activity
20182020
most citedDeep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going

77 citations · 99 across the 4 of their papers we have counts for

collaborators

6 papers

physics.optics202015 cited

Dynamic control of mode modulation and spatial multiplexing using hybrid metasurfaces

Zemeng Lin, Lingling Huang, Ruizhe Zhao +4

Designing reconfigurable metasurfaces that can dynamically control scattered electromagnetic waves and work in the near-infrared (NIR) and optical regimes remains a challenging tas…

cs.LG20191 cited

Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling

Daniel Stoller, Mi Tian, Sebastian Ewert +1

Convolutional neural networks (CNNs) with dilated filters such as the Wavenet or the Temporal Convolutional Network (TCN) have shown good results in a variety of sequence modelling…

cs.LG20196 cited

Adaptive Loss Scaling for Mixed Precision Training

Ruizhe Zhao, Brian Vogel, Tanvir Ahmed

Mixed precision training (MPT) is becoming a practical technique to improve the speed and energy efficiency of training deep neural networks by leveraging the fast hardware support…

cs.CV201977 cited

Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going

Erwei Wang, James J. Davis, Ruizhe Zhao +5

Deep neural networks have proven to be particularly effective in visual and audio recognition tasks. Existing models tend to be computationally expensive and memory intensive, howe…

cs.CV2018

Efficient Structured Pruning and Architecture Searching for Group Convolution

Ruizhe Zhao, Wayne Luk

Efficient inference of Convolutional Neural Networks is a thriving topic recently. It is desirable to achieve the maximal test accuracy under given inference budget constraints whe…

cs.CV2018

Towards Efficient Convolutional Neural Network for Domain-Specific Applications on FPGA

Ruizhe Zhao, Ho-Cheung Ng, Wayne Luk +1

FPGA becomes a popular technology for implementing Convolutional Neural Network (CNN) in recent years. Most CNN applications on FPGA are domain-specific, e.g., detecting objects fr…