Transfer learning from informative source networks improves target DCMM estimation accuracy by enlarging the eigenvalue gap of the connection probability matrix, with algorithms to avoid negative transfer.
Advances in neural information processing systems , volume=
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Transfer Learning for Degree-Corrected Mixed Membership Network Models
Transfer learning from informative source networks improves target DCMM estimation accuracy by enlarging the eigenvalue gap of the connection probability matrix, with algorithms to avoid negative transfer.