Self-Generating Policies for Machine Learning in Coalition Environments-Reference-Cited by-同舟云学术

Self-Generating Policies for Machine Learning in Coalition Environments

Published:2019 Issue: Volume: Page:42-65
ISSN:0302-9743
Container-title:Policy-Based Autonomic Data Governance
language:
Short-container-title:

Author:

Verma Dinesh,Calo Seraphin,Witherspoon Shonda,Manotas Irene,Bertino Elisa,Jabal Amani M. Abu,Cirincione Greg,Swami Ananthram,Pearson Gavin,de Mel Geeth

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-17277-0_3

Reference15 articles.

1. Rasch, R., Kott, A., Forbus, K.D.: AI on the battlefield: an experimental exploration. In: AAAI/IAAI, pp. 906–912 (2002)

2. Cortes, C., Jackel, L.D., Solla, S.A., Vapnik, V., Denker, J.S.: Learning curves: asymptotic values and rate of convergence. In: Advances in Neural Information Processing Systems, pp. 327–334 (1994)

3. Perlich, C., Provost, F., Simonoff, J.S.: Tree induction vs. logistic regression: a learning-curve analysis. J. Mach. Learn. Res. 4(Jun), 211–255 (2003)

4. Verma, D., et al.: Generative policy model for autonomic management. In: 2017 IEEE SmartWorld, Distributed Analytics InfraStructure and Algorithms for Multi-organization Federations Workshop. IEEE (2017)

5. Cirincione, G., Verma, D., Bertino, E., Swami, A.: Security issues for distributed fusion in coalition environments. In: 2018 21st International Conference on Information Fusion (FUSION), pp. 830–837. IEEE (2018)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Towards Data Governance for Federated Machine Learning;Communications in Computer and Information Science;2022