A KL-LUCB algorithm for Large-Scale Crowdsourcing
Authors: Ervin Tanczos, Robert Nowak, Bob Mankoff
NeurIPS 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We corroborate our theoretical results with numerical experiments based on the New Yorker Cartoon Caption Contest. and Section 5 provides experimental support for the lil-KLUCB algorithm using data from the New Yorker Caption Contest. |
| Researcher Affiliation | Collaboration | Ervin Tánczos and Robert Nowak University of Wisconsin-Madison tanczos@wisc.edu, rdnowak@wisc.edu Bob Mankoff Former Cartoon Editor of the New Yorker bmankoff@hearst.com |
| Pseudocode | Yes | 1. Initialize by sampling every arm once. 2. While LTOP(t)(TTOP(t)(t), δ/(n 1)) max i =TOP(t)Ui(Ti(t), δ) do: Sample the following two arms: TOP(t), and arg max i =TOP(t)Ui(Ti(t), δ) and update means and confidence bounds. 3. Output TOP(t) |
| Open Source Code | No | The paper states 'These data can be found at https://github.com/nextml/caption-contest-data' which refers to data, not the open-source code for the proposed methodology. |
| Open Datasets | Yes | We corroborate our theoretical results with numerical experiments based on the New Yorker Cartoon Caption Contest. and Section 5 provides experimental support for the lil-KLUCB algorithm using data from the New Yorker Caption Contest. Footnote 7: These data can be found at https://github.com/nextml/caption-contest-data |
| Dataset Splits | No | The paper does not provide specific training/test/validation dataset splits (percentages, sample counts, or citations to predefined splits) for the data used in experiments. |
| Hardware Specification | No | The paper does not provide any specific hardware details (like GPU models, CPU types, or memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment. |
| Experiment Setup | Yes | We set N = 8 and δ = 0.01 in our experiments. |