Research map / Probabilistic and scientific modeling / Variational and generative sampling
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Block CA instead of Shrunken FW or Two-Phase FW | PISM variational inference · Football | ELBO | Helped |
| Use Block CA instead of Frank-Wolfe baselines | PISM variational inference · Football | convergence speed | Helped |
| Initialize Block CA with the Shrunken FW solution (ablation) | Block CA · Football | ELBO | Helped |
| Initialize Block CA with the Two-Phase FW solution (ablation) | Block CA · Football | ELBO | Helped |
| Use different Block CA variants (ablation) | Block CA · Integer facility location | ELBO | No clear effect |
| Use Block CA instead of Shrunken FW or Two-Phase FW | PISM variational inference · Integer facility location | ELBO | Helped |
| Use Block CA instead of Shrunken FW | PISM variational inference · Social graph datasets | ELBO | Helped |
Closest papers by meaning
- Provable Variational Inference for Constrained Log-Submodular Models (NeurIPS 2018 · similarity 0.91)
- Variational Inference in Mixed Probabilistic Submodular Models (NeurIPS 2016 · similarity 0.88)
- Differentiable Learning of Submodular Models (NeurIPS 2017 · similarity 0.88)
- Improved Approximation Algorithms for $k$-Submodular Maximization via Multilinear Extension (ICLR 2025 · similarity 0.88)
- Probabilistic Submodular Maximization in Sub-Linear Time (ICML 2017 · similarity 0.88)
- Online Two-Stage Submodular Maximization (NeurIPS 2025 · similarity 0.87)
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