Gasper Petelin

According to our database, Gasper Petelin authored at least 17 papers between 2020 and 2024.

Collaborative distances:

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

2024

TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting.

Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov

Swarm Evol. Comput., February, 2024

2023

Towards understanding the importance of time-series features in automated algorithm performance prediction.

Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov

Expert Syst. Appl., 2023

TransOpt: Transformer-based Representation Learning for Optimization Problem Classification.

Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov

CoRR, 2023

Dealing with zero-inflated data: achieving SOTA with a two-fold machine learning approach.

Joze M. Rozanec, Gasper Petelin, João Pita Costa, Blaz Bertalanic, Gregor Cerar, Marko Gucek, Gregor Papa, Dunja Mladenic

CoRR, 2023

How Far Out of Distribution Can We Go With ELA Features and Still Be Able to Rank Algorithms?

Gasper Petelin, Gjorgjina Cenikj

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems.

Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem.

Rok Hribar, Timotej Hrga, Gregor Papa, Gasper Petelin, Janez Povh, Natasa Przulj, Vida Vukasinovic

J. Glob. Optim., 2022

Less is more: Selecting the right benchmarking set of data for time series classification.

Tome Eftimov, Gasper Petelin, Gjorgjina Cenikj, Ana Kostovska, Gordana Ispirova, Peter Korosec, Jasmin Bogatinovski

Expert Syst. Appl., 2022

TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances.

Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

On Suitability of the Customized Measuring Device for Electric Motor.

Rok Hribar, Gasper Petelin, Margarita Antoniou, Anton Biasizzo, Stanko Ciglaric, Gregor Papa

Proceedings of the IECON 2022, 2022

Dynamic computational resource allocation for CFD simulations based on pareto front optimization.

Gasper Petelin, Margarita Antoniou, Gregor Papa

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

SciFoodNER: Food Named Entity Recognition for Scientific Text.

Gjorgjina Cenikj, Gasper Petelin, Barbara Korousic-Seljak, Tome Eftimov

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Preferred Solutions of the Ground Station Scheduling Problem using NSGA-III with Weighted Reference Points Selection.

Margarita Antoniou, Gasper Petelin, Gregor Papa

Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020

DSCTool: A web-service-based framework for statistical comparison of stochastic optimization algorithms.

Tome Eftimov, Gasper Petelin, Peter Korosec

Appl. Soft Comput., 2020

Deep statistics: more robust performance statistics for single-objective optimization benchmarking.

Tome Eftimov, Gasper Petelin, Rok Hribar, Gorjan Popovski, Urban Skvorc, Peter Korosec

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

PerformViz: a machine learning approach to visualize and understand the performance of single-objective optimization algorithms.

Tome Eftimov, Rok Hribar, Urban Skvorc, Gorjan Popovski, Gasper Petelin, Peter Korosec

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

On Formulating the Ground Scheduling Problem as a Multi-objective Bilevel Problem.

Margarita Antoniou, Gasper Petelin, Gregor Papa

Proceedings of the Bioinspired Optimization Methods and Their Applications, 2020