Hypergraph Structure Evolution

نویسندگان

چکیده

Abstract In practice, noise exists in the process of data collection and hypergraph construction. Therefore, missing, abundant, noisy connections may be introduced into generated structure, which lead to inaccurate inference on hypergraph. Another issue comes from increasing stream, is also very common many applications. It important consider structure evolution methods hypergraph, optimize accordingly. Early computation mainly rely static suffer limitation mechanism when confronting random scenarios. this chapter, we introduce dynamic methods, including both component optimization optimization. Finally, briefly incremental learning method growing data.

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ژورنال

عنوان ژورنال: Artificial intelligence: Foundations, theory, and algorithms

سال: 2023

ISSN: ['2365-3051', '2365-306X']

DOI: https://doi.org/10.1007/978-981-99-0185-2_6