Research map / Learning theory and algorithms / Matrix and tensor methods
A Faster Practical Approximation Scheme for the Permanent
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use the Extended Huber nesting bound instead of prior rejection-sampling bounds | rejection sampling for nonnegative matrix permanents · three synthetic matrix classes | running time: at best the improvements are of one order of magnitude | Helped |
| use the Extended Huber bound instead of ADAPART or Huber–Law | rejection sampling for real-world permanents · ENZYMES-g575; CAG-mat72; GD95-c | running time: of an order of magnitude | Helped |
| add sharpening preprocessing (ablation) | Extended Huber rejection sampling · synthetic matrix classes | running time: up to a factor of 20 | Helped |
| use deep bounds rather than depth-0 bounds (ablation) | rejection-sampling schemes with sharpening · synthetic matrix classes | running time | Mixed |
| add sharpening preprocessing (ablation) | Extended Huber rejection sampling · CAG-mat72 | running time | Helped |
| use EXTHUBER-S instead of importance samplers | permanent estimation · Random Lines | estimate stability | Mixed |
| use EXTHUBER-S instead of importance samplers | permanent estimation · Mixed | estimate stability | Helped |
| use EXTHUBER-S instead of importance samplers | permanent estimation · Random Permutations | estimate stability | Hurt |
| use EXTHUBER-S instead of SIS | permanent estimation · Random Entries | convergence speed | Hurt |
| extend Huber’s binary nesting bound to real-valued matrices | Extended Huber upper bound · all nonnegative matrices | upper-bound ratio to Brouwer–Schrijver: < 1.042ⁿ | Hurt |
| use the Extended Huber bound instead of Huber–Law | permanent upper bounding · matrices with entries in [0, 1] | upper bound | Helped |
Closest papers by meaning
- Estimating the Permanent by Nesting Importance Sampling (ICML 2024 · similarity 0.91)
- Simple Randomized Rounding for Max-Min Eigenvalue Augmentation (ICML 2025 · similarity 0.86)
- Fast exact recovery of noisy matrix from few entries: the infinity norm approach (NeurIPS 2025 · similarity 0.85)
- Spectral Perturbation Bounds for Low-Rank Approximation with Applications to Privacy (NeurIPS 2025 · similarity 0.85)
- Symmetric Matrix Completion with ReLU Sampling (ICML 2024 · similarity 0.84)
- Entrywise error bounds for low-rank approximations of kernel matrices (NeurIPS 2024 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.