Research map / Learning theory and algorithms / Submodular and game algorithms
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Local Search instead of Greedy as the offline algorithm | Determinant maximization · GENES | determinant improvement over Greedy: 13% | Helped |
| Use Local Search instead of Greedy as the offline algorithm | Determinant maximization · MNIST | determinant improvement over Greedy: 5% | Helped |
| Use Local Search instead of Greedy for core-set construction | GD aggregation · GENES | determinant improvement over GD/GD: 9.6% | Helped |
| Use Local Search instead of Greedy for core-set construction | GD aggregation · MNIST10 | determinant improvement over GD/GD: 2.5% | Helped |
| Use Local Search instead of Greedy for core-set construction | GD aggregation · MNIST50 | determinant improvement over GD/GD: 1.9% | Helped |
| Use Local Search for both core-set construction and aggregation instead of Greedy | Composable determinant maximization · GENES | determinant improvement over GD/GD: 23% | Helped |
| Use Local Search for both core-set construction and aggregation instead of Greedy | Composable determinant maximization · MNIST10 | determinant improvement over GD/GD: 5.5% | Helped |
| Use Local Search for both core-set construction and aggregation instead of Greedy | Composable determinant maximization · MNIST50 | determinant improvement over GD/GD: 6.0% | Helped |
| Use Local Search instead of LP-based core-set construction | GD aggregation · GENES | determinant improvement over GD/LP: 7.3% | Helped |
| Use Local Search instead of LP-based core-set construction | GD aggregation · MNIST10 | determinant improvement over GD/LP: 1.8% | Helped |
| Use Local Search instead of LP-based core-set construction | GD aggregation · MNIST50 | determinant improvement over GD/LP: 1.4% | Helped |
| Use Local Search instead of Greedy | Offline determinant maximization · GENES and MNIST | runtime: 6.5 times more | Hurt |
Closest papers by meaning
- Composable Coresets for Determinant Maximization: Greedy is Almost Optimal (NeurIPS 2023 · similarity 0.95)
- Faster Greedy MAP Inference for Determinantal Point Processes (ICML 2017 · similarity 0.89)
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- Small coresets via negative dependence: DPPs, linear statistics, and concentration (NeurIPS 2024 · similarity 0.85)
- An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale (ICML 2025 · similarity 0.84)
- Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization (ICLR 2024 · similarity 0.83)
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