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Vicente Pérez

Vicente Pérez

PhD Student

Google Scholar
Vicente P. Soloviev received the M.Sc. degree in Artificial Intelligence from Universidad Politécnica de Madrid, in 2020 and he is currently a PhD student at Universidad Politécnica de Madrid in the Computational Intelligence Group. He has been recognized as a Qiskit Advocate by IBM Qiskit in 2021. Vicente holds a pre-doctoral FPI contract awarded by the Spanish Ministry of Science and Innovation since 2021.

  • Teaching
    • Data mining – B.Sc. in Computer Science at Universidad Politécnica de Madrid
    • Machine learning – M.Sc. AEPIA
  • Seminars
      • “Webinar: Application of variational quantum algorithms for learning the structure of Bayesian networks.” – CESGA
      • “PYSQT seminar: QAOA for Bayesian network structure learning” – PYSQT organization
  • Research Interest
        • His research interests include the areas of probabilistic graphical models, metaheuristics for optimization, quantum machine learning, quantum heuristics, and real applications such as industry 4.0.
  • Publications
    • Indexed Journal Acticles
      • Soloviev, V. P., Bielza, C., & Larrañaga, P. (2023). Semiparametric estimation of distribution algorithms for continuous optimization. IEEE Transactions on Evolutionary Computation.
      • Soloviev, V. P., Bielza, C., & Larrañaga, P. (2022). Quantum approximate optimization algorithm for Bayesian network structure learning. Quantum Information Processing22(1), 19.
      • Soloviev, V. P., Larrañaga, P., & Bielza, C. (2022). Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables. Journal of Combinatorial Optimization44(2), 1077-1098.
  • Main Conference Proceedings
    • Soloviev, V. P., Larrañaga, P., & Bielza, C. (2023, July). Variational Quantum Algorithm Parameter Tuning with Estimation of Distribution Algorithms. In 2023 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-9). IEEE.