Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Bayesian Boolean Matrix Factorisation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use OrM instead of message passing | Boolean matrix completion · MovieLens 100K, 1%–95% observed | accuracy: 58.5 vs 52.8 (1%); 70.0 vs 69.5 (95%) | Helped |
| Use OrM instead of message passing | Boolean matrix completion · MovieLens 1M, 1%–50% observed | accuracy: 63.4 vs 56.7 (1%); 70.9 vs 70.7 (50%) | Helped |
| Use OrM instead of message passing | Boolean matrix completion · MovieLens 1M, 95% observed | accuracy: 71.2 vs 71.5 | Hurt |
| Stack two OrMachine layers (sizes 4 and 2) (ablation) | OrM · MovieLens 100K and 1M | accuracy: 100K: 58.5, 63.5, 65.2, 66.5, 68.8, 70.1; 1M: 63.8, 67.2, 68.6, 70.0, 71.4, 72.1 | Mixed |
| Increase the latent dimension to 3 or 4 (ablation) | OrM · MovieLens matrix completion | accuracy | No clear effect |
| Use a three-hidden-layer architecture of widths 7, 4, and 2 instead of a single layer of width 7 (ablation) | OrM · Calculator digits with 70% missing | reconstruction error: 1.4% to 0.4% | Helped |
Closest papers by meaning
- Probabilistic Boolean Tensor Decomposition (ICML 2018 · similarity 0.90)
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- Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent (NeurIPS 2022 · similarity 0.88)
- Sampling Binary Data by Denoising through Score Functions (ICML 2025 · similarity 0.83)
- Federated Binary Matrix Factorization Using Proximal Optimization (AAAI 2025 · similarity 0.83)
- Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction (ICLR 2025 · similarity 0.82)
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