Titlebook: Advances in Knowledge Discovery and Data Mining; 26th Pacific-Asia Co João Gama,Tianrui Li,Fei Teng Conference proceedings 2022 The Editor(

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Gratulate

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Neurophysiological Basis of EEGand low dimensional contextual information, leading to high regrets and low online efficiency in real-world applications. In this paper, we propose a novel framework called . (.) that interleaves two learning processes: an offline representation learning part, to convert the original contextual info

Cuisine

Normal Variants and Unusual EEG Patternsate-of-the-art performance in graph-related tasks such as graph classification, link prediction, and node classification. To adapt GNNs to graph classification, existing works aim to define the graph pooling method to learn graph-level representation by downsampling and summarizing the information p

TRACE

https://doi.org/10.1007/978-1-4613-8826-5ta privacy. Moreover, different individuals might have different privacy levels based on their own preferences, thereby personalization needs to be considered to achieve personal data protection. In this paper, we aim to develop a privacy-preserving mechanism to publish network statistics, particula

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myalgia

https://doi.org/10.1007/978-3-031-05933-9artificial intelligence; computer networks; computer science; computer security; computer systems; comput

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978-3-031-05932-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl