A Survey of Privacy-Preserving Methods Across Vertically Partitioned Data

By Jaideep Vaidya. 2008

50 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Philip S. Yu
2. Benjamin C. M. Fung
3. Yang Liu
4. Rui Chen
5. Qiang Yang
6. Ke Wang
7. Tianjian Chen
8. Charu C. Aggarwal

In Management Science and Operations Research

1. Philip S. Yu
2. Ke Wang
3. Benjamin C. M. Fung
4. Tianjian Chen
5. Qiang Yang
6. Tao Fan
7. Kewei Cheng
8. Yang Liu

Citations in the corpus

• SecureBoost: A Lossless Federated Learning Framework (2019, background): “Unlike the situation where the data are horizontally split, the above setting requires a more complex mechanism to decompose the loss function at each party (Vaidya 2008; Vaidya and Clifton 2005; Hardy et al. 2017).”
• Privacy-preserving data publishing: A survey of recent developments (2010, methodology): “We refer readers interested in PPDDM to work by [Clifton et al. 2002; Kantarcioglu 2008; Pinkas 2002; Vaidya 2008; Wright et al. 2005].”