The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels
Authors: Florian Kalinke, Zoltan Szabo
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we prove that the minimax optimal rate of HSIC estimation on Rd for Borel measures containing the Gaussians with continuous bounded translation-invariant characteristic kernels is O n 1/2 . |
| Researcher Affiliation | Academia | Florian Kalinke Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Karlsruhe, Germany florian.kalinke@kit.edu Zoltán Szabó Department of Statistics London School of Economics London, UK z.szabo@lse.ac.uk |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is theoretical and does not mention providing open-source code for its methodology. |
| Open Datasets | No | The paper does not include experiments and thus does not use a training dataset. It focuses on theoretical bounds for distributions. |
| Dataset Splits | No | The paper does not include experiments and thus does not specify validation dataset splits. |
| Hardware Specification | No | The paper does not include experiments and thus does not provide hardware specifications. |
| Software Dependencies | No | The paper does not include experiments and thus does not provide specific software dependencies with version numbers. |
| Experiment Setup | No | The paper does not include experiments and thus does not provide details about an experimental setup like hyperparameters or training settings. |