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  2024 (1)
Optimal design of vaccination policies: A case study for Newfoundland and Labrador. Khoshbakhtian, F.; Validi, H.; Ventresca, M.; and Aleman, D. M. Oper. Res. Lett., 55: 107140. 2024.
Optimal design of vaccination policies: A case study for Newfoundland and Labrador. [link]Link   Optimal design of vaccination policies: A case study for Newfoundland and Labrador. [link]Paper   link   bibtex  
  2022 (1)
Identifying the source of an epidemic using particle swarm optimization. MaGee, J.; Arora, V.; and Ventresca, M. In Fieldsend, J. E.; and Wagner, M., editor(s), GECCO, pages 1237-1244, 2022. ACM
Identifying the source of an epidemic using particle swarm optimization. [link]Link   Identifying the source of an epidemic using particle swarm optimization. [link]Paper   link   bibtex  
  2021 (2)
Supervised Link Weight Prediction Using Node Metadata. Mori, L.; Ventresca, M.; and Pujol, T. A. In Benito, R. M.; Cherifi, C.; Cherifi, H.; Moro, E.; Rocha, L. M.; and Sales-Pardo, M., editor(s), COMPLEX NETWORKS, volume 1016, of Studies in Computational Intelligence, pages 496-507, 2021. Springer
Supervised Link Weight Prediction Using Node Metadata. [link]Link   Supervised Link Weight Prediction Using Node Metadata. [link]Paper   link   bibtex  
A Graph-Based Ant Algorithm for the Winner Determination Problem in Combinatorial Auctions. Ray, A.; Ventresca, M.; and Kannan, K. N. Inf. Syst. Res., 32(4): 1099-1114. 2021.
A Graph-Based Ant Algorithm for the Winner Determination Problem in Combinatorial Auctions. [link]Link   A Graph-Based Ant Algorithm for the Winner Determination Problem in Combinatorial Auctions. [link]Paper   link   bibtex  
  2020 (1)
Improving neighbor-based collaborative filtering by using a hybrid similarity measurement. Wang, D.; Yih, Y.; and Ventresca, M. Expert Syst. Appl., 160: 113651. 2020.
Improving neighbor-based collaborative filtering by using a hybrid similarity measurement. [link]Link   Improving neighbor-based collaborative filtering by using a hybrid similarity measurement. [link]Paper   link   bibtex  
  2019 (1)
Multiple traveling salesman problem with drones: Mathematical model and heuristic approach. Kitjacharoenchai, P.; Ventresca, M.; Moshref-Javadi, M.; Lee, S.; Tanchoco, J. M. A.; and Brunese, P. A. Comput. Ind. Eng., 129: 14-30. 2019.
Multiple traveling salesman problem with drones: Mathematical model and heuristic approach. [link]Link   Multiple traveling salesman problem with drones: Mathematical model and heuristic approach. [link]Paper   link   bibtex  
  2018 (6)
New Multiobjective Optimization Approach to Rehabilitate and Maintain Sewer Networks Based on Whole Lifecycle Behavior. Altarabsheh, A.; Kandil, A.; and Ventresca, M. J. Comput. Civ. Eng., 32(1). 2018.
New Multiobjective Optimization Approach to Rehabilitate and Maintain Sewer Networks Based on Whole Lifecycle Behavior. [link]Link   New Multiobjective Optimization Approach to Rehabilitate and Maintain Sewer Networks Based on Whole Lifecycle Behavior. [link]Paper   link   bibtex  
New Approach for Critical Pipe Prioritization in Wastewater Asset Management Planning. Altarabsheh, A.; Ventresca, M.; and Kandil, A. J. Comput. Civ. Eng., 32(5). 2018.
New Approach for Critical Pipe Prioritization in Wastewater Asset Management Planning. [link]Link   New Approach for Critical Pipe Prioritization in Wastewater Asset Management Planning. [link]Paper   link   bibtex  
Evaluating the Natural Variability in Generative Models for Complex Networks. Arora, V.; and Ventresca, M. In Aiello, L. M.; Cherifi, C.; Cherifi, H.; Lambiotte, R.; Lió, P.; and Rocha, L. M., editor(s), COMPLEX NETWORKS (1), volume 812, of Studies in Computational Intelligence, pages 743-754, 2018. Springer
Evaluating the Natural Variability in Generative Models for Complex Networks. [link]Link   Evaluating the Natural Variability in Generative Models for Complex Networks. [link]Paper   link   bibtex  
A Mechanism Design Approach to Blockchain Protocols. Ray, A.; Ventresca, M.; and Wan, H. In iThings/GreenCom/CPSCom/SmartData, pages 1603-1608, 2018. IEEE
A Mechanism Design Approach to Blockchain Protocols. [link]Link   A Mechanism Design Approach to Blockchain Protocols. [link]Paper   link   bibtex  
Using Algorithmic Complexity to Differentiate Cognitive States in fMRI. Ventresca, M. In Aiello, L. M.; Cherifi, C.; Cherifi, H.; Lambiotte, R.; Lió, P.; and Rocha, L. M., editor(s), COMPLEX NETWORKS (2), volume 813, of Studies in Computational Intelligence, pages 663-674, 2018. Springer
Using Algorithmic Complexity to Differentiate Cognitive States in fMRI. [link]Link   Using Algorithmic Complexity to Differentiate Cognitive States in fMRI. [link]Paper   link   bibtex  
An Ant Colony Approach for the Winner Determination Problem. Ray, A.; and Ventresca, M. In Liefooghe, A.; and López-Ibáñez, M., editor(s), EvoCOP, volume 10782, of Lecture Notes in Computer Science, pages 174-188, 2018. Springer
An Ant Colony Approach for the Winner Determination Problem. [link]Link   An Ant Colony Approach for the Winner Determination Problem. [link]Paper   link   bibtex  
  2017 (3)
Dynamic Generative Model of the Human Brain in Resting-State. Guo, D.; Arora, V.; Amico, E.; Goñi, J.; and Ventresca, M. In Cherifi, C.; Cherifi, H.; Karsai, M.; and Musolesi, M., editor(s), COMPLEX NETWORKS, volume 689, of Studies in Computational Intelligence, pages 1271-1283, 2017. Springer
Dynamic Generative Model of the Human Brain in Resting-State. [link]Link   Dynamic Generative Model of the Human Brain in Resting-State. [link]Paper   link   bibtex  
Action-Based Model for Topologically Resilient Supply Networks. Arora, V.; and Ventresca, M. In Cherifi, C.; Cherifi, H.; Karsai, M.; and Musolesi, M., editor(s), COMPLEX NETWORKS, volume 689, of Studies in Computational Intelligence, pages 658-669, 2017. Springer
Action-Based Model for Topologically Resilient Supply Networks. [link]Link   Action-Based Model for Topologically Resilient Supply Networks. [link]Paper   link   bibtex  
Attacking Unexplored Networks - The Probe-and-Attack Problem. Chong, B. H.; and Ventresca, M. In Cherifi, C.; Cherifi, H.; Karsai, M.; and Musolesi, M., editor(s), COMPLEX NETWORKS, volume 689, of Studies in Computational Intelligence, pages 692-703, 2017. Springer
Attacking Unexplored Networks - The Probe-and-Attack Problem. [link]Link   Attacking Unexplored Networks - The Probe-and-Attack Problem. [link]Paper   link   bibtex  
  2016 (1)
A Multi-objective Optimization Approach for Generating Complex Networks. Arora, V.; and Ventresca, M. In Friedrich, T.; Neumann, F.; and Sutton, A. M., editor(s), GECCO (Companion), pages 15-16, 2016. ACM
A Multi-objective Optimization Approach for Generating Complex Networks. [link]Link   A Multi-objective Optimization Approach for Generating Complex Networks. [link]Paper   link   bibtex  
  2015 (2)
Investigating Fitness Measures for the Automatic Construction of Graph Models. Harrison, K. R.; Ventresca, M.; and Ombuki-Berman, B. M. In Mora, A. M.; and Squillero, G., editor(s), EvoApplications, volume 9028, of Lecture Notes in Computer Science, pages 189-200, 2015. Springer
Investigating Fitness Measures for the Automatic Construction of Graph Models. [link]Link   Investigating Fitness Measures for the Automatic Construction of Graph Models. [link]Paper   link   bibtex  
An Experimental Evaluation of Multi-objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks. Ventresca, M.; Harrison, K. R.; and Ombuki-Berman, B. M. In Mora, A. M.; and Squillero, G., editor(s), EvoApplications, volume 9028, of Lecture Notes in Computer Science, pages 164-176, 2015. Springer
An Experimental Evaluation of Multi-objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks. [link]Link   An Experimental Evaluation of Multi-objective Evolutionary Algorithms for Detecting Critical Nodes in Complex Networks. [link]Paper   link   bibtex  
  2014 (5)
Genetic Programming for the Automatic Inference of Graph Models for Complex Networks. Bailey, A.; Ventresca, M.; and Ombuki-Berman, B. M. IEEE Trans. Evol. Comput., 18(3): 405-419. 2014.
Genetic Programming for the Automatic Inference of Graph Models for Complex Networks. [link]Link   Genetic Programming for the Automatic Inference of Graph Models for Complex Networks. [link]Paper   link   bibtex  
A randomized algorithm with local search for containment of pandemic disease spread. Ventresca, M.; and Aleman, D. M. Comput. Oper. Res., 48: 11-19. 2014.
A randomized algorithm with local search for containment of pandemic disease spread. [link]Link   A randomized algorithm with local search for containment of pandemic disease spread. [link]Paper   link   bibtex  
Network robustness versus multi-strategy sequential attack. Ventresca, M.; and Aleman, D. Journal of Complex Networks,cnu010+. 05 2014.
Network robustness versus multi-strategy sequential attack [link]Paper   doi   link   bibtex   abstract  
A Fast Greedy Algorithm for the Critical Node Detection Problem. Ventresca, M.; and Aleman, D. M. In Zhang, Z.; Wu, L.; Xu, W.; and Du, D., editor(s), COCOA, volume 8881, of Lecture Notes in Computer Science, pages 603-612, 2014. Springer
A Fast Greedy Algorithm for the Critical Node Detection Problem. [link]Link   A Fast Greedy Algorithm for the Critical Node Detection Problem. [link]Paper   link   bibtex  
A Region Growing Algorithm for Detecting Critical Nodes. Ventresca, M.; and Aleman, D. M. In Zhang, Z.; Wu, L.; Xu, W.; and Du, D., editor(s), COCOA, volume 8881, of Lecture Notes in Computer Science, pages 593-602, 2014. Springer
A Region Growing Algorithm for Detecting Critical Nodes. [link]Link   A Region Growing Algorithm for Detecting Critical Nodes. [link]Paper   link   bibtex  
  2013 (2)
Automatic inference of hierarchical graph models using genetic programming with an application to cortical networks. Bailey, A.; Ombuki-Berman, B. M.; and Ventresca, M. In Blum, C.; and Alba, E., editor(s), GECCO, pages 893-900, 2013. ACM
Automatic inference of hierarchical graph models using genetic programming with an application to cortical networks. [link]Link   Automatic inference of hierarchical graph models using genetic programming with an application to cortical networks. [link]Paper   link   bibtex  
Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures. Ventresca, M.; Ombuki-Berman, B. M.; and Runka, A. In Middendorf, M.; and Blum, C., editor(s), EvoCOP, volume 7832, of Lecture Notes in Computer Science, pages 214-225, 2013. Springer
Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures. [link]Link   Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures. [link]Paper   link   bibtex  
  2012 (1)
Automatic generation of graph models for complex networks by genetic programming. Bailey, A.; Ventresca, M.; and Ombuki-Berman, B. M. In Soule, T.; and Moore, J. H., editor(s), GECCO, pages 711-718, 2012. ACM
Automatic generation of graph models for complex networks by genetic programming. [link]Link   Automatic generation of graph models for complex networks by genetic programming. [link]Paper   link   bibtex  
  2009 (3)
Improving gradient-based learning algorithms for large scale feedforward networks. Ventresca, M.; and Tizhoosh, H. R. In IJCNN, pages 3212-3219, 2009. IEEE Computer Society
Improving gradient-based learning algorithms for large scale feedforward networks. [link]Link   Improving gradient-based learning algorithms for large scale feedforward networks. [link]Paper   link   bibtex  
Symmetry Induction in Computational Intelligence. Ventresca, M. Ph.D. Thesis, University of Waterloo, Ontario, Canada, 2009. base-search.net (ftunivwaterloo:oai:uwspace.uwaterloo.ca:10012/4845)
Symmetry Induction in Computational Intelligence. [link]Link   link   bibtex  
A search space analysis for the waste collection vehicle routing problem with time windows. Runka, A.; Ombuki-Berman, B. M.; and Ventresca, M. In Rothlauf, F., editor(s), GECCO, pages 1813-1814, 2009. ACM
A search space analysis for the waste collection vehicle routing problem with time windows. [link]Link   A search space analysis for the waste collection vehicle routing problem with time windows. [link]Paper   link   bibtex  
  2008 (1)
Numerical condition of feedforward networks with opposite transfer functions. Ventresca, M.; and Tizhoosh, H. R. In IJCNN, pages 3233-3240, 2008. IEEE
Numerical condition of feedforward networks with opposite transfer functions. [link]Link   Numerical condition of feedforward networks with opposite transfer functions. [link]Paper   link   bibtex  
  2007 (4)
Simulated Annealing with Opposite Neighbors. Ventresca, M.; and Tizhoosh, H. R. In FOCI, pages 186-192, 2007. IEEE
Simulated Annealing with Opposite Neighbors. [link]Link   Simulated Annealing with Opposite Neighbors. [link]Paper   link   bibtex  
Opposite Transfer Functions and Backpropagation Through Time. Ventresca, M.; and Tizhoosh, H. R. In FOCI, pages 570-577, 2007. IEEE
Opposite Transfer Functions and Backpropagation Through Time. [link]Link   Opposite Transfer Functions and Backpropagation Through Time. [link]Paper   link   bibtex  
Epistasis in Multi-Objective Evolutionary Recurrent Neuro-Controllers. Ventresca, M.; and Ombuki-Berman, B. M. In ALIFE, pages 77-84, 2007. IEEE
Epistasis in Multi-Objective Evolutionary Recurrent Neuro-Controllers. [link]Link   Epistasis in Multi-Objective Evolutionary Recurrent Neuro-Controllers. [link]Paper   link   bibtex  
Search Difficulty of Two-Connected Ring-based Topological Network Designs. Ombuki-Berman, B. M.; and Ventresca, M. In FOCI, pages 267-274, 2007. IEEE
Search Difficulty of Two-Connected Ring-based Topological Network Designs. [link]Link   Search Difficulty of Two-Connected Ring-based Topological Network Designs. [link]Paper   link   bibtex  
  2006 (3)
Search Space Analysis of Recurrent Spiking and Continuous-time Neural Networks. Ventresca, M.; and Ombuki-Berman, B. M. In IJCNN, pages 4514-4521, 2006. IEEE
Search Space Analysis of Recurrent Spiking and Continuous-time Neural Networks. [link]Link   Search Space Analysis of Recurrent Spiking and Continuous-time Neural Networks. [link]Paper   link   bibtex  
Improving the Convergence of Backpropagation by Opposite Transfer Functions. Ventresca, M.; and Tizhoosh, H. R. In IJCNN, pages 4777-4784, 2006. IEEE
Improving the Convergence of Backpropagation by Opposite Transfer Functions. [link]Link   Improving the Convergence of Backpropagation by Opposite Transfer Functions. [link]Paper   link   bibtex  
Optimized Memory Assignment for DSPs. Gréwal, G.; Coros, S.; Banerji, D. K.; Morton, A.; and Ventresca, M. In IEEE Congress on Evolutionary Computation, pages 64-72, 2006. IEEE
Optimized Memory Assignment for DSPs. [link]Link   Optimized Memory Assignment for DSPs. [link]Paper   link   bibtex