Prof. Jie Ding Profile

Prof. Jie Ding

at Univ of Minnesota Twin Cities

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Proceedings Article | 12 April 2021 Presentation

Assisted learning: cooperative AI with autonomy

Jiaying Zhou, Xun Xian, Na Li, Jie Ding

Proceedings Volume 11746, 117461P (2021) https://doi.org/10.1117/12.2586887

KEYWORDS: Artificial intelligence, Data modeling, Performance modeling, Neural networks, Computer security

Read Abstract +

The rapid development in data collecting devices and computation platforms produces an emerging number of agents, each equipped with a unique data modality over a particular population of subjects. While an agent’s predictive performance may be enhanced by transmitting others’ data to it, this is often unrealistic due to intractable transmission costs and security concerns. In this paper, we propose a method named ASCII for an agent to improve its classification performance through assistance from other agents, without sharing proprietary data and model information. The method is naturally suitable for privacy-aware, transmission-economical, and decentralized learning scenarios. The method is also general as it allows the agents to use arbitrary classifiers such as logistic regression, ensemble tree, and neural network, and they may be heterogeneous among agents. We demonstrate the proposed method with extensive experimental studies.

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