A Privacy-Preserving Finite-Time Push-Sum-Based Gradient Method for Distributed Optimization Over Digraphs.
Xiaomeng ChenWei JiangThemistoklis CharalambousLing ShiPublished in: IEEE Control. Syst. Lett. (2023)
Keyphrases
- privacy preserving
- gradient method
- horizontally partitioned data
- multi party
- horizontally partitioned
- optimization methods
- partitioned data
- privacy preserving data mining
- privacy sensitive
- privacy preservation
- secure multiparty computation
- vertically partitioned data
- privacy preserving classification
- private information
- optimization problems
- sensitive information
- optimization method
- data privacy
- privacy concerns
- scalar product
- privacy protection
- negative matrix factorization
- optimization algorithm
- convergence rate
- objective function
- privacy preserving association rule mining
- high dimensional
- step size
- private data
- privacy issues
- differential privacy
- evolutionary algorithm
- peer to peer
- simulated annealing
- sensitive data
- data sets