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Gasper Petelin
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2020 – today
- 2024
- [j7]Gasper Petelin
, Gjorgjina Cenikj
Random Filter Mappings as Optimization Problem Feature Extractors. IEEE Access 12: 143554-143571 (2024) - [j6]Gasper Petelin
TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting. Swarm Evol. Comput. 84: 101448 (2024) - [j5]Gjorgjina Cenikj
A cross-benchmark examination of feature-based algorithm selector generalization in single-objective numerical optimization. Swarm Evol. Comput. 87: 101534 (2024) - [c13]Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov:
Impact of Scaling in ELA Feature Calculation on Algorithm Selection Cross-Benchmark Transferability. CEC 2024: 1-8 - [c12]Gjorgjina Cenikj
TransOptAS: Transformer-Based Algorithm Selection for Single-Objective Optimization. GECCO Companion 2024: 403-406 - [c11]Gasper Petelin
On Generalization of ELA Feature Groups. GECCO Companion 2024: 419-422 - [i5]Gjorgjina Cenikj, Ana Nikolikj, Gasper Petelin, Niki van Stein, Carola Doerr, Tome Eftimov:
A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization. CoRR abs/2406.06629 (2024) - 2023
- [j4]Gasper Petelin
Towards understanding the importance of time-series features in automated algorithm performance prediction. Expert Syst. Appl. 213(Part): 119023 (2023) - [c10]Gjorgjina Cenikj
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. GECCO 2023: 813-821 - [c9]Gasper Petelin, Gjorgjina Cenikj:
How Far Out of Distribution Can We Go With ELA Features and Still Be Able to Rank Algorithms? SSCI 2023: 341-346 - [i4]Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov:
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. CoRR abs/2306.05438 (2023) - [i3]Joze M. Rozanec, Gasper Petelin, João Pita Costa, Blaz Bertalanic, Gregor Cerar, Marko Gucek, Gregor Papa, Dunja Mladenic:
Dealing with zero-inflated data: achieving SOTA with a two-fold machine learning approach. CoRR abs/2310.08088 (2023) - [i2]Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov:
TransOpt: Transformer-based Representation Learning for Optimization Problem Classification. CoRR abs/2311.18035 (2023) - 2022
- [j3]Tome Eftimov
Less is more: Selecting the right benchmarking set of data for time series classification. Expert Syst. Appl. 198: 116871 (2022) - [j2]Rok Hribar, Timotej Hrga, Gregor Papa
Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem. J. Glob. Optim. 82(2): 283-312 (2022) - [c8]Gjorgjina Cenikj, Gasper Petelin, Barbara Korousic-Seljak, Tome Eftimov:
SciFoodNER: Food Named Entity Recognition for Scientific Text. IEEE Big Data 2022: 4065-4073 - [c7]Gasper Petelin, Margarita Antoniou
Dynamic computational resource allocation for CFD simulations based on pareto front optimization. GECCO Companion 2022: 1666-1673 - [c6]Rok Hribar, Gasper Petelin, Margarita Antoniou, Anton Biasizzo, Stanko Ciglaric, Gregor Papa:
On Suitability of the Customized Measuring Device for Electric Motor. IECON 2022: 1-6 - [c5]Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov:
TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances. SSCI 2022: 1698-1705 - 2021
- [c4]Margarita Antoniou
Preferred Solutions of the Ground Station Scheduling Problem using NSGA-III with Weighted Reference Points Selection. CEC 2021: 1840-1847 - 2020
- [j1]Tome Eftimov
DSCTool: A web-service-based framework for statistical comparison of stochastic optimization algorithms. Appl. Soft Comput. 87: 105977 (2020) - [c3]Margarita Antoniou
On Formulating the Ground Scheduling Problem as a Multi-objective Bilevel Problem. BIOMA 2020: 177-188 - [c2]Tome Eftimov, Gasper Petelin, Rok Hribar, Gorjan Popovski, Urban Skvorc, Peter Korosec:
Deep statistics: more robust performance statistics for single-objective optimization benchmarking. GECCO Companion 2020: 5-6 - [c1]Tome Eftimov, Rok Hribar, Urban Skvorc, Gorjan Popovski, Gasper Petelin, Peter Korosec:
PerformViz: a machine learning approach to visualize and understand the performance of single-objective optimization algorithms. GECCO Companion 2020: 7-8 - [i1]Rok Hribar, Timotej Hrga, Gregor Papa, Gasper Petelin, Janez Povh, Natasa Przulj, Vida Vukasinovic:
Four algorithms to solve symmetric multi-type non-negative matrix tri-factorization problem. CoRR abs/2012.05963 (2020)
Coauthor Index
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