Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
Authors: Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Section 5 Empirical Evaluations We conduct extensive numerical experiments on both synthetic and real-world datasets to evaluate the performance of the proposed algorithms and compare them with state-of-the-art baselines. |
| Researcher Affiliation | Academia | Liang-Ching Lin, Shi-Cho Cha, Pratik Kumar, Siva Theja Maguluri, Harsha Honnappa, Siva Kumar Sastry University of Maryland, Georgia Institute of Technology, Carnegie Mellon University, University of Minnesota |
| Pseudocode | Yes | Algorithm 1: CORRAL (Confidence Region based Online Risk-Aware Learning) |
| Open Source Code | No | The paper does not provide an explicit statement about the release of source code for the described methodology, nor does it include a link to a code repository. |
| Open Datasets | Yes | We use the Yahoo! Today Module dataset, which contains click-through rates (CTR) for various news articles over a period of 10 days. |
| Dataset Splits | No | The paper describes the generation of synthetic datasets and the characteristics of the real-world Yahoo! Today Module dataset, but it does not specify explicit training, validation, or test dataset splits (e.g., percentages or sample counts) needed for reproduction in a traditional sense. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, memory amounts, or cloud instance types) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | For the numerical experiments, the parameters are chosen as τ = 0.5, ρ = 0.1, λ = 0.05, c1 = 1, and c2 = 1. The confidence level is set to δ = 0.01. |