Mario Garza-Fabre

According to our database, Mario Garza-Fabre authored at least 25 papers between 2009 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Enabling realistic experimentation of disaggregated RAN: Design, implementation, and validation of a modular multi-split eNodeB.

Cristian C. Erazo-Agredo, Luis Díez, Ramón Agüero, Mario Garza-Fabre, Javier Rubio-Loyola

Comput. Networks, November, 2023

Evolutionary Multiobjective Clustering Over Multiple Conflicting Data Views.

Mario Garza-Fabre, Julia Handl, Adán José García

IEEE Trans. Evol. Comput., 2023

2022

Protein Structure and Synthetic Multi-view Clustering Datasets.

Mario Garza-Fabre, Julia Handl

Dataset, November, 2022

Decision Making in Evolutionary Multiobjective Clustering: A Machine Learning Challenge.

Mario Garza-Fabre, Aarón Leonardo Sánchez-Martínez, Edwin Aldana-Bobadilla, Ricardo Landa Becerra

IEEE Access, 2022

Machine Learning-Based Decision Making in Evolutionary Multiobjective Clustering.

Aarón Leonardo Sánchez-Martínez, Mario Garza-Fabre, Ricardo Landa Becerra, Edwin Aldana-Bobadilla

Proceedings of the Advances in Computational Intelligence, 2022

2021

Joint Route Selection and Split Level Management for 5G C-RAN.

Cristian C. Erazo-Agredo, Mario Garza-Fabre, Ramón Agüero Calvo, Luis Díez, Joan Serrat, Javier Rubio-Loyola

IEEE Trans. Netw. Serv. Manag., 2021

An evolutionary many-objective approach to multiview clustering using feature and relational data.

Adán José García, Julia Handl, Wilfrido Gómez-Flores, Mario Garza-Fabre

Appl. Soft Comput., 2021

2019

Many-view clustering: an illustration using multiple dissimilarity measures.

Adán José García, Julia Handl, Wilfrido Gómez-Flores, Mario Garza-Fabre

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

2018

An Improved and More Scalable Evolutionary Approach to Multiobjective Clustering.

Mario Garza-Fabre, Julia Handl, Joshua D. Knowles

IEEE Trans. Evol. Comput., 2018

2017

On heuristic bias in fragment-assembly methods for protein structure prediction.

Julia Handl, Mario Garza-Fabre, Shaun M. Kandathil, Simon C. Lovell

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

A New Reduced-Length Genetic Representation for Evolutionary Multiobjective Clustering.

Mario Garza-Fabre, Julia Handl, Joshua D. Knowles

Proceedings of the Evolutionary Multi-Criterion Optimization, 2017

2016

Generating, Maintaining, and Exploiting Diversity in a Memetic Algorithm for Protein Structure Prediction.

Mario Garza-Fabre, Shaun M. Kandathil, Julia Handl, Joshua D. Knowles, Simon C. Lovell

Evol. Comput., 2016

2015

Multi-objectivization, fitness landscape transformation and search performance: A case of study on the hp model for protein structure prediction.

Mario Garza-Fabre, Gregorio Toscano Pulido, Eduardo Rodriguez-Tello

Eur. J. Oper. Res., 2015

Constraint-handling through multi-objective optimization: The hydrophobic-polar model for protein structure prediction.

Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregorio Toscano Pulido

Comput. Oper. Res., 2015

Using Machine Learning to Explore the Relevance of Local and Global Features During Conformational Search in Rosetta.

Mario Garza-Fabre, Shaun M. Kandathil, Julia Handl, Joshua D. Knowles, Simon C. Lovell

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2013

Comparative Analysis of Different Evaluation Functions for Protein Structure Prediction Under the HP Model.

Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregorio Toscano Pulido

J. Comput. Sci. Technol., 2013

Handling constraints in the HP model for protein structure prediction by multiobjective optimization.

Mario Garza-Fabre, Gregorio Toscano Pulido, Eduardo Rodriguez-Tello

Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2012

An Improved Multiobjectivization Strategy for HP Model-Based Protein Structure Prediction.

Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregorio Toscano Pulido

Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012

Locality-based multiobjectivization for the HP model of protein structure prediction.

Mario Garza-Fabre, Gregorio Toscano Pulido, Eduardo Rodriguez-Tello

Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Multiobjectivizing the HP Model for Protein Structure Prediction.

Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregorio Toscano Pulido

Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2012

2011

Comparing alternative energy functions for the HP model of protein structure prediction.

Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregorio Toscano Pulido

Proceedings of the IEEE Congress on Evolutionary Computation, 2011

Effective ranking + speciation = Many-objective optimization.

Mario Garza-Fabre, Gregorio Toscano Pulido, Carlos A. Coello Coello, Eduardo Rodriguez-Tello

Proceedings of the IEEE Congress on Evolutionary Computation, 2011

2010

Two novel approaches for many-objective optimization.

Mario Garza-Fabre, Gregorio Toscano Pulido, Carlos A. Coello Coello

Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2009

Ranking Methods for Many-Objective Optimization.

Mario Garza-Fabre, Gregorio Toscano Pulido, Carlos A. Coello Coello

Proceedings of the MICAI 2009: Advances in Artificial Intelligence, 2009

Alternative Fitness Assignment Methods for Many-Objective Optimization Problems.

Mario Garza-Fabre, Gregorio Toscano Pulido, Carlos A. Coello Coello

Proceedings of the Artifical Evolution, 2009