5 citations · 8 across the 8 of their papers we have counts for
4 papers · 1 filter
Starting Positions Matter: A Study on Better Weight Initialization for Neural Network Quantization
Stone Yun, Alexander Wong
Deep neural network (DNN) quantization for fast, efficient inference has been an important tool in limiting the cost of machine learning (ML) model inference. Quantization-specific…
Reproducing BowNet: Learning Representations by Predicting Bags of Visual Words
Harry Nguyen, Stone Yun, Hisham Mohammad
This work aims to reproduce results from the CVPR 2020 paper by Gidaris et al. Self-supervised learning (SSL) is used to learn feature representations of an image using an unlabele…
Do All MobileNets Quantize Poorly? Gaining Insights into the Effect of Quantization on Depthwise Separable Convolutional Networks Through the Eyes of Multi-scale Distributional Dynamics
Stone Yun, Alexander Wong
As the "Mobile AI" revolution continues to grow, so does the need to understand the behaviour of edge-deployed deep neural networks. In particular, MobileNets are the go-to family…
FactorizeNet: Progressive Depth Factorization for Efficient Network Architecture Exploration Under Quantization Constraints
Stone Yun, Alexander Wong
Depth factorization and quantization have emerged as two of the principal strategies for designing efficient deep convolutional neural network (CNN) architectures tailored for low-…