Ruizhou Ding

Orcid: 0000-0002-6357-6723

According to our database1, Ruizhou Ding authored at least 21 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Efficient Test Chip Design via Smart Computation.
ACM Trans. Design Autom. Electr. Syst., March, 2023

QUIDAM: A Framework for Quantization-aware DNN Accelerator and Model Co-Exploration.
ACM Trans. Embed. Comput. Syst., March, 2023

2022
QADAM: Quantization-Aware DNN Accelerator Modeling for Pareto-Optimality.
CoRR, 2022

QAPPA: Quantization-Aware Power, Performance, and Area Modeling of DNN Accelerators.
CoRR, 2022

2020
Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization.
IEEE J. Sel. Top. Signal Process., 2020

ViP: Virtual Pooling for Accelerating CNN-based Image Classification and Object Detection.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Towards Efficient Model Compression via Learned Global Ranking.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Single-Path NAS: Device-Aware Efficient ConvNet Design.
CoRR, 2019

LeGR: Filter Pruning via Learned Global Ranking.
CoRR, 2019

Single-Path NAS: Designing Hardware-Efficient ConvNets in Less Than 4 Hours.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

AdaScale: Towards Real-time Video Object Detection using Adaptive Scaling.
Proceedings of Machine Learning and Systems 2019, 2019

IPSA: Integer Programming via Sparse Approximation for Efficient Test-Chip Design.
Proceedings of the 37th IEEE International Conference on Computer Design, 2019

FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019

Regularizing Activation Distribution for Training Binarized Deep Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Lightening the Load with Highly Accurate Storage- and Energy-Efficient LightNNs.
ACM Trans. Reconfigurable Technol. Syst., 2018

Understanding the Impact of Label Granularity on CNN-Based Image Classification.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Quantized deep neural networks for energy efficient hardware-based inference.
Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018

2017
LightNN: Filling the Gap between Conventional Deep Neural Networks and Binarized Networks.
Proceedings of the on Great Lakes Symposium on VLSI 2017, 2017

Leveraging Classification Models for River Forecasting.
Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017

Enhancing precipitation models by capturing multivariate and multiscale climate dynamics.
Proceedings of the 3rd International Workshop on Cyber-Physical Systems for Smart Water Networks, 2017

2015
Roadside-unit caching in vehicular ad hoc networks for efficient popular content delivery.
Proceedings of the 2015 IEEE Wireless Communications and Networking Conference, 2015


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