A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), pp. 9777-9787, 2019.
supervised learningsemi-supervised learningrandom guess
In this paper, we proposed a general framework for data poisoning attacks to graph-based semi-supervised learning (G-SSL). In this framework, we first unify different tasks, goals and constraints into a single formula for data poisoning attack in G-SSL, then we propose two specialized algorithms to efficiently solve two important cases - ...More
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