Minh Tang
Biographic Data
| ID | 4163899 |
|---|---|
| NAME | Minh Tang |
| GIVEN NAMES | Minh |
| FAMILY NAME | Tang |
| SIGNATURE | TANG M |
| ORCID | 0000-0003-1420-7187 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 0 |
On spectral embedding performance and elucidating network structure in stochastic blockmodel graphs
Statistical inference on graphs often proceeds via spectral methods involving low-dimensional embeddings of matrix-valued graph representations such as the graph Laplacian or adjacency matrix. In this paper, we analyze the asymptotic information-theoretic relative performance of Laplacian spectral embedding and adjacency spectral embedding for block assignment recovery in stochastic blockmodel graphs by way of Chernoff information. We investigate…
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On spectral embedding performance and elucidating network structure in stochastic blockmodel graphs
Statistical inference on graphs often proceeds via spectral methods involving low-dimensional embeddings of matrix-valued graph representations such as the graph Laplacian or adjacency matrix. In this paper, we analyze the asymptotic information-theoretic relative performance of Laplacian spectral embedding and adjacency spectral embedding for block assignment recovery in stochastic blockmodel graphs by way of Chernoff information. We investigate…
Adjacency list (1 work) · Adjacency matrix (1 work) · Artificial Intelligence (1 work) · Block (permutation group theory (1 work) · Combinatorics (1 work) · Complex Network Analysis Techniques (1 work) · Computer Science (1 work) · Embedding (1 work) · Graph (1 work) · Graph theory and applications (1 work)