34 citations · 34 across the 2 of their papers we have counts for
2 papers
cs.CL2023
SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
Arash Ardakani, Altan Haan, Shangyin Tan +4
Transformer-based models, such as BERT and ViT, have achieved state-of-the-art results across different natural language processing (NLP) and computer vision (CV) tasks. However, t…
cs.NE2016★ 34 cited
Sparsely-Connected Neural Networks: Towards Efficient VLSI Implementation of Deep Neural Networks
Arash Ardakani, Carlo Condo, Warren J. Gross
Recently deep neural networks have received considerable attention due to their ability to extract and represent high-level abstractions in data sets. Deep neural networks such as…