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Books and Theses
- 2024
[b1]Eirik Lund Flogard:
Improving Labour Inspection Efficiency via Machine Learning. Norwegian University of Science and Technology, Trondheim, Norway, 2024
Conference and Workshop Papers
- 2023
- [c6]Eirik Lund Flogard, Ole Jakob Mengshoel, Ole Magnus Theisen, Kerstin Bach:
Creating Explainable Dynamic Checklists via Machine Learning to Ensure Decent Working Environment for All: A Field Study with Labour Inspections. ECAI 2023: 3218-3225 - 2022
- [c5]Ole Jakob Mengshoel, Eirik Lund Flogard, Tong Yu, Jon Riege:
Understanding the cost of fitness evaluation for subset selection: Markov chain analysis of stochastic local search. GECCO 2022: 251-259 - [c4]Eirik Lund Flogard, Ole Jakob Mengshoel, Kerstin Bach:
Creating Dynamic Checklists via Bayesian Case-Based Reasoning: Towards Decent Working Conditions for All. IJCAI 2022: 5108-5114 - [c3]Eirik Lund Flogard, Ole Jakob Mengshoel:
A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments. NeurIPS 2022 - 2021
- [c2]Ole Jakob Mengshoel, Tong Yu, Jon Riege, Eirik Flogard:
Stochastic local search for efficient hybrid feature selection. GECCO Companion 2021: 133-134 - [c1]Eirik Flogard
, Ole Jakob Mengshoel, Kerstin Bach:
Bayesian Feature Construction for Case-Based Reasoning: Generating Good Checklists. ICCBR 2021: 94-109
Data and Artifacts
- 2021
- [d1]Eirik Flogard, Ole Jakob Mengshoel, Kerstin Bach:
Labour Inspection Checklist Content. IEEE DataPort, 2021
Coauthor Index
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