31 citations · 32 across the 3 of their papers we have counts for
3 papers
CES-KD: Curriculum-based Expert Selection for Guided Knowledge Distillation
Ibtihel Amara, Maryam Ziaeefard, Brett H. Meyer +2
Knowledge distillation (KD) is an effective tool for compressing deep classification models for edge devices. However, the performance of KD is affected by the large capacity gap b…
Efficient Fine-Tuning of Compressed Language Models with Learners
Danilo Vucetic, Mohammadreza Tayaranian, Maryam Ziaeefard +3
Fine-tuning BERT-based models is resource-intensive in memory, computation, and time. While many prior works aim to improve inference efficiency via compression techniques, e.g., p…
Efficient Fine-Tuning of BERT Models on the Edge
Danilo Vucetic, Mohammadreza Tayaranian, Maryam Ziaeefard +3
Resource-constrained devices are increasingly the deployment targets of machine learning applications. Static models, however, do not always suffice for dynamic environments. On-de…