Communication efficient privacy-preserving distributed optimization using adaptive differential quantization

Privacy, accuracy and communication efficiency are major concerns in distributed computing systems and they are achieved simultaneously with the proposed approach. Information theoretical privacy-preserving methods often incur a privacy and communication bandwidth trade-off. The connection of quantization and privacy-preservation is established with adaptive differential quantization. Accuracy is not compromised by considering communication efficiency and privacy. The result is of high practical values.