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02/16/2023
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification
We introduce Meta-Album, an image classification meta-dataset designed t...
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01/16/2023
PyExperimenter: Easily distribute experiments and track results
PyExperimenter is a tool to facilitate the setup, documentation, executi...
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06/15/2022
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification
Although deep neural networks are capable of achieving performance super...
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01/28/2022
Learning Curves for Decision Making in Supervised Machine Learning – A Survey
Learning curves are a concept from social sciences that has been adopted...
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11/29/2021
Naive Automated Machine Learning
An essential task of Automated Machine Learning (AutoML) is the problem ...
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11/27/2021
Fast and Informative Model Selection using Learning Curve Cross-Validation
Common cross-validation (CV) methods like k-fold cross-validation or Mon...
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11/10/2021
Towards Green Automated Machine Learning: Status Quo and Future Directions
Automated machine learning (AutoML) strives for the automatic configurat...
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09/10/2021
Automated Machine Learning, Bounded Rationality, and Rational Metareasoning
The notion of bounded rationality originated from the insight that perfe...
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03/18/2021
Naive Automated Machine Learning – A Late Baseline for AutoML
Automated Machine Learning (AutoML) is the problem of automatically find...
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03/02/2021
Single and Parallel Machine Scheduling with Variable Release Dates
In this paper we study a simple extension of the total weighted flowtime...
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07/06/2020
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
Algorithm selection (AS) deals with the automatic selection of an algori...
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11/09/2018
Automated Multi-Label Classification based on ML-Plan
Automated machine learning (AutoML) has received increasing attention in...
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09/03/2018