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Št. zadetkov: 10
RF+clust for leave-one-problem-out performance prediction
Ana Nikolikj, Carola Doerr, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: algorithm performance prediction;automated machine learning;zero-shot learning;black-box optimization;
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
DynamoRep
Gjorgjina Cenikj, Gašper Petelin, Carola Doerr, Peter Korošec, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: black-box single-objective optimization;optimization problem classification;problem representation;meta-learning;
DynamoRep
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
Sensitivity analysis of RF+clust for leave-one-problem-out performance prediction
Ana Nikolikj, Michal Pluhacek, Carola Doerr, Peter Korošec, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: strojno učenje;automated performance prediction;autoML;single-objective black-box optimization;zero-shot learning;
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
Quantifying individual and joint module impact in modular optimization frameworks
Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: metapodatki;strojno učenje;meta-learning;single-objective optimization;module importance;
Leto: 2024 Vir: Institut Jožef Stefan (IJS)
Generalization ability of feature-based performance prediction models
Ana Nikolikj, Ana Kostovska, Gjorgjina Cenikj, Carola Doerr, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: metapodatki;strojno učenje;meta-learning;single-objective optimization;module importance;
This study examines the generalization ability of algorithm performance prediction models across various bench-mark suites. Comparing the statistical similarity between the problem collections with the accuracy of performance prediction models that are based on exploratory landscape analysis feature ...
Leto: 2024 Vir: Institut Jožef Stefan (IJS)
Learned features vs. classical ELA on affine BBOB functions
Moritz Seiler, Urban Škvorc, Gjorgjina Cenikj, Carola Doerr, Heike Trautmann
Objavljeni znanstveni prispevek na konferenci
Oznake: black box optimization;automated algorithm selection;exploratory landscape analysis;
Leto: 2024 Vir: Institut Jožef Stefan (IJS)
Using machine learning methods to assess module performance contribution in modular optimization frameworks
Ana Kostovska, Diederick Vermetten, Peter Korošec, Sašo Džeroski, Carola Doerr, Tome Eftimov
Izvirni znanstveni članek
Oznake: mreže;algoritmi;evolutionary computation;modular algorithm frameworks;DE;
Modular algorithm frameworks not only allow for combinations never tested in manually selected algorithm portfolios, but they also provide a structured approach to assess which algorithmic ideas are crucial for the observed performance of algorithms. In this study, we propose a methodology for analy ...
Leto: 2024 Vir: Institut Jožef Stefan (IJS)
Algorithm instance footprint
Ana Nikolikj, Sašo Džeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korošec, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: black-box optimization;algorithms;problem instances;machine learning;
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
PS-AAS
Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten, Anja Janković, Ana Nikolikj, Urban Škvorc, Peter Korošec, Carola Doerr, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: automated algorithm selection;portfolio selection;black box optimization;
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
Assessing the generalizability of a performance predictive model
Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries P. Engelbrecht, Carola Doerr, Peter Korošec, Tome Eftimov
Objavljeni znanstveni prispevek na konferenci
Oznake: algorithms;predictive models;machine learning;
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
Št. zadetkov: 10
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