Gasper Petelin

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 24

Top Topics

Machine Learning

Continuous Optimization

Reference Points

Top Venues

GECCO Companion

Swarm Evol. Comput.

Publications

Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov
TransOptAS: Transformer-Based Algorithm Selection for Single-Objective Optimization. GECCO Companion (2024)
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 (2024)
Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov
TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting. Swarm Evol. Comput. 84 (2024)
Gasper Petelin, Gjorgjina Cenikj
On Generalization of ELA Feature Groups. GECCO Companion (2024)
Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov
A cross-benchmark examination of feature-based algorithm selector generalization in single-objective numerical optimization. Swarm Evol. Comput. 87 (2024)
Gjorajina Ceniki, Gasper Petelin, Tome Eftimov
Impact of Scaling in ELA Feature Calculation on Algorithm Selection Cross-Benchmark Transferability. CEC (2024)
Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. GECCO (2023)
Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. CoRR (2023)
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 (2023)
Gasper Petelin, Gjorgjina Cenikj
How Far Out of Distribution Can We Go With ELA Features and Still Be Able to Rank Algorithms? SSCI (2023)
Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov
Towards understanding the importance of time-series features in automated algorithm performance prediction. Expert Syst. Appl. 213 (Part) (2023)
Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov
TransOpt: Transformer-based Representation Learning for Optimization Problem Classification. CoRR (2023)
Rok Hribar, Gasper Petelin, Margarita Antoniou, Anton Biasizzo, Stanko Ciglaric, Gregor Papa
On Suitability of the Customized Measuring Device for Electric Motor. IECON (2022)
Gjorgjina Cenikj, Gasper Petelin, Barbara Korousic-Seljak, Tome Eftimov
SciFoodNER: Food Named Entity Recognition for Scientific Text. Big Data (2022)
Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov
TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances. SSCI (2022)
Gasper Petelin, Margarita Antoniou, Gregor Papa
Dynamic computational resource allocation for CFD simulations based on pareto front optimization. GECCO Companion (2022)
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. J. Glob. Optim. 82 (2) (2022)
Tome Eftimov, Gasper Petelin, Gjorgjina Cenikj, Ana Kostovska, Gordana Ispirova, Peter Korosec, Jasmin Bogatinovski
Less is more: Selecting the right benchmarking set of data for time series classification. Expert Syst. Appl. 198 (2022)
Margarita Antoniou, Gasper Petelin, Gregor Papa
Preferred Solutions of the Ground Station Scheduling Problem using NSGA-III with Weighted Reference Points Selection. CEC (2021)
Margarita Antoniou, Gasper Petelin, Gregor Papa
On Formulating the Ground Scheduling Problem as a Multi-objective Bilevel Problem. BIOMA (2020)
Tome Eftimov, Gasper Petelin, Peter Korosec
DSCTool: A web-service-based framework for statistical comparison of stochastic optimization algorithms. Appl. Soft Comput. 87 (2020)
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 (2020)
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)
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)