Density Ratio Estimation with Doubly Strong Robustness
Authors: Ryosuke Nagumo, Hironori Fujisawa
ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Numerical experiments show that our proposals are more robust than the previous methods. In Section 4, numerical experiments illustrate that the proposed methods are more robust than the past ones. |
| Researcher Affiliation | Collaboration | 1The Graduate University for Advanced Studies (SOKENDAI), Tokyo, Japan 2Panasonic Holdings Corporation, Osaka, Japan 3Institute of Statistical Mathematics, Tokyo, Japan. |
| Pseudocode | No | The paper describes its methods and optimization procedures using mathematical formulations and descriptive text, but it does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide a concrete access link or explicit statement for the open-sourcing of the code for its proposed methodology. While it references a GitHub link for a comparison method (Ru LSIF), it does not do so for its own contributions. |
| Open Datasets | Yes | We used a human activity dataset provided by the Human Activity Sensing Consortium (HASC) Challenge 2011, which was used in the experiment of change detection with DRE (Liu et al., 2013). |
| Dataset Splits | Yes | The dataset sizes were set to np = nq = 100. The dataset sizes of the reference and target datasets were set to np = nq = 100. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper mentions using a Python code for a comparison method but does not provide specific software dependencies with version numbers for its own implementation or experimental setup. |
| Experiment Setup | Yes | The weight function was set to w(x) = exp x 4 4/50 . The trimming quantile ν in Trimmed DRE was set to the true contamination ratio. The parameter γ in γ-DRE was set to 0.01. No regularization term was added to the objective function. We added the elastic net regularization term λ1 θ 1 + λ2 θ 2 2 with λ1 = λ2 = 0.5 to the objective function. |