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In Revision

  1. A Randomized Approximation Algorithm for the Critical Node Detection Problem
    M. Ventresca and D. Aleman
    Computers and Operations Research, 2013. [Impact: 1.98]
  2. Genetic Programming for the Automatic Inference of Graph Models for Complex Networks
    A. Bailey, M. Ventresca and B. Ombuki-Berman
    IEEE Transactions on Evolutionary Computation, 2013. [Impact: 3.34]

Journals

  1. Evaluation of Strategies to Mitigate Contagion Spread Using Social Network Characteristics
    M. Ventresca and D. Aleman
    (in press) Social Networks, 2013. [Impact: 3.48]
  2. The Polyfunctionality of Human Memory CD8+ T Cells Elicited by Acute and Chronic Virus Infections Is Not Influenced by Age
    A. Lelic, C. Verschoor, M. Ventresca, R. Parsons, C. Evelegh, D. Bowdish, M. R. Betts, M. B. Loeb and J. L. Bramson
    PLoS Pathogens, 8(12):e1003076, 2012. [Impact: 9.13]
  3. Global Search Algorithms Using a Combinatorial Unranking-Based Problem Representation for the Critical Node Detection Problem
    M. Ventresca
    Computers and Operations Research, 39(11):2763-2775, 2012. [Impact: 1.98] Problem Instances
  4. An Intuitive Distance-Based Explanation of Opposition-Based Sampling
    S. Rahnamayan, G. Wang and M. Ventresca
    Applied Soft Computing, 12(9):2828-2839, 2012. [Impact: 2.61]
  5. Enhancing Particle Swarm Optimization using Generalized Opposition-Based Learning
    H. Wang, Z. Wu, S. Rahnamayan, Y. Liu and M. Ventresca
    Information Sciences, 181(20):4699-4714, 2011. [Impact: 2.98]
  6. Prevalence of Antibodies Against Seasonal Influenza A and B Viruses in Children in The Netherlands
    R. Bodewes, G. de Mutsert, F. van der Klis, M. Ventresca, S. Wilks, D. Smith, M. koopmans, R. A. M. Fouchier, A. D. M. E. Osterhaus, G. F. Rimmelzwaan
    Clinical and Vaccine Immunology, 18(3):469-476, 2011. [Impact: 2.55]
  7. A Note on Opposition Versus Randomness in Soft Computing Techniques
    M. Ventresca, S. Rahnamayan and H. R. Tizhoosh
    Applied Soft Computing, 10(3):956-967, 2010. [Impact: 2.61]
  8. A Diversity Maintaining Population-Based Incremental Learning Algorithm
    M. Ventresca and H. R. Tizhoosh
    Information Sciences, 178(21):4038-4056, 2008. [Impact: 2.98]
  9. A Memetic Algorithm for Performing Memory Assignment in Dual-Bank DSPs
    G. Grewal, S. Coros and M. Ventresca
    Computational Intelligence and Applications, 6(4):473-497, 2006. [Impact: 0.5]
  10. A Genetic Algorithm for the Design of Two Connected Networks with Bounded Rings
    M. Ventresca and B. Ombuki
    Computational Intelligence and Applications, 5(2):267-281, 2005. [Impact: 0.5]
  11. Local Search Genetic Algorithm for the Job Shop Scheduling Problem
    B. Ombuki and M. Ventresca
    Applied Intelligence, 21(1):99-109, 2004. [Impact: 0.85]

Conferences

  1. Automatic Inference of Hierarchical Graph Models using Genetic Programming with an Application to Cortical Networks
    A. Bailey, M. Ventresca and B. Ombuki-Berman
    (to appear), Genetic and Evolutionary Computation Conference (GECCO), 2013.
  2. Predicting Genetic Algorithm Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures
    M. Ventresca, A. Runka and B. Ombuki-Berman
    13th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP), pp: 214-225, Vienna, Austria, 2013.
  3. Automatic Generation of Graph Models For Complex Networks by Genetic Programming
    A. Bailey, M. Ventresca and B. Ombuki-Berman
    Genetic and Evolutionary Computation Conference (GECCO), pp: 711-718, Philadelphia, USA, 2012.
  4. A Search Space Analysis for the Waste Collection Vehicle Routing Problem with Time Windows
    A. Runka, B. Ombuki-Berman and M. Ventresca
    Genetic and Evolutionary Computation Conference (GECCO), pp:1813-1814, Montreal, Canada, 2009.
  5. Improving Gradient-Based Learning Algorithms for Large Scale Neural Networks
    M. Ventresca and H. R. Tizhoosh
    IEEE International Joint Conference on Neural Networks, pp:1529-1536, Atlanta, USA, 2009.
  6. Numerical Condition of Feedforward Networks with Opposite Transfer Functions
    M. Ventresca and H. R. Tizhoosh
    IEEE International Joint Conference on Neural Networks (IJCNN), pp:3232-3239, Hong Kong, China, 2008.
  7. Simulated Annealing with Opposite Neighbors
    M. Ventresca and H. R. Tizhoosh
    IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp:186-192, Honolulu, USA, 2007.
  8. Opposite Transfer Functions and Backpropagation Through Time
    M. Ventresca and H. R. Tizhoosh
    IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp:570-577, Honolulu, USA, 2007.
  9. Epistasis in Multi-Objective Evolutionary Recurrent Neuro-Controllers
    M. Ventresca and B. Ombuki-Berman
    IEEE Symposium on Artificial Life (CI-ALIFE), pp:77-84, Honolulu, USA, 2007.
  10. Search Difficulty of Two-Connected Ring-based Topological Network Designs
    B. Ombuki-Berman and M. Ventresca
    IEEE Symposium on Foundations of Computational Intelligence (FOCI), pp:267-274, Honolulu, USA, 2007.
  11. Improving the Convergence of Backpropagation by Opposite Transfer Functions
    M. Ventresca, H. R. Tizhoosh
    International Joint Conference on Neural Networks (IJCNN), pp:9527-9534, Vancouver, Canada, 2006.
  12. Search Space Analysis of Recurrent Spiking and Continuous-time Neural Networks
    M. Ventresca and B. Ombuki
    International Joint Conference on Neural Networks (IJCNN), pp:8947-8954, Vancouver, Canada, 2006.
  13. Optimized Memory Assignment for DSPs
    G. Grewal, S. Coros, D. Banerji, A. Morton and M. Ventresca
    Congress on Evolutionary Computation (CEC), pp:371-379, Vancouver, Canada, 2006.
  14. Ant Colony Optimization for Job Shop Scheduling Problem
    M. Ventresca and B. Ombuki
    8th International Conference On Artificial Intelligence and Soft Computing (ASC 2004), CDROM:451-152. Marbella, Spain, 2004.
  15. A Genetic Algorithm for the Design of Two Connected Networks with Bounded Rings
    M. Ventresca and B. Ombuki
    8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), Birmingham, UK, 2004.
  16. Meta-heuristics for the Job Shop Scheduling Problem
    M. Ventresca and B. Ombuki
    Proceedings of Late Breaking Papers, Genetic and Evolutionary Computation Conference(GECCO) pp:303-306, Chicago, USA, 2003.

Books

  1. Oppositional Concepts in Computational Intelligence
    H. R. Tizhoosh and M. Ventresca (Eds.),
    Studies in Computational Intelligence, Springer-Verlag, 2008.

Book Chapters

  1. The Use of Opposition for Decreasing Function Evaluations in Population-Based Search
    M. Ventresca, S. Rahnamayan and H. R. Tizhoosh
    Computational Intelligence in Optimization-Applications and Implementations, Springer-Verlag, 2010.
  2. Two Frameworks for Improving Gradient-Based Learning Algorithms
    M. Ventresca and H. R. Tizhoosh
    Oppositional Concepts in Computational Intellligence, 2008.
  3. Opposition-Based Computing
    H. R. Tizhoosh, M. Ventresca and S. Rahnamayan
    Oppositional Concepts in Computational Intellligence, 2008.

Refereed and Invited Abstracts

  1. A Critical Node Detection Approach to Pandemic Planning
    M. Ventresca and D. Aleman
    (to appear), 55th Canadian Operational Research Society Annual Conference, 2013.
  2. Infectious Disease Mitigation: From Contact Networks to Public Policies
    M. Ventresca and D. Aleman
    (to appear), INFORMS Healthcare, 2013.
  3. Using a Pandemic Disease Spread Simulation Model to Make Deterministic, Graph-Theory Based Vaccine Decisions
    D. Aleman and M. Ventresca
    (to appear), IIE Industrial and Systems Engineering Research Conference (ISERC), 2013.
  4. Evaluation of Disease Mitigation Strategies Using Social Network Characteristics
    M. Ventresca and D. Aleman
    INFORMS Annual Meeting, Phoenix, USA, 2012.
  5. Simplifying the Interpretation of Human Serology in Vaccine Selection
    S.L. James, J.M. Fonville, M. Ventresca, L. Xue, S. Wilks, Y. Wong, G. van der Net, R. Bodewes, C.A. Russell, G.F. Rimmelzwaan, A. Mosterin, N. Masurel, J.C. de Jong, W.E.P. Beyer, F. Pistoor, A. Palache, A. Hurt, I.G. Barr, A.D.M.E. Osterhaus, R.A.M. Fouchier and D.J. Smith
    Public Health Science, Royal Society of Medicine, 2012.
  6. Antibody Landscapes: Quantifying the Antibody Immune Response
    J.M. Fonville, S. L. James, M. Ventresca, L. Xue, S. Wilks, Y. Wong, G. van der Net, R. Bodewes, C.A. Russell, G.F. Rimmelzwaan, A. Mosterin, N. Masurel, J.C. de Jong, W.E. Beyer, F. Pistoor, A. Palache, A. Hurt, I.G. Barr, A.D.M.E. Osterhaus, R.A.M. Fouchier and D.J. Smith
    6th Orthomyxovirus Research Conference, Montreal 2012.
  7. Controlling for Antigenic Differences Simplifies the Interpretation of Human Serology Data
    S. L. James, M. Ventresca, S. Wilks, Y. Wong, G. van der Net, R. Bodewes, C.A. Russell, G.F. Rimmelzwaan, A. Mosterin, N. Masurel, J.C. de Jong, W.E. Beyer, F. Pistoor, A. Palache, A.D.M.E. Osterhaus, R.A.M. Fouchier and D.J. Smith
    The Fourth ESWI Influenza Conference, Malta, 2011.