Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards

1 code implementation • 17 Dec 2021 • Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low

This paper presents a novel collaborative generative modeling (CGM) framework that incentivizes collaboration among self-interested parties to contribute data to a pool for training a generative model (e. g., GAN), from which synthetic data are drawn and distributed to the parties as rewards commensurate to their contributions.

BIG-bench Machine Learning Data Valuation +1