Research map / Learning theory and algorithms / Combinatorial and search optimization
Safe Element Screening for Submodular Function Minimization
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 |
|---|---|---|---|
| Add IAES screening to MinNorm | MinNorm · two-moons, p=200 | speedup: 6.8 | Helped |
| Add IAES screening to MinNorm | MinNorm · two-moons, p=400 | speedup: 10.0 | Helped |
| Add IAES screening to MinNorm | MinNorm · two-moons, p=600 | speedup: 9.6 | Helped |
| Add IAES screening to MinNorm | MinNorm · two-moons, p=800 | speedup: 6.8 | Helped |
| Add IAES screening to MinNorm | MinNorm · two-moons, p=1000 | speedup: 7.0 | Helped |
| Add IAES screening to MinNorm | MinNorm · image segmentation, image1 | speedup: 20.19 | Helped |
| Add IAES screening to MinNorm | MinNorm · image segmentation, image2 | speedup: 13.69 | Helped |
| Add IAES screening to MinNorm | MinNorm · image segmentation, image3 | speedup: 30.70 | Helped |
| Add IAES screening to MinNorm | MinNorm · image segmentation, image4 | speedup: 11.96 | Helped |
| Add IAES screening to MinNorm | MinNorm · image segmentation, image5 | speedup: 21.50 | Helped |
| Use AES without IES instead of IAES (ablation) | MinNorm · image segmentation | speedup: 1.12, 1.48, 1.24, 1.15, 1.11 | Mixed |
| Use IES without AES instead of IAES (ablation) | MinNorm · two-moons and image segmentation | speedup: 2.4, 3.6, 3.1, 2.7, 3.7; 6.48, 2.89, 6.27, 5.14, 7.95 | Hurt |
Closest papers by meaning
- Optimal approximation for unconstrained non-submodular minimization (ICML 2020 · similarity 0.90)
- Gradient Methods for Submodular Maximization (NeurIPS 2017 · similarity 0.89)
- Corporate Needs You to Find the Difference: Revisiting Submodular and Supermodular Ratio Optimization Problems (NeurIPS 2025 · similarity 0.88)
- Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy? (ICML 2018 · similarity 0.88)
- Minimizing a Submodular Function from Samples (NeurIPS 2017 · similarity 0.88)
- Non-Monotone DR-Submodular Function Maximization (AAAI 2017 · similarity 0.87)
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.