Research map / Learning theory and algorithms / Kernels and regression theory
Practical Kernel Selection for Kernel-based Conditional Independence Test
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AI-extracted summary. Written by AI from the paper's abstract only. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Studies how to select kernels (and their hyperparameters) for kernel-based conditional independence tests so the tests perform well in practice.
Problem
Kernel-based conditional independence tests depend on kernel choice, and selecting appropriate kernels in practice is difficult; the abstract is truncated, so the specific failure modes are not stated.
Approach
Abstract is truncated; the proposed kernel selection approach cannot be determined from the provided text.
Limitations
- Full text unavailable; only a truncated abstract was provided
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