Notice: 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. Full accuracy metrics and methodology are described in [1].
PRODuctive bandits: Importance Weighting No More
Authors: Julian Zimmert, Teodor Vanislavov Marinov
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | By leveraging the interpretation of Prod as a first-order OMD approximation, we present the following surprising results: 1. Variants of Prod can obtain optimal regret for adversarial multi-armed bandits. 2. There exists a simple and (arguably) importance-weighting free variant with optimal rate. 3. One can even achieve best-both-worlds guarantees with logarithmic regret in the stochastic regime. |
| Researcher Affiliation | Industry | Julian Zimmert Google Research EMAIL Teodor V. Marinov Google Research EMAIL |
| Pseudocode | No | The paper describes algorithm update rules within the text (e.g., 'WSU-UX uses importance-weighted updates... πt+1,i = πt,i(1 η(ˆℓt,i λt))'), but it does not contain clearly labeled 'Pseudocode' or 'Algorithm' blocks or figures. |
| Open Source Code | No | Question: Does the paper provide open access to the data and code, with sufficient instructions to faithfully reproduce the main experimental results, as described in supplemental material? Answer: [NA] Justification: No experiments requiring code. |
| Open Datasets | No | The paper is purely theoretical and does not conduct experiments with datasets. |
| Dataset Splits | No | The paper is purely theoretical and does not conduct experiments, so it does not specify training, validation, or test dataset splits. |
| Hardware Specification | No | Question: For each experiment, does the paper provide sufficient information on the computer resources (type of compute workers, memory, time of execution) needed to reproduce the experiments? Answer: [NA] Justification: No experiments. |
| Software Dependencies | No | The paper is purely theoretical and does not involve experiments requiring specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is purely theoretical and does not involve experiments, thus no experimental setup details such as hyperparameters or system-level training settings are provided. |