Qin Hua

Orcid: 0000-0003-2846-6083

According to our database1, Qin Hua authored at least 13 papers between 2010 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
V-ABFT: Variance-Based Adaptive Threshold for Fault-Tolerant Matrix Multiplication in Mixed-Precision Deep Learning.
CoRR, February, 2026

GFS: A Preemption-aware Scheduling Framework for GPU Clusters with Predictive Spot Instance Management.
Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

2025
EDGC: Entropy-driven Dynamic Gradient Compression for Efficient LLM Training.
CoRR, November, 2025

Humas: A Heterogeneity- and Upgrade-Aware Microservice Auto-Scaling Framework in Large-Scale Data Centers.
IEEE Trans. Computers, March, 2025

Mitigating interference of microservices with a scoring mechanism in large-scale clusters.
J. Supercomput., January, 2025

DIJS: A Dual Interference-Aware Job Scheduling Framework for Co-located Data Centers.
Proceedings of the Service-Oriented Computing - 23rd International Conference, 2025

EoT: Evolution of Thoughts for Complex Reasoning Tasks.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2023
Bi-GAE: A Bidirectional Generative Auto-Encoder.
J. Comput. Sci. Technol., June, 2023

KAE-Informer: A Knowledge Auto-Embedding Informer for Forecasting Long-Term Workloads of Microservices.
Proceedings of the ACM Web Conference 2023, 2023

2022
Qore-DL: A QoS-aware joint optimization framework for distributed deep learning training.
J. Syst. Archit., 2022

2020
TouchPass: towards behavior-irrelevant on-touch user authentication on smartphones leveraging vibrations.
Proceedings of the MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking, 2020

2012
Simulation and modeling of radar echo signal.
Proceedings of the 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012

2010
A Novel Method for Training Large Scale E-Business SVM Models in a Grid Computing Environment.
Proceedings of the International Conference on E-Business and E-Government, 2010


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