Yuxuan Cai

Affiliations:
  • Northeastern University, Boston, MA, USA


According to our database1, Yuxuan Cai authored at least 14 papers between 2020 and 2022.

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

2022
Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework.
ACM Trans. Embed. Comput. Syst., September, 2022

Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration.
ACM Trans. Design Autom. Electr. Syst., 2022

2021
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search.
CoRR, 2021

Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search.
Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021

Work in Progress: Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework.
Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021

Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI.
Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

Neural Pruning Search for Real-Time Object Detection of Autonomous Vehicles.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

NPAS: A Compiler-Aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Real-Time Mobile Acceleration of DNNs: From Computer Vision to Medical Applications.
Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021

A Compression-Compilation Co-Design Framework Towards Real-Time Object Detection on Mobile Devices.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device.
CoRR, 2020

6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.
CoRR, 2020


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