3 papers
cs.LG2025
Mosaic: Composite Projection Pruning for Resource-efficient LLMs
Bailey J. Eccles, Leon Wong, Blesson Varghese
Extensive compute and memory requirements limit the deployment of large language models (LLMs) on any hardware. Compression methods, such as pruning, can reduce model size, which i…
cs.LG2024
Rapid Deployment of DNNs for Edge Computing via Structured Pruning at Initialization
Bailey J. Eccles, Leon Wong, Blesson Varghese
Edge machine learning (ML) enables localized processing of data on devices and is underpinned by deep neural networks (DNNs). However, DNNs cannot be easily run on devices due to t…
cs.LG2023
DNNShifter: An Efficient DNN Pruning System for Edge Computing
Bailey J. Eccles, Philip Rodgers, Peter Kilpatrick +2
Deep neural networks (DNNs) underpin many machine learning applications. Production quality DNN models achieve high inference accuracy by training millions of DNN parameters which…