Name
Title | ||
|---|---|---|
A variational inference procedure allowing internal structure for overlapping clusters and deterministic constraints |
Abstract | ||
|---|---|---|
We develop a novel algorithm, called VIP*, for structured variational approximate inference. This algorithm extends known algorithms to allow efficient multiple potential updates for overlapping clusters, and overcomes the difficulties imposed by deterministic constraints. The algorithm's convergence is proven and its applicability demonstrated for genetic linkage analysis. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1613/jair.2028 | J. Artif. Intell. Res. (JAIR) |
Keywords | Field | DocType |
deterministic constraint,internal structure,overlapping cluster,efficient multiple potential updates,variational inference procedure,genetic linkage analysis,novel algorithm,structured variational approximate inference,genetic linkage | Convergence (routing),Cluster (physics),Mathematical optimization,Inference,Genetic linkage analysis,Approximate inference,Artificial intelligence,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
27 | 1 | 1076-9757 |
Citations | PageRank | References |
10 | 0.80 | 12 |
Authors | ||
48 | ||