto, 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, and Esparcia-Alcázar, Anna I., editor

Published
2013
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16. Load Balancing in Distributed Applications Based on Extremal Optimization

Author

De Falco, Ivanoe, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, 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, and Esparcia-Alcázar, Anna I., editor

Published
2013
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17. A Model Based on Biological Invasions for Island Evolutionary Algorithms

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Maisto, Domenico, Scafuri, Umberto, Tarantino, Ernesto, 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, Hao, Jin-Kao, editor, Legrand, Pierrick, editor, Collet, Pierre, editor, Monmarché, Nicolas, editor, Lutton, Evelyne, editor, and Schoenauer, Marc, editor

Published
2012
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18. Distributed Java Programs Initial Mapping Based on Extremal Optimization

Author

Laskowski, Eryk, Tudruj, Marek, De Falco, Ivanoe, Scafuri, Umberto, Tarantino, Ernesto, Olejnik, Richard, 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, and Jónasson, Kristján, editor

Published
2012
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19. Extremal Optimization Approach Applied to Initial Mapping of Distributed Java Programs

Author

De Falco, Ivanoe, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, 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, D’Ambra, Pasqua, editor, Guarracino, Mario, editor, and Talia, Domenico, editor

Published
2010
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23. Extremal Optimization as a Viable Means for Mapping in Grids

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Maisto, Domenico, Scafuri, Umberto, Tarantino, Ernesto, 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, Giacobini, Mario, editor, Brabazon, Anthony, editor, Cagnoni, Stefano, editor, Di Caro, Gianni A., editor, Ekárt, Anikó, editor, Esparcia-Alcázar, Anna Isabel, editor, Farooq, Muddassar, editor, Fink, Andreas, editor, and Machado, Penousal, editor

Published
2009
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24. A Multiobjective Evolutionary Approach for Multisite Mapping on Grids

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Scafuri, Umberto, Tarantino, Ernesto, 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, Wyrzykowski, Roman, editor, Dongarra, Jack, editor, Karczewski, Konrad, editor, and Wasniewski, Jerzy, editor

Published
2008
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25. Satellite Image Registration by Distributed Differential Evolution

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Maisto, Domenico, Scafuri, Umberto, Tarantino, Ernesto, 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, and Giacobini, Mario, editor

Published
2007
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26. Parsimony Doesn’t Mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Maisto, Domenico, Scafuri, Umberto, Tarantino, Ernesto, 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, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ebner, Marc, editor, O’Neill, Michael, editor, Ekárt, Anikó, editor, Vanneschi, Leonardo, editor, and Esparcia-Alcázar, Anna Isabel, editor

Published
2007
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27. Multiobjective Differential Evolution for Mapping in a Grid Environment

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Scafuri, Umberto, Tarantino, Ernesto, 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, Perrott, Ronald, editor, Chapman, Barbara M., editor, Subhlok, Jaspal, editor, de Mello, Rodrigo Fernandes, editor, and Yang, Laurence T., editor

Published
2007
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28. A Genetic Programming Approach to Solomonoff’s Probabilistic Induction

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Maisto, Domenico, Tarantino, Ernesto, 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, Dough, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Collet, Pierre, editor, Tomassini, Marco, editor, Ebner, Marc, editor, Gustafson, Steven, editor, and Ekárt, Anikó, editor

Published
2006
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30. A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction.

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Koutny, Tomas, Ubl, Martin, Krcma, Michal, Scafuri, Umberto, and Tarantino, Ernesto

Subjects
EVOLUTIONARY algorithms, DATA privacy, BIOLOGICALLY inspired computing, GLUCOSE, STATISTICS, MACHINE learning, STATISTICAL models
Abstract

In this paper, we propose an innovative Federated Learning-inspired evolutionary framework. Its main novelty is that this is the first time that an Evolutionary Algorithm is employed on its own to directly perform Federated Learning activity. A further novelty resides in the fact that, differently from the other Federated Learning frameworks in the literature, ours can efficiently deal at the same time with two relevant issues in Machine Learning, i.e., data privacy and interpretability of the solutions. Our framework consists of a master/slave approach in which each slave contains local data, protecting sensible private data, and exploits an evolutionary algorithm to generate prediction models. The master shares through the slaves the locally learned models that emerge on each slave. Sharing these local models results in global models. Being that data privacy and interpretability are very significant in the medical domain, the algorithm is tested to forecast future glucose values for diabetic patients by exploiting a Grammatical Evolution algorithm. The effectiveness of this knowledge-sharing process is assessed experimentally by comparing the proposed framework with another where no exchange of local models occurs. The results show that the performance of the proposed approach is better and demonstrate the validity of its sharing process for the emergence of local models for personal diabetes management, usable as efficient global models. When further subjects not involved in the learning process are considered, the models discovered by our framework show higher generalization capability than those achieved without knowledge sharing: the improvement provided by knowledge sharing is equal to about 3.03% for precision, 1.56% for recall, 3.17% for F 1 , and 1.56% for accuracy. Moreover, statistical analysis reveals the statistical superiority of model exchange with respect to the case of no exchange taking place. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment.

Author

Ubl, Martin, Koutny, Tomas, Della Cioppa, Antonio, De Falco, Ivanoe, Tarantino, Ernesto, and Scafuri, Umberto

Subjects
INSULIN pumps, BLOOD sugar, INSULIN therapy, SIMULATED patients, DIABETES, DECISION trees
Abstract

Diabetes is a heterogeneous group of diseases that share a common trait of elevated blood glucose levels. Insulin lowers this level by promoting glucose utilization, thus avoiding short- and long-term organ damage due to the elevated blood glucose level. A patient with diabetes uses an insulin pump to dose insulin. The pump uses a controller to compute and dose the correct amount of insulin to keep blood glucose levels in a safe range. Insulin-pump controller development is an ongoing process aiming at fully closed-loop control. Controllers entering the market must be evaluated for safety. We propose an evaluation method that exploits an FDA-approved diabetic patient simulator. The method evaluates a Cartesian product of individual insulin-pump parameters with a fine degree of granularity. As this is a computationally intensive task, the simulator executes on a distributed cluster. We identify safe and risky combinations of insulin-pump parameter settings by applying the binomial model and decision tree to this product. As a result, we obtain a tool for insulin-pump settings and controller safety assessment. In this paper, we demonstrate the tool with the Low-Glucose Suspend and OpenAPS controllers. For average ± standard deviation, LGS and OpenAPS exhibited 1.7 ± 0.6% and 3.2 ± 1.8% of local extrema (i.e., good insulin-pump settings) out of all the entire Cartesian products, respectively. A continuous region around the best-discovered settings (i.e., the global extremum) of the insulin-pump settings spread across 4.0 ± 1.1% and 4.1 ± 1.3% of the Cartesian products, respectively. [ABSTRACT FROM AUTHOR]

Published
2022
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33. Multi-Objective Extremal Optimization in Processor Load Balancing for Distributed Programs

Author

Falco, Ivanoe De, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, Institute of High Performance Computing and Networking (ICAR), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Institue of Computer Science [Pologne], Polska Akademia Nauk = Polish Academy of Sciences (PAN), Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS), Consiglio Nazionale delle Ricerche [Roma] (CNR), and Olejnik, Richard

Subjects
Extremal Optimization, Multi-objective optimization, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO]Computer Science [cs], Processor load balancing, [INFO] Computer Science [cs], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-ES] Computer Science [cs]/Embedded Systems
Abstract

The paper presents a multi-objective load balancing algorithm based on Extremal Optimization in execution of distributed programs. The Extremal Optimization aims in defining task migration as a means for improving balance in loading executive processors with program tasks. In the proposed multi-objective approach three objectives relevant in processor load balancing for distributed applications are jointly optimized. These objectives include: balance in computational load of distributed processors, total volume of inter-processor communication between tasks and task migration metrics. In the proposed Extremal Optimization algorithms a special approach called Guided Search is applied in selection of a new partial solution to be improved. It is supported by some knowledge of the problem in terms of computational and communication loads influenced by task migration. The proposed algorithms are assessed by simulation experiments with distributed execution of program macro data flow graphs.

Published
2017

34. Preface

Author

Squillero, Giovanni, Sim, Kevin, Ascheid, Gerd, Bacardit, Jaume, Brabazon, Anthony, Burelli, Paolo, Cagnoni, Stefano, Coler, Matt, Cotta, Carlos, D’Andreagiovanni, Fabio, Divina, Federico, Esparcia-Alcázar, Anna I., de Vega, Francisco Fernández, Glette, Kyrre, Haasdijk, Evert, Heinerman, Jacqueline, Hidalgo, J. Ignacio, Hu, Ting, Iacca, Giovanni, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Mora Garcia, Antonio M., Schaefer, Robert, Silva, Sara, Tarantino, Ernesto, Nguyen, Trung Thanh, Tonda, Alberto, Urquhart, Neil, and Zhang, Mengjie

Published
2017

35. EvoApplications: 2017: 20th European Conference on the Applications of Evolutionary Computation, Amsterdam; Netherlands; 19-21 April 2017

Author

Squillero, Giovanni, Sim, Kevin, Ascheid, Gerd, Bacardit, Jaume, Brabazon, Anthony, Burelli, Paolo, Cagnoni, Stefano, Coler, Matt, Cotta, Carlos, D'Andreagiovanni, Fabio, Divina, Federico, Esparcia-Alcázar, Anna I., de Vega, Francisco Fernández, Glette, Kyrre, Haasdijk, Evert, Heinerman, Jacqueline, Hidalgo, J. Ignacio, Hu, Ting, Iacca, Giovanni, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Mora Garcia, Antonio M., Schaefer, Robert, Silva, Sara, Tarantino, Ernesto, Nguyen, Trung Thanh, Tonda, Alberto, Urquhart, Neil, and Zhang, Mengjie

Subjects
applications, Evolutionary computation
Abstract

Proceedings of the European Conference on the Applications of Evolutionary Computation, EvoApplications 2017; Amsterdam; Netherlands; 19 -21 April 2017

Published
2017

36. Applications of Evolutionary Computation: 20th European Conference, EvoApplications 2017, Proceedings Part II

Author

Squillero, Giovanni, Sim, Kevin, Ascheid, Gerd, Bacardit, Jaume, Brabazon, Anthony, Burelli, Paolo, Cagnoni, Stefano, Coler, Matt, Cotta, Carlos, D'Andreagiovanni, Fabio, Divina, Federico, Esparcia-Alcazar, Anna I., De Vega, Francisco Fernandez, Glette, Kyrre, Haasdijk, Evert, Heinerman, Jacqueline, Hidalgo, J. Ignacio, Hu, Ting, Iacca, Giovanni, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Mora García, Antonio M., Nguyen, Trung Thanh, Schaefer, Robert, Silva, Sara, Tarantino, Ernesto, Tonda, Alberto, Urquhart, Neil, Zhang, Mengjie, Squillero, Giovanni, Sim, Kevin, Ascheid, Gerd, Bacardit, Jaume, Brabazon, Anthony, Burelli, Paolo, Cagnoni, Stefano, Coler, Matt, Cotta, Carlos, D'Andreagiovanni, Fabio, Divina, Federico, Esparcia-Alcazar, Anna I., De Vega, Francisco Fernandez, Glette, Kyrre, Haasdijk, Evert, Heinerman, Jacqueline, Hidalgo, J. Ignacio, Hu, Ting, Iacca, Giovanni, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Mora García, Antonio M., Nguyen, Trung Thanh, Schaefer, Robert, Silva, Sara, Tarantino, Ernesto, Tonda, Alberto, Urquhart, Neil, and Zhang, Mengjie

Abstract

The two volumes LNCS 10199 and 10200 constitute the refereed conference proceedings of the 20th European Conference on the Applications of Evolutionary Computation, EvoApplications 2017, held in Amsterdam, The Netherlands, in April 2017, colocated with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented together with 26 poster papers were carefully reviewed and selected from 108 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoKNOW (knowledge incorporation in evolutionary computation), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoROBOT (evolutionary robotics), EvoSET (nature-inspired algorithms in software engineering and testing), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

Published
2017

37. Applications of evolutionary computation:19th European conference, Evoapplications 2016 Porto, Portugal, March 30 – April 1, 2016 proceedings, part II

Author

Squillero, Giovanni, Burelli, Paolo, Bacardit, Jaume, Brabazon, Anthony, Cagnoni, Stefano, Cotta, Carlos, De Falco, Ivanoe, Cioppa, Antonio Della, Divina, Federico, Eiben, A. E., Esparcia-Alcàza, Anna I., de Vega, Francisco Fernàndez, Glette, Kyrre, Haasdijk, Evert, Hidalgo, J. Ignacio, Hu, Ting, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Mora García, Antonio M., Nguyen, Trung Thanh, Schaefer, Robert, Sim, Kevin, Tarantino, Ernesto, Urquhart, Neil, and Zhang, Mengjie

Published
2016

38. Applications of evolutionary computation: 19th European conference, Evoapplications 2016 Porto, Portugal, March 30 – April 1, 2016 proceedings, part II

Author

Squillero, Giovanni, Burelli, Paolo, Bacardit, Jaume, Brabazon, Anthony, Cagnoni, Stefano, Cotta, Carlos, De Falco, Ivanoe, Cioppa, Antonio Della, Divina, Federico, Eiben, A. E., Esparcia-Alcàza, Anna I., de Vega, Francisco Fernàndez, Glette, Kyrre, Haasdijk, Evert, Hidalgo, J. Ignacio, Hu, Ting, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Mora García, Antonio M., Nguyen, Trung Thanh, Schaefer, Robert, Sim, Kevin, Tarantino, Ernesto, Urquhart, Neil, Zhang, Mengjie, Artificial intelligence, Network Institute, and Computational Intelligence

Published
2016

39. Preface

Author

Squillero, Giovanni, Bacardit, Jaume, Cagnoni, Stefano, De Falco, Ivanoe, Divina, Federico, Esparcia-Alcázar, Anna I., Glette, Kyrre, Hidalgo, J. Ignacio, Kampouridis, Michael, Mavrovouniotis, Michalis, Nguyen, Trung Thanh, Sim, Kevin, Urquhart, Neil, Burelli, Paolo, Brabazon, Anthony, Cotta, Carlos, Cioppa, Antonio Della, Eiben, A. E., de Vega, Francisco Fernández, Haasdijk, Evert, Hu, Ting, Kaufmann, Paul, Mora Garcia, Antonio M., Schaefer, Robert, Tarantino, Ernesto, Zhang, Mengjie, Artificial intelligence, Physics of Living Systems, Computational Intelligence, and Network Institute

Published
2016

40. Applications of evolutionary computation

Author

Mora, Antonio M., Squillero, Giovanni, Agapitos, Alexandros, Burelli, Paolo, Bush, William S., Cagnoni, Stefano, Cotta, Carlos, De Falco, Ivanoe, Cioppa, Antonio Della, Divina, Federico, Eiben, A. E., Esparcia-Alcázar, Anna I., de Vega, Francisco Fernández, Glette, Kyrre, Haasdijk, Evert, Hidalgo, J. Ignacio, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Nguyen, Trung Thanh, Schaefer, Robert, Sim, Kevin, Tarantino, Ernesto, Urquhart, Neil, Zhang, Mengjie, Vrije Universiteit Amsterdam, Artificial intelligence, Computational Intelligence, Network Institute, and Physics of Living Systems

Published
2015

41. Improving Extremal Optimization in Load Balancing by Local Search

Author

Falco, Ivanoe De, Laskowski, Eryk, Olejnik, Richard, Scafuri, Umberto, Tarantino, Ernesto, Tudruj, Marek, Institute of High Performance Computing and Networking (ICAR), Consiglio Nazionale delle Ricerche [Roma] (CNR), Institute of Computer Science [Warszawa], Polska Akademia Nauk = Polish Academy of Sciences (PAN), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Polish-Japanese Institute of Information Technology (PJIIT), and National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)

Subjects
Extremal optimization, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Distributed program design, Load balancing
Abstract

International audience; The paper concerns the use of Extremal Optimization (EO) technique in dynamic load balancing for optimized execution of distributed programs. EO approach is used to periodically detect the best candidates for task migration leading to balanced execution. To improve the quality of load balancing and decrease time complexity of the algorithms, we have improved EO by a local search of the best computing node to receive migrating tasks. The improved guided EO algorithm assumes a two-step stochastic selection based on two separate fitness functions. The functions are based on specific program models which estimate relations between the programs and the executive hardware. The proposed load balancing algorithm is compared against a standard EO-based algorithm with random placement of migrated tasks and a classic genetic algorithm. The algorithm is assessed by experiments with simulated load balancing of distributed program graphs and analysis of the outcome of the discussed approaches.

Published
2014

42. Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Proceedings Part II

Author

Squillero, Giovanni, Burelli, Paolo, Bacardit, Jaume, Brabazon, Anthony, Cagnoni, Stefano, Cotta, Carlos, De Falco, Ivanoe, Della Cioppa, Antonio, Divina, Federico, Eiben, A.E., Esparcia-Alcazar, Anna I., De Vega, Francisco Fernandez, Glette, Kyrre, Haasdijk, Evert, Hidalgo, J. Ignacio, Hu, Ting, Kampouridis, Michael, Sim, Kevin, Tarantino, Ernesto, Urquhart, Neil, Zhang, Mengjie, Squillero, Giovanni, Burelli, Paolo, Bacardit, Jaume, Brabazon, Anthony, Cagnoni, Stefano, Cotta, Carlos, De Falco, Ivanoe, Della Cioppa, Antonio, Divina, Federico, Eiben, A.E., Esparcia-Alcazar, Anna I., De Vega, Francisco Fernandez, Glette, Kyrre, Haasdijk, Evert, Hidalgo, J. Ignacio, Hu, Ting, Kampouridis, Michael, Sim, Kevin, Tarantino, Ernesto, Urquhart, Neil, and Zhang, Mengjie

Abstract

The two volumes LNCS 9597 and 9598 constitute the refereed conference proceedings of the 19th European Conference on the Applications of Evolutionary Computation, EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 57 revised full papers presented together with 17 poster papers were carefully reviewed and selected from 115 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

Published
2016

43. Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings

Author

Mora, Antonio, Squillero, Giovanni, Agapitos, Alexandros, Burelli, Paolo, Bush, William, Cagnoni, Stefano, Cotta, Carlos, De Falco, Ivanoe, Della Cioppa, Antonio, Divina, Federico, Eiben, A.E., Esparcia-Alcazar, Anna I., Fernandez de Vega, Francisco, Glette, Kyrre, Haasdijk, Evert, Hidalgo, J. Ignacio, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Nguyen, Trung Thanh, Schaefer, Robert, Sim, Kevin, Tarantino, Ernesto, Urquhart, Neil, Zhang, Mengjie, Mora, Antonio, Squillero, Giovanni, Agapitos, Alexandros, Burelli, Paolo, Bush, William, Cagnoni, Stefano, Cotta, Carlos, De Falco, Ivanoe, Della Cioppa, Antonio, Divina, Federico, Eiben, A.E., Esparcia-Alcazar, Anna I., Fernandez de Vega, Francisco, Glette, Kyrre, Haasdijk, Evert, Hidalgo, J. Ignacio, Kampouridis, Michael, Kaufmann, Paul, Mavrovouniotis, Michalis, Nguyen, Trung Thanh, Schaefer, Robert, Sim, Kevin, Tarantino, Ernesto, Urquhart, Neil, and Zhang, Mengjie

Abstract

This book constitutes the refereed conference proceedings of the 18th International Conference on the Applications of Evolutionary Computation, EvoApplications 2015, held in Copenhagen, Spain, in April 2015, colocated with the Evo 2015 events EuroGP, EvoCOP, and EvoMUSART. The 72 revised full papers presented were carefully reviewed and selected from 125 submissions. EvoApplications 2015 consisted of the following 13 tracks: EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary computation in robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

Published
2015

45. CTRNN parameter learning using Differential Evolution

Author

De Falco, Ivanoe, Della Cioppa, Antonio, Donnarumma, Francesco, Maisto, Domenico, Prevete, Roberto, Tarantino, Ernesto, Ghallab, M, Spyropoulos, CD, Fakotakis, N, et al, DE FALCO, Ivan, DELLA CIOPPA, Andrea, Donnarumma, Francesco, Maisto, D, Prevete, Roberto, and Tarantino, E.

Subjects
Genetic Algorithms, Dynamical System, Differential Evolution, Ctrnn, Dynamical Systems
Abstract

Target behaviours can be achieved by finding suitable parameters for Continuous Time Recurrent Neural Networks (CTRNNs) used as agent control systems. Differential Evolution (DE) has been deployed to search parameter space of CTRNNs and overcome granularity, boundedness and blocking limitations. In this paper we provide initial support for DE in the context of two sample learning problems.

Published
2008

47. Automatic Classification of Handsegmented Image Parts using Differential Evolution

Author

De Falco Ivanoe, Tarantino Ernesto, and Della Cioppa Antonio

Subjects
centroids, classification, multi-class database, recognition of image parts, Differential evolution
Abstract

Differential Evolution, a version of an Evolutionary Algorithm, is used to perform automatic classification of handsegmented image parts collected in a seven–class database. Our idea is to exploit it to find the positions of the class centroids in the search space such that for any class the average distance of instances belonging to that class from the relative class centroid is minimized. The performance of the resulting best individual is computed in terms of error rate on the testing set. Then, such a performance is compared against those of other ten classification techniques well known in literature. Results show the effectiveness of the approach in solving the classification task.

Published
2006

49. Inductive Inference on Noisy Data by Genetic Programming

Author

De Falco Ivanoe, Della Cioppa Antonio, Maisto Domenico, and Tarantino Ernesto

Subjects
Solomonoff's induction theory, Genetic Programming, inductive inference, symbolic regression
Abstract

In this paper a Genetic Programming algorithm based on Solomonoff probabilistic induction concepts is designed and used to face an Inductive Inference task, i.e. symbolic regression. To this aim, Schwefel function is dressed with increasing levels of additive noise and the algorithm is employed to denoise the resulting function and recover the starting one. The proposed algorithm is compared against a classical parsimony-based GP. The earliest results seem to show a superiority of the Solomonoff-based approach.

Published
2006

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