11 citations · 16 across the 13 of their papers we have counts for
4 papers · 1 filter
EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models
Xinlin Li, Mariana Parazeres, Adam Oberman +3
With the advent of deep learning application on edge devices, researchers actively try to optimize their deployments on low-power and restricted memory devices. There are establish…
DenseShift: Towards Accurate and Efficient Low-Bit Power-of-Two Quantization
Xinlin Li, Bang Liu, Rui Heng Yang +3
Efficiently deploying deep neural networks on low-resource edge devices is challenging due to their ever-increasing resource requirements. To address this issue, researchers have p…
Low-bit Shift Network for End-to-End Spoken Language Understanding
Anderson R. Avila, Khalil Bibi, Rui Heng Yang +3
Deep neural networks (DNN) have achieved impressive success in multiple domains. Over the years, the accuracy of these models has increased with the proliferation of deeper and mor…
Deep Neural Networks pruning via the Structured Perspective Regularization
Matteo Cacciola, Antonio Frangioni, Xinlin Li +1
In Machine Learning, Artificial Neural Networks (ANNs) are a very powerful tool, broadly used in many applications. Often, the selected (deep) architectures include many layers, an…