Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates.
Online A-Optimal Design and Active Linear Regression
Authors: Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet
ICML 2021 | Venue PDF | LLM Run Details | Input Tokens: 17,217 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 4,066 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Numerical experiments validate our theoretical ο¬ndings. |
| Researcher Affiliation | Collaboration | 1Centre Borelli, ENS Paris-Saclay, Palaiseau, France 2Idemia, Courbevoie, France 3Google Deep Mind, Paris, France 4CREST, ENSAE, Palaiseau, France 5Criteo AI Lab, Paris, France. |
| Pseudocode | Yes | Algorithm 1 Naive randomized algorithm; Algorithm 2 Bandit algorithm |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for their methods is publicly available. |
| Open Datasets | No | We run our experiments on synthetic data with horizon time T between 104 and 106, averaging the results over 25 rounds. |
| Dataset Splits | No | The paper mentions running experiments on synthetic data but does not specify any training, validation, or test dataset splits. The experimental process involves sequential sampling over rounds rather than predefined splits. |
| Hardware Specification | No | All the experiments ran in less than 15 minutes on a standard laptop. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers for reproducibility. |
| Experiment Setup | No | The paper describes the general setup of numerical simulations, including using synthetic data and averaging results over 25 rounds, but does not provide specific experimental setup details such as hyperparameters, model initialization, or optimizer settings. |