Conveners
Resource-Aware ML: Research Area Meeting
- Sebastian Buschjäger (Lamarr Institute for ML and AI, TU Dortmund)
Description
This session will be split into two halves: In the first half, we present / discuss / review two contributions from Lamarr to resource-aware ML. In the second half, we will focus more on sustainability in computer science in general and how this might shape our research in resource-aware ML@Lamarr.
As machine learning models become increasingly integrated into various applications, the need for resource-aware deployment strategies becomes paramount. One promising approach for optimizing resource consumption is rejection ensembles. Rejection ensembles combine a small model deployed to an edge device with a large model deployed in the cloud, with a rejector tasked to determine the most...
A long, long time ago, in a far away land, some smart people thought about how to connect hardware and machine learning to make ML and hardware more resource-aware. At this time, the term "resource-aware ML" came along. While our roots go back some 10-15 years now, the term "resource-aware ML" only partially reflects the current trend in ML research. In fact, most new projects and ideas...
