8 citations · 21 across the 10 of their papers we have counts for
3 papers · 1 filter
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices
Sahidul Islam, Jieren Deng, Shanglin Zhou +3
Energy harvesting (EH) IoT devices that operate intermittently without batteries, coupled with advances in deep neural networks (DNNs), have opened up new opportunities for enablin…
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm
Shaoyi Huang, Dongkuan Xu, Ian E. H. Yen +8
Conventional wisdom in pruning Transformer-based language models is that pruning reduces the model expressiveness and thus is more likely to underfit rather than overfit. However,…
Binary Complex Neural Network Acceleration on FPGA
Hongwu Peng, Shanglin Zhou, Scott Weitze +9
Being able to learn from complex data with phase information is imperative for many signal processing applications. Today' s real-valued deep neural networks (DNNs) have shown effi…