Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging
Authors: Ping-Chun Hsieh, Xi Liu, Anirban Bhattacharya, P R Kumar
ICML 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we validate the performance of HR-UCB via simulations. |
| Researcher Affiliation | Academia | 1Department of Electrical and Computer Engineering, Texas A&M University, College Station, USA 2Department of Statistics, Texas A&M University, College Station, USA. |
| Pseudocode | Yes | Algorithm 1 The HR-UCB Policy |
| Open Source Code | No | The paper does not provide any explicit statements or links about the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper states: "For simplicity, the context of each user-action pair is designed to be a four-dimensional vector, which is drawn uniformly at random from a unit ball." This indicates a simulated or synthetic dataset without public access information. |
| Dataset Splits | No | The paper describes the simulation setup and parameters but does not specify train, validation, or test dataset splits in the conventional sense. It refers to simulating over T=30000 users. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory, or cloud instances) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software names with version numbers that would be necessary to replicate the experiments. |
| Experiment Setup | Yes | For the mean and variance of the outcome distribution, we set θ = [0.6, 0.5, 0.5, 0.3] and φ = [0.5, 0.2, 0.8, 0.9] , respectively. We consider the function f(x) = x + L with L = 2 and Mf = 1. The acceptance level of each user is drawn uniformly at random from the interval [ 1, 1]. We set T = 30000 throughout the simulations. For HR-UCB, we set δ = 0.1 and λ = 1. All the results in this section are the average of 20 simulation trials. |