A nonconvex l1/2-regularized nonnegative matrix factorization method with ADMM solver and detection estimation improves sparse network recovery under imperfect observations compared to baselines.
Connecting the dots: Identifying network structure via graph signal processing,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
The paper derives feedback conditions that violate topology identifiability for partial and full observations and proposes a distributed design that trades consensus deviation against topology privacy under limited budgets.
citing papers explorer
-
Sparse Network Inference under Imperfect Detection and its Application to Ecological Networks
A nonconvex l1/2-regularized nonnegative matrix factorization method with ADMM solver and detection estimation improves sparse network recovery under imperfect observations compared to baselines.
-
Preserving Topology Privacy of Network Systems by Feedback: Conditions and Distributed Design
The paper derives feedback conditions that violate topology identifiability for partial and full observations and proposes a distributed design that trades consensus deviation against topology privacy under limited budgets.