Gasper Petelin
Orcid: 0000-0001-5929-5761
According to our database1,
Gasper Petelin
authored at least 22 papers
between 2020 and 2024.
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Bibliography
2024
TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting.
Swarm Evol. Comput., February, 2024
A cross-benchmark examination of feature-based algorithm selector generalization in single-objective numerical optimization.
Swarm Evol. Comput., 2024
A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization.
CoRR, 2024
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024
Impact of Scaling in ELA Feature Calculation on Algorithm Selection Cross-Benchmark Transferability.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024
2023
Towards understanding the importance of time-series features in automated algorithm performance prediction.
Expert Syst. Appl., 2023
TransOpt: Transformer-based Representation Learning for Optimization Problem Classification.
CoRR, 2023
Dealing with zero-inflated data: achieving SOTA with a two-fold machine learning approach.
CoRR, 2023
How Far Out of Distribution Can We Go With ELA Features and Still Be Able to Rank Algorithms?
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
2022
Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem.
J. Glob. Optim., 2022
Less is more: Selecting the right benchmarking set of data for time series classification.
Expert Syst. Appl., 2022
TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022
Proceedings of the IECON 2022, 2022
Dynamic computational resource allocation for CFD simulations based on pareto front optimization.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
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.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021
2020
DSCTool: A web-service-based framework for statistical comparison of stochastic optimization algorithms.
Appl. Soft Comput., 2020
Deep statistics: more robust performance statistics for single-objective optimization benchmarking.
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.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
Proceedings of the Bioinspired Optimization Methods and Their Applications, 2020