output
20182025
most citedTowards Green Automated Machine Learning: Status Quo and Future Directions

50 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing cs.LGShow all

5 papers · 1 filter

cs.LG2025

HKT: A Biologically Inspired Framework for Modular Hereditary Knowledge Transfer in Neural Networks

Yanick Chistian Tchenko, Felix Mohr, Hicham Hadj Abdelkader +1

A prevailing trend in neural network research suggests that model performance improves with increasing depth and capacity - often at the cost of integrability and efficiency. In th…

cs.LG2023★ 5 cited

RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network

Haozhe Sun, Isabelle Guyon, Felix Mohr +1

It has become mainstream in computer vision and other machine learning domains to reuse backbone networks pre-trained on large datasets as preprocessors. Typically, the last layer…

cs.LG2022★ 35 cited

Learning Curves for Decision Making in Supervised Machine Learning: A Survey

Felix Mohr, Jan N. van Rijn

Learning curves are a concept from social sciences that has been adopted in the context of machine learning to assess the performance of a learning algorithm with respect to a cert…

cs.LG2021★ 50 cited

Towards Green Automated Machine Learning: Status Quo and Future Directions

Tanja Tornede, Alexander Tornede, Jonas Hanselle +3

Automated machine learning (AutoML) strives for the automatic configuration of machine learning algorithms and their composition into an overall (software) solution - a machine lea…

cs.LG2020★ 6 cited

Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis

Alexander Tornede, Marcel Wever, Stefan Werner +2

Algorithm selection (AS) deals with the automatic selection of an algorithm from a fixed set of candidate algorithms most suitable for a specific instance of an algorithmic problem…