Jiawei Guan

Orcid: 0000-0002-7538-9722

According to our database1, Jiawei Guan authored at least 13 papers between 2020 and 2025.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2025
A Systematic Study on Early Stopping Metrics in HPO and the Implications of Uncertainty.
Proc. VLDB Endow., February, 2025

Breaking the Edge: Enabling Efficient Neural Network Inference on Integrated Edge Devices.
IEEE Trans. Cloud Comput., 2025

2024
Enabling Efficient Deep Learning on MCU With Transient Redundancy Elimination.
IEEE Trans. Computers, December, 2024

HocoPG: A Database System with Homomorphic Compression for Text Processing.
Proc. VLDB Endow., August, 2024

Improving Graph Compression for Efficient Resource-Constrained Graph Analytics.
Proc. VLDB Endow., May, 2024

UQ-Guided Hyperparameter Optimization for Iterative Learners.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023
Homomorphic Compression: Making Text Processing on Compression Unlimited.
Proc. ACM Manag. Data, December, 2023

Expanding the Edge: Enabling Efficient Winograd CNN Inference With Deep Reuse on Edge Device.
IEEE Trans. Knowl. Data Eng., October, 2023

CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression.
Proc. ACM Manag. Data, 2023

Space-Efficient TREC for Enabling Deep Learning on Microcontrollers.
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022
DREW: Efficient Winograd CNN Inference with Deep Reuse.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

TREC: Transient Redundancy Elimination-based Convolution.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020
Residual network with detail perception loss for single image super-resolution.
Comput. Vis. Image Underst., 2020


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