Mario A. Muñoz

According to our database, Mario A. Muñoz authored at least 36 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

On the impact of initialisation strategies on Maximum Flow algorithm performance.

Hossein Alipour, Mario Andrés Muñoz, Kate Smith-Miles

Comput. Oper. Res., March, 2024

Optimal selection of benchmarking datasets for unbiased machine learning algorithm evaluation.

João Luiz Junho Pereira, Kate Smith-Miles, Mario Andrés Muñoz, Ana Carolina Lorena

Data Min. Knowl. Discov., 2024

Characterising harmful data sources when constructing multi-fidelity surrogate models.

Nicolau Andrés-Thió, Mario Andrés Muñoz, Kate Smith-Miles

CoRR, 2024

2023

Instance Space Analysis for Algorithm Testing: Methodology and Software Tools.

Kate Smith-Miles, Mario Andrés Muñoz

ACM Comput. Surv., December, 2023

An Instance Space Analysis of Constrained Multiobjective Optimization Problems.

Hanan Alsouly, Michael Kirley, Mario Andrés Muñoz

IEEE Trans. Evol. Comput., October, 2023

Instance Space Analysis of Search-Based Software Testing.

Neelofar, Kate Smith-Miles, Mario Andrés Muñoz, Aldeida Aleti

IEEE Trans. Software Eng., April, 2023

Enhanced instance space analysis for the maximum flow problem.

Hossein Alipour, Mario Andrés Muñoz, Kate Smith-Miles

Eur. J. Oper. Res., 2023

Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances.

Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Dynamic Landscape Analysis for Constrained Multiobjective Optimization Problems.

Hanan Alsouly, Michael Kirley, Mario Andrés Muñoz

Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023

2022

Informing Multiobjective Optimization Benchmark Construction Through Instance Space Analysis.

Estefania Yap, Mario Andrés Muñoz, Kate Smith-Miles

IEEE Trans. Evol. Comput., 2022

Analyzing randomness effects on the reliability of exploratory landscape analysis.

Mario Andrés Muñoz, Michael Kirley, Kate Smith-Miles

Nat. Comput., 2022

An Instance Space Analysis of Constrained Multi-Objective Optimization Problems.

Hanan Alsouly, Michael Kirley, Mario Andrés Muñoz

CoRR, 2022

Benchmarking algorithm portfolio construction methods.

Mario Andrés Muñoz, Hamed Soleimani, Sevvandi Kandanaarachchi

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Examining algorithm behavior using recurrence quantification and landscape analyses.

Mario Andrés Muñoz

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021

An Instance Space Analysis of Regression Problems.

Mario Andrés Muñoz, Tao Yan, Matheus R. Leal, Kate Smith-Miles, Ana Carolina Lorena, Gisele L. Pappa, Rômulo Madureira Rodrigues

ACM Trans. Knowl. Discov. Data, 2021

Revisiting <i>where are the hard knapsack problems?</i> via Instance Space Analysis.

Kate Smith-Miles, Jeffrey Christiansen, Mario Andrés Muñoz

Comput. Oper. Res., 2021

On the diversity and robustness of parameterised multi-objective test suites.

Estefania Yap, Mario Andrés Muñoz, Kate Smith-Miles

Appl. Soft Comput., 2021

Sampling Effects on Algorithm Selection for Continuous Black-Box Optimization.

Mario Andrés Muñoz, Michael Kirley

Algorithms, 2021

2020

Generating New Space-Filling Test Instances for Continuous Black-Box Optimization.

Mario A. Muñoz, Kate Smith-Miles

Evol. Comput., 2020

On normalization and algorithm selection for unsupervised outlier detection.

Sevvandi Kandanaarachchi, Mario A. Muñoz, Rob J. Hyndman, Kate Smith-Miles

Data Min. Knowl. Discov., 2020

Instance Space Analysis of Combinatorial Multi-objective Optimization Problems.

Estefania Yap, Mario A. Muñoz, Kate Smith-Miles, Arnaud Liefooghe

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019

Instance Space Analysis for Unsupervised Outlier Detection.

Sevvandi Kandanaarachchi, Mario A. Muñoz, Kate Smith-Miles

Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning co-located with SIAM International Conference on Data Mining (SDM 2019), 2019

2018

Instance spaces for machine learning classification.

Mario A. Muñoz, Laura Villanova, Davaatseren Baatar, Kate Smith-Miles

Mach. Learn., 2018

2017

Performance Analysis of Continuous Black-Box Optimization Algorithms via Footprints in Instance Space.

Mario A. Muñoz, Kate Amanda Smith-Miles

Evol. Comput., 2017

Generating custom classification datasets by targeting the instance space.

Mario A. Muñoz, Kate Smith-Miles

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Non-parametric model of the space of continuous black-box optimization problems.

Mario A. Muñoz, Kate Smith-Miles

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

2016

ICARUS: Identification of complementary algorithms by uncovered sets.

Mario A. Muñoz, Michael Kirley

Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015

Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content.

Mario A. Muñoz, Michael Kirley, Saman K. Halgamuge

IEEE Trans. Evol. Comput., 2015

Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges.

Mario A. Muñoz, Yuan Sun, Michael Kirley, Saman K. Halgamuge

Inf. Sci., 2015

Effects of function translation and dimensionality reduction on landscape analysis.

Mario A. Muñoz, Kate Smith-Miles

Proceedings of the IEEE Congress on Evolutionary Computation, 2015

2013

Decision support systems for the automatic selection of algorithms for continuous optimization problems.

Mario Andrés Muñoz Acosta

PhD thesis, 2013

2012

A Meta-learning Prediction Model of Algorithm Performance for Continuous Optimization Problems.

Mario A. Muñoz, Michael Kirley, Saman K. Halgamuge

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

Landscape characterization of numerical optimization problems using biased scattered data.

Mario A. Muñoz, Michael Kirley, Saman K. Halgamuge

Proceedings of the IEEE Congress on Evolutionary Computation, 2012

2010

Simplifying the Bacteria Foraging Optimization Algorithm.

Mario A. Muñoz, Saman K. Halgamuge, Wilfredo Alfonso, Eduardo Caicedo

Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2009

An artificial beehive algorithm for continuous optimization.

Mario A. Muñoz, Jesús A. López, Eduardo Caicedo

Int. J. Intell. Syst., 2009

2007

Bacteria Swarm Foraging Optimization for Dynamical Resource Allocation in a Multizone Temperature Experimentation Platform.

Mario A. Muñoz, Jesús A. López, Eduardo Caicedo

Proceedings of the Analysis and Design of Intelligent Systems using Soft Computing Techniques, 2007