Research map / Probabilistic and scientific modeling / Molecules and proteins
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Tucker decomposition (BPTD) instead of CP decomposition (BPTF) with matched factor count | BPTD · ICEWS/GDELT, most active 15 countries held out | inverse perplexity | Helped |
| Hold out the remaining (sparse) elements instead of the most active countries | BPTD vs BPTF · ICEWS/GDELT, complement mask | inverse perplexity | No clear effect |
| Mixed-membership (BPTD/BPTF) versus single-membership (GPIRM/DCGPIRM) models | BPTD · Highly dispersed held-out elements | inverse perplexity | Helped |
| Shrinkage priors to infer number of communities and topics from C=50, K=8, R=3 | BPTD · ICEWS 1995-2000 | number of latent classes: 50 -> 20 | Helped |
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