Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning

Published:2023 Issue: Volume:11 Page:42796-42808
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Gomrokchi Maziar¹^ORCID,Amin Susan²^ORCID,Aboutalebi Hossein³,Wong Alexander⁴^ORCID,Precup Doina¹

Affiliation:

1. Department of Computer Science, McGill University, Montréal, Canada

2. Mila-Québec AI Institute, Montréal, Canada

3. VIP Laboratory, Cheriton School of Computer Science, University of Waterloo, Waterloo, Canada

4. DarwinAI Corporation, Waterloo, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10108924.pdf?arnumber=10108924

Reference53 articles.

1. Revisiting fundamentals of experience replay;fedus;Proc Int Conf Mach Learn,2020

2. The Effects of Memory Replay in Reinforcement Learning

3. Exposed! A Survey of Attacks on Private Data

4. Hybrid algorithms based on combining reinforcement learning and metaheuristic methods to solve global optimization problems

5. The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

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