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Machine Learning

About the Group

The group is interested in the development and application of innovative computational learning models for the solution of computational complex problems. We have applied our techniques in contexts such as cybersecurity, personal integrity, intelligent cities, video surveillance, data science, citizen science, etc.

Research lines

  • Grouping
  • Big Data
  • Innovative classification models based on instances, contrast patterns, decision trees, and combination.
  • Data management models for real-time processing in different hardware architectures.
  • Palm fingerprint recognition algorithms
  • Visualization models to support decision making combined with computational learning techniques.

Leader

Raúl Monroy Borja
 

Core reserchers

Leonardo Chang Fernández
Luciano García Bañuelos
Luis Angel Trejo Rodríguez
Miguel Angel Medina Perez
Miguel González Mendoza
Octavio Loyola González

 

Adjunct researchers

Alberto Aguilar González
Andrés Eduardo Gutiérrez Rodríguez
Armando López Cuevas
Cesar Torres Huitzil
Gilberto Ochoa Ruiz
Joanna Alvarado Uribe
Jorge Rodríguez Ruiz
Mariano Vargas Santiago
Mariel Alfaro Ponce
Neil Hernández Gress
Víctor Adrián Sosa Hernández

Publications

Top 5 of publications 2015-2019

- A review of definitions and measures of system resilience
Authors: Hosseini, S., Barker, K., & Ramirez-Marquez, J.

- A Community Perspective on Resilience Analytics: A Visual Analysis of Community Mood
Authors: López-Cuevas, A., Ramírez-Márquez, J., Sanchez-Ante, G., & Barker, K.

- PBC4cip: A new contrast pattern-based classifier for class imbalance problems
Authors: Loyola-González, O., Medina-Pérez, M., Martínez-Trinidad, J., Carrasco-Ochoa, J., Monroy, R., & García-Borroto, M.

- Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning
Authors: Nicholson, C., Barker, K., & Ramirez-Marquez, J.

- Quantifying the risk of project delays with a genetic algorithm
Authors: Pfeifer, J., Barker, K., Ramirez-Marquez, J., & Morshedlou, N.