test power
SampleTesting
Inrealisticscenarios with very limited numbers of data samples, it can be challenging to identify a kernel powerful enough to distinguish complex distributions.
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- Asia > Middle East > UAE > Abu Dhabi Emirate > Abu Dhabi (0.14)
- Asia > China > Shanghai > Shanghai (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
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- Oceania > Australia > New South Wales > Sydney (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
Practical Methods for Graph Two-Sample Testing
Debarghya Ghoshdastidar, Ulrike von Luxburg
We demonstrate the practical merits and limitations of existing theoretical tests and their bootstrapped variants.
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- Europe > Germany > Baden-Württemberg > Tübingen Region > Tübingen (0.05)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- North America > Canada > Quebec > Montreal (0.04)
- Asia > Middle East > Jordan (0.04)
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- Europe > Germany > Baden-Württemberg > Tübingen Region > Tübingen (0.04)
- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- North America > United States > California > Monterey County > Pacific Grove (0.04)
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- Europe > Germany > Baden-Württemberg > Tübingen Region > Tübingen (0.04)
- Asia > Middle East > UAE (0.04)
- Europe > Germany > Saarland > Saarbrücken (0.04)
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- Europe > Germany > Baden-Württemberg > Tübingen Region > Tübingen (0.04)
- Asia > Middle East > UAE (0.04)
- Europe > Germany > Saarland > Saarbrücken (0.04)
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- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- North America > Canada (0.04)
- Europe > Germany > Baden-Württemberg > Tübingen Region > Tübingen (0.04)
- Asia > Japan > Honshū > Kantō > Kanagawa Prefecture (0.04)
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LearningKernelTestsWithoutDataSplitting
Inspired by the selectiveinference framework, we propose an approach that enables learning the hyperparameters and testing onthefullsample without data splitting.
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- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
- Europe > Germany > Baden-Württemberg > Tübingen Region > Tübingen (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Performance Analysis > Accuracy (0.46)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.48)