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AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning [article]

Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu
2020 arXiv   pre-print
To bridge the gap, in this paper, we propose AutoOD, an automated outlier detection framework, which aims to search for an optimal neural network model within a predefined search space.  ...  We further introduce an experience replay mechanism based on self-imitation learning to improve the sample efficiency.  ...  AutoOD builds on the theory of curiosity-driven exploration and self-imitation learning.  ... 
arXiv:2006.11321v1 fatcat:sqptlaxro5gb7frxdugtvje46y