Hao Zhang

Orcid: 0000-0002-6769-2115

Affiliations:
  • Harbin Institute of Technology, School of Computer Science and Technology, China
  • University of Science and Technology of China, Hefei, China (PhD 2014)


According to our database1, Hao Zhang authored at least 24 papers between 2013 and 2024.

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

Timeline

Legend:

Book 
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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
CC-FedAvg: Computationally Customized Federated Averaging.
IEEE Internet Things J., February, 2024

DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination.
IEEE Trans. Multim., 2024

DB-RNN: An RNN for Precipitation Nowcasting Deblurring.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

2023
MS-LSTM: Exploring spatiotemporal multiscale representations in video prediction domain.
Appl. Soft Comput., November, 2023

Dynamic adaptive workload offloading strategy in mobile edge computing networks.
Comput. Networks, September, 2023

FedCos: A Scene-Adaptive Enhancement for Federated Learning.
IEEE Internet Things J., March, 2023

MM-RNN: A Multimodal RNN for Precipitation Nowcasting.
IEEE Trans. Geosci. Remote. Sens., 2023

Data-Augmentation-Based Federated Learning.
IEEE Internet Things J., 2023

Dynamic layer-wise sparsification for distributed deep learning.
Future Gener. Comput. Syst., 2023

ACIGS: An automated large-scale crops image generation system based on large visual language multi-modal models.
Proceedings of the 20th Annual IEEE International Conference on Sensing, 2023

NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
PrecipLSTM: A Meteorological Spatiotemporal LSTM for Precipitation Nowcasting.
IEEE Trans. Geosci. Remote. Sens., 2022

Focal Frame Loss: A Simple but Effective Loss for Precipitation Nowcasting.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

CCFL: Computationally Customized Federated Learning.
CoRR, 2022

DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination.
CoRR, 2022

MS-RNN: A Flexible Multi-Scale Framework for Spatiotemporal Predictive Learning.
CoRR, 2022

FedCos: A Scene-adaptive Federated Optimization Enhancement for Performance Improvement.
CoRR, 2022

Aperiodic Local SGD: Beyond Local SGD.
Proceedings of the 51st International Conference on Parallel Processing, 2022

STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2015
Mobile cloud computing based privacy protection in location-based information survey applications.
Secur. Commun. Networks, 2015

2014
The Optimal Noise Distribution for Privacy Preserving in Mobile Aggregation Applications.
Int. J. Distributed Sens. Networks, 2014

Towards optimal noise distribution for privacy preserving in data aggregation.
Comput. Secur., 2014

2013
Distributed Hash Table - Theory, Platforms and Applications.
Springer Briefs in Computer Science, Springer, ISBN: 978-1-4614-9008-1, 2013

Toward Optimal Additive Noise Distribution for Privacy Protection in Mobile Statistics Aggregation.
Proceedings of the 2013 IEEE International Conference on Green Computing and Communications (GreenCom) and IEEE Internet of Things (iThings) and IEEE Cyber, 2013


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