Approximate to Be Great: Communication Efficient and Privacy-Preserving Large-Scale Distributed Deep Learning in Internet of Things.
Wei DuAng LiPan ZhouZichuan XuXiumin WangHao JiangDapeng Oliver WuPublished in: IEEE Internet Things J. (2020)
Keyphrases
- privacy preserving
- deep learning
- multi party
- horizontally partitioned data
- partitioned data
- privacy preserving data mining
- privacy preservation
- horizontally partitioned
- vertically partitioned data
- privacy sensitive
- communication cost
- private information
- data privacy
- sensitive information
- privacy protection
- unsupervised learning
- secure multiparty computation
- privacy preserving classification
- privacy concerns
- record linkage
- machine learning
- private data
- data mining
- preserving privacy
- privacy issues
- differential privacy
- distributed data
- information retrieval
- real world
- sensitive data
- personal information
- distributed environment
- support vector