Enhancing Robustness of On-line Learning Models on Highly Noisy Data-Reference-Cited by-同舟云学术

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Enhancing Robustness of On-line Learning Models on Highly Noisy Data

Published:2021 Issue: Volume: Page:1-1
ISSN:1545-5971
Container-title:IEEE Transactions on Dependable and Secure Computing
language:
Short-container-title:IEEE Trans. Dependable and Secure Comput.

Author:

Zhao Zilong,Birke Robert,Han Rui,Robu Bogdan,Bouchenak Sara,Ben Mokhtar Sonia,Chen Lydia Y.

Funder

National Natural Science Foundation of China

Agence Nationale de la Recherche

Schweizerischer Nationalfonds zur Frderung der Wissenschaftlichen Forschung

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8858/4358699/09369874.pdf?arnumber=9369874

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4. Modelling and Optimal Control of MIMO System - France Macroeconomic Model Case*;2023 European Control Conference (ECC);2023-06-13

5. Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection;Machine Learning and Knowledge Discovery in Databases: Research Track;2023

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