Toward Optimal Additive Noise Distribution for Privacy Protection in Mobile Statistics Aggregation. - Hao Zhang 016; Yonggang Wen 001; Honggang Hu; Nenghai Yu (GreenCom/iThings/CPScom, 2013)

Distributed Hash Table - Theory, Platforms and Applications. - Hao Zhang 016; Yonggang Wen 001; Haiyong Xie 001; Nenghai Yu (Springer, 2013)

Towards optimal noise distribution for privacy preserving in data aggregation. - Hao Zhang 016; Nenghai Yu; Yonggang Wen 001; Weiming Zhang 001 (Comput. Secur., 2014)

The Optimal Noise Distribution for Privacy Preserving in Mobile Aggregation Applications. - Hao Zhang 016; Nenghai Yu; Honggang Hu (Int. J. Distributed Sens. Networks, 2014)

Mobile cloud computing based privacy protection in location-based information survey applications. - Hao Zhang 016; Nenghai Yu; Yonggang Wen 001 (Secur. Commun. Networks, 2015)

STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing. - Tingting Wu; Xiao Ding; Minji Tang; Hao Zhang 016; Bing Qin 001; Ting Liu 001 (EMNLP, 2022)

Aperiodic Local SGD: Beyond Local SGD. - Hao Zhang 016; Tingting Wu; Siyao Cheng; Jie Liu 001 (ICPP, 2022)

FedCos: A Scene-adaptive Federated Optimization Enhancement for Performance Improvement. - Hao Zhang 016; Tingting Wu; Siyao Cheng; Jie Liu 001 (CoRR, 2022)

MS-RNN: A Flexible Multi-Scale Framework for Spatiotemporal Predictive Learning. - Zhifeng Ma; Hao Zhang 016; Jie Liu 001 (CoRR, 2022)

DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination. - Tingting Wu; Xiao Ding; Hao Zhang 016; Jinglong Gao; Li Du; Bing Qin 001; Ting Liu 001 (CoRR, 2022)

CCFL: Computationally Customized Federated Learning. - Hao Zhang 016; Tingting Wu; Siyao Cheng; Jie Liu 001 (CoRR, 2022)

Focal Frame Loss: A Simple but Effective Loss for Precipitation Nowcasting. - Zhifeng Ma; Hao Zhang 016; Jie Liu 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

PrecipLSTM: A Meteorological Spatiotemporal LSTM for Precipitation Nowcasting. - Zhifeng Ma; Hao Zhang 016; Jie Liu 001 (IEEE Trans. Geosci. Remote. Sens., 2022)

NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing. - Tingting Wu; Xiao Ding; Minji Tang; Hao Zhang 016; Bing Qin 001; Ting Liu 001 (ACL (Findings), 2023)

ACIGS: An automated large-scale crops image generation system based on large visual language multi-modal models. - Bolong Liu; Hao Zhang 016; Jie Liu 001; Qiang Wang 001 (SECON, 2023)

Dynamic layer-wise sparsification for distributed deep learning. - Hao Zhang 016; Tingting Wu; Zhifeng Ma; Feng Li; Jie Liu 001 (Future Gener. Comput. Syst., 2023)

Data-Augmentation-Based Federated Learning. - Hao Zhang 016; Qingying Hou; Tingting Wu; Siyao Cheng; Jie Liu 001 (IEEE Internet Things J., 2023)

MM-RNN: A Multimodal RNN for Precipitation Nowcasting. - Zhifeng Ma; Hao Zhang 016; Jie Liu 001 (IEEE Trans. Geosci. Remote. Sens., 2023)

FedCos: A Scene-Adaptive Enhancement for Federated Learning. - Hao Zhang 016; Tingting Wu; Siyao Cheng; Jie Liu 001 (IEEE Internet Things J., 2023)

Dynamic adaptive workload offloading strategy in mobile edge computing networks. - Yinlong Li; Siyao Cheng; Hao Zhang 016; Jie Liu 001 (Comput. Networks, 2023)

MS-LSTM: Exploring spatiotemporal multiscale representations in video prediction domain. - Zhifeng Ma; Hao Zhang 016; Jie Liu 001 (Appl. Soft Comput., 2023)

Federated Edge Learning with Blurred or Pseudo Data Sharing. - Yinlong Li; Hao Zhang 016; Siyao Cheng; Jie Liu 001 (ICPP, 2024)

StressViT: Splitting and Compressing Vision Transformer Through Edge-Cloud Collaboration. - Changyao Lin; Yi Liu; Xiangyu Li; Chengxiang Li; Hao Zhang 016; Jing Jin; Jie Liu 001 (ICPR (5), 2024)

Uncertainty-guided label correction with wavelet-transformed discriminative representation enhancement. - Tingting Wu; Xiao Ding; Hao Zhang 016; Minji Tang; Bing Qin 001; Ting Liu 001 (Neural Networks, 2024)

DB-RNN: An RNN for Precipitation Nowcasting Deblurring. - Zhifeng Ma; Hao Zhang 016; Jie Liu 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination. - Tingting Wu; Xiao Ding; Hao Zhang 016; Jinglong Gao; Minji Tang; Li Du; Bing Qin 001; Ting Liu 001 (IEEE Trans. Multim., 2024)

CC-FedAvg: Computationally Customized Federated Averaging. - Hao Zhang 016; Tingting Wu; Siyao Cheng; Jie Liu 001 (IEEE Internet Things J., 2024)

A Stackelberg-Game-Based Framework for Edge Pricing and Resource Allocation in Mobile Edge Computing. - Siyao Cheng; Tian Ren; Hao Zhang 016; Jiayan Huang; Jie Liu 001 (IEEE Internet Things J., 2024)

Dynamic clustered federated learning via adaptive distribution similarity computation. - Tian Ren; Siyao Cheng; Hao Zhang 016; Jie Liu 001 (Comput. Networks, 2025)

Omniveyor: An Assembled Logistics Sorting System Powered by Reinforcement Learning. - Mingrui Yin; Hao Zhang 016; Chenxin Cai; Meiyan Liang; Jie Liu 001 (IEEE Trans Autom. Sci. Eng., 2025)