Multiple-Play Bandits in the Position-Based Model
Authors: Paul Lagrée, Claire Vernade, Olivier Cappe
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In the last section dedicated to experiments, those policies are compared to several benchmarks on both synthetic and realistic data. |
| Researcher Affiliation | Academia | Paul Lagrée LRI, Université Paris Sud Université Paris Saclay paul.lagree@u-psud.fr Claire Vernade LTCI, CNRS, Télécom Paris Tech Université Paris Saclay vernade@enst.fr Olivier Cappé LTCI, CNRS Télécom Paris Tech Université Paris Saclay |
| Pseudocode | Yes | Algorithm 1 PBM-PIE |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. It references a dataset but not its own code. |
| Open Datasets | Yes | The dataset was provided for KDD Cup 2012 track 2[1] and involves session logs of soso.com, a search engine owned by Tencent. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning into train/validation/test sets. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) 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 | In order to evaluate our strategies, a simple problem is considered in which K = 5, L = 3, κ = (0.9, 0.6, 0.3) and θ = (0.45, 0.35, 0.25, 0.15, 0.05). ... We conducted a series of 2,000 simulations over this dataset. At the beginning of each run, a query was randomly selected together with corresponding probabilities of scanning positions and arm expectations. |