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Daniel Aloise
M.Sc. (PUC-Rio, Brésil) et un Ph.D. (Poly)

Research interests and affiliations

Research interests
  • Data Science
  • Big Data
  • Optimization
  • Mathematical Programming
Expertise type(s) (NSERC subjects)
  • 1601 Operations research and management science
  • 2510 Adaptive, learning and evolutionary systems
  • 2713 Algorithms
  • 2715 Optimization

Publications

Recent publications
Journal article
Rodrigues, I.M., Khvorov, A., Aloise, D., Vasiliev, R., Koznov, D., Fernandes, E.R., Chernishev, G., Luciv, D. & Povarov, N. (2022). TraceSim: An Alignment Method for Computing Stack Trace Similarity. Empirical Software Engineering, 27(2), 41 pages. Retrieved from https://doi.org/10.1007/s10664-021-10070-w
Journal article
Rocha, D., Aloise, D., Aloise, D.J. & Contardo, C. (2022). Visual attractiveness in vehicle routing via bi-objective optimization. Computers & Operations Research, 137, 14 pages. Retrieved from https://doi.org/10.1016/j.cor.2021.105507
Journal article
Kohyarnejadfard, I., Aloise, D., Dagenais, M.R. & Shakeri, M. (2021). A Framework for Detecting System Performance Anomalies Using Tracing Data Analysis. Entropy, 23(8), 24 pages. Retrieved from https://doi.org/10.3390/e23081011
Journal article
Randel, R., Aloise, D., Blanchard, S.J. & Hertz, A. (2021). A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering. Data Mining and Knowledge Discovery, 35(6), 2341-2368. Retrieved from https://doi.org/10.1007/s10618-021-00794-0

Supervision at Polytechnique

COMPLETED

  • Ph.D. Thesis (2)

    • Alves Randel, R. (2021). Optimization Methods to Enhance Constraint-Based Semi-Supervised Clustering (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9240/
    • Rochink Costa, L. (2021). Workload Optimization for Swarm-Powered Ad-hoc Clouds (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6650/
  • Master's Thesis (7)

    • Bouchard, I. (2021). Building Damage Assessment After a Natural Disaster in Emergency Contexts: A Deep Learning Approach (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9470/
    • Ton, K. (2021). Using a Diversity Criterion to Select Training Sets for Machine Learning Models (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/9902/
    • Haouas, M.N. (2020). Résolution exacte du problème de partitionnement de données avec minimisation de variance sous contraintes de cardinalité par programmation par contraintes (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/4207/
    • Heutte, N. (2020). A Divide-and-Conquer Approach to Employee Scheduling (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/5362/
    • Moins, T. (2020). Modèle hybride combinant réseau de neurones convolutifs et modèle basé sur le choix pour la recommandation de sièges (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/5336/
    • Boucaud, L. (2019). Mécanismes d'attention pour les modèles convolutifs dans le cadre de la prédiction de trajectoires (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/3951/
    • Hulot, P. (2018). Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/3160/

News about Daniel Aloise

BLOG | November 23, 2021
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