Robust learning from untrusted sources

N.H. Konstantinov, C. Lampert, in:, Proceedings of the 36th International Conference on Machine Learning, n.d.

Conference Paper | Submitted | English
Department
Abstract
Modern machine learning methods often require more data for training than a single expert can provide. Therefore, it has become a standard procedure to collect data from external sources, e.g. via crowdsourcing. Unfortunately, the quality of these sources is not always guaranteed. As additional complications, the data might be stored in a distributed way, or might even have to remain private. In this work, we address the question of how to learn robustly in such scenarios. Studying the problem through the lens of statistical learning theory, we derive a procedure that allows for learning from all available sources, yet automatically suppresses irrelevant or corrupted data. We show by extensive experiments that our method provides significant improvements over alternative approaches from robust statistics and distributed optimization.
Publishing Year
Date Published
2019-06-01
Proceedings Title
Proceedings of the 36th International Conference on Machine Learning
Conference
ICML: International Conference on Machine Learning
Conference Location
Long Beach, CA, USA
Conference Date
2019-06-10 – 2919-06-15
IST-REx-ID

Cite this

Konstantinov NH, Lampert C. Robust learning from untrusted sources. In: Proceedings of the 36th International Conference on Machine Learning.
Konstantinov, N. H., & Lampert, C. (n.d.). Robust learning from untrusted sources. In Proceedings of the 36th International Conference on Machine Learning. Long Beach, CA, USA.
Konstantinov, Nikola H, and Christoph Lampert. “Robust Learning from Untrusted Sources.” In Proceedings of the 36th International Conference on Machine Learning, n.d.
N. H. Konstantinov and C. Lampert, “Robust learning from untrusted sources,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, USA.
Konstantinov NH, Lampert C. Robust learning from untrusted sources. Proceedings of the 36th International Conference on Machine Learning. ICML: International Conference on Machine Learning
Konstantinov, Nikola H., and Christoph Lampert. “Robust Learning from Untrusted Sources.” Proceedings of the 36th International Conference on Machine Learning.

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