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Št. zadetkov: 9
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)
Recent advances in meta-features for automated single-objective black-box optimization
Gjorgjina Cenikj, Ana Nikolikj, Tome Eftimov
Video in druga učna gradiva
Oznake: black-box optimization;
Leto: 2024 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)
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)
Instance selection for dynamic algorithm configuration with reinforcement learning
Carolin Benjamins, Gjorgjina Cenikj, Ana Nikolikj, Aditya Mohan, Tome Eftimov, Marius Lindauer
Objavljeni znanstveni prispevek na konferenci
Oznake: izbira algoritmov;dynamic algorithm configuration;reinforcement learning;instance selection;generalization;
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: 9
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