2025-01-12-selvan25a.md

title	openreview	software	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
PePR: Performance Per Resource Unit as a Metric to Promote Small-scale Deep Learning	Pb47B5t0pr	https://github.com/saintslab/PePR	The recent advances in deep learning (DL) have been accelerated by access to large-scale data and compute. These large-scale resources have been used to train progressively larger models which are resource intensive in terms of compute, data, energy, and carbon emissions. These costs are becoming a new type of entry barrier to researchers and practitioners with limited access to resources at such scale, particularly in the Global South. In this work, we take a comprehensive look at the landscape of existing DL models for medical image analysis tasks and demonstrate their usefulness in settings where resources are limited. To account for the resource consumption of DL models, we introduce a novel measure to estimate the performance per resource unit, which we call the PePR score. Using a diverse family of 131 unique DL architectures (spanning $1M$ to $130M$ trainable parameters) and three medical image datasets, we capture trends about the performance-resource trade-offs. In applications like medical image analysis, we argue that small-scale, specialized models are better than striving for large-scale models. Furthermore, we show that using existing pretrained models that are fine-tuned on new data can significantly reduce the computational resources and data required compared to training models from scratch. We hope this work will encourage the community to focus on improving AI equity by developing methods and models with smaller resource footprints.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	selvan25a	0	Pe{PR}: Performance Per Resource Unit as a Metric to Promote Small-scale Deep Learning	220	229	220-229	220	false	Selvan, Raghavendra and Pepin, Bob and Igel, Christian and Samuel, Gabrielle and Dam, Erik B	given family Raghavendra Selvan given family Bob Pepin given family Christian Igel given family Gabrielle Samuel given family Erik B Dam	2025-01-12		Proceedings of the 6th Northern Lights Deep Learning Conference (NLDL)	265	inproceedings	date-parts 2025 1 12	https://raw.githubusercontent.com/mlresearch/v265/main/assets/selvan25a/selvan25a.pdf