A Privacy-Preserving Finite-Time Push-Sum based Gradient Method for Distributed Optimization over Digraphs.
Xiaomeng ChenWei JiangThemistoklis CharalambousLing ShiPublished in: CoRR (2023)
Keyphrases
- privacy preserving
- gradient method
- horizontally partitioned data
- horizontally partitioned
- multi party
- optimization methods
- partitioned data
- privacy sensitive
- privacy preserving data mining
- secure multiparty computation
- vertically partitioned data
- privacy preservation
- privacy preserving classification
- data privacy
- convergence rate
- preserving privacy
- optimization problems
- step size
- private data
- optimization method
- privacy concerns
- private information
- privacy preserving association rule mining
- privacy protection
- privacy issues
- distributed data
- sensitive information
- differential privacy
- negative matrix factorization
- scalar product
- optimization algorithm
- machine learning
- peer to peer
- sensitive data
- data sets
- document clustering
- sparse representation