Auditing for Federated Learning: A Model Elicitation Approach

Author:

Liu Yang1ORCID,Lou Rixing2ORCID,Wei Jiaheng1ORCID

Affiliation:

1. University of California, Santa Cruz, United States

2. California State University, Monterey Bay, United States

Funder

National Science Foundation

Publisher

ACM

Reference53 articles.

1. Jacob D Abernethy and Rafael M Frongillo. 2011. A collaborative mechanism for crowdsourcing prediction problems. In Advances in Neural Information Processing Systems. 2600–2608. Jacob D Abernethy and Rafael M Frongillo. 2011. A collaborative mechanism for crowdsourcing prediction problems. In Advances in Neural Information Processing Systems. 2600–2608.

2. Dan Alistarh , Zeyuan Allen-Zhu , and Jerry Li. 2018. Byzantine stochastic gradient descent. Advances in Neural Information Processing Systems 31 ( 2018 ). Dan Alistarh, Zeyuan Allen-Zhu, and Jerry Li. 2018. Byzantine stochastic gradient descent. Advances in Neural Information Processing Systems 31 (2018).

3. Dan Alistarh , Jerry Li , Ryota Tomioka , and Milan Vojnovic . 2016 . Qsgd: Randomized quantization for communication-optimal stochastic gradient descent. arXiv preprint arXiv:1610.02132 1 (2016). Dan Alistarh, Jerry Li, Ryota Tomioka, and Milan Vojnovic. 2016. Qsgd: Randomized quantization for communication-optimal stochastic gradient descent. arXiv preprint arXiv:1610.02132 1 (2016).

4. Convexity, Classification, and Risk Bounds

5. Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds

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