Learning input-aware performance models of configurable systems: An empirical evaluation

Finding Near-Optimal Configurations in Colossal Spaces with Statistical Guarantees

(2023) Jeho Oh et al.   ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY

Learning software configuration spaces: A systematic literature review

(2021) Juliana Alves Pereira et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Tabular data: Deep learning is not all you need

(2021) Ravid Shwartz-Ziv et al.   Information Fusion

Whence to Learn? Transferring Knowledge in Configurable Systems Using BEETLE

(2020) Rahul Krishna et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

SATzilla: Portfolio-based Algorithm Selection for SAT

(2018) L. Xu et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

Automated Algorithm Selection: Survey and Perspectives

(2018) Pascal Kerschke et al.   EVOLUTIONARY COMPUTATION

Learning Contextual-Variability Models

(2017) Paul Temple et al.   IEEE SOFTWARE

Heterogeneous Defect Prediction

(2017) Jaechang Nam et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Algorithm runtime prediction: Methods & evaluation

(2013) Frank Hutter et al.   ARTIFICIAL INTELLIGENCE

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING