Distributed Clustering of Linear Bandits in Peer to Peer Networks
Authors: Nathan Korda, Balazs Szorenyi, Shuai Li
ICML 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Through experiments on several real-world datasets, we demonstrate the performance of proposed algorithms compared to the state-of-the-art. |
| Researcher Affiliation | Academia | Nathan Korda NATHAN@ROBOTS.OX.AC.UK MLRG, University of Oxford Bal azs Sz or enyi SZORENYI.BALAZS@GMAIL.COM EE, Technion & MTA-SZTE Research Group on Artiļ¬cial Intelligence Shuai Li SHUAI.SLI@GMAIL.COM Di STA, University of Insubria |
| Pseudocode | Yes | Pseudocode for CB is given in the Appendix A.1. ... Pseudocode for DCB is given in Appendix A.1, and in Algorithm 1. ... Full pseudo-code for the DCCB algorithm is given in Algorithm 1, and the differences with the DCB algorithm are highlighted in blue. |
| Open Source Code | No | The paper does not provide any explicit statements about releasing its source code or links to a code repository for the described methodology. |
| Open Datasets | No | The paper mentions using "Last FM dataset", "Delicious dataset", and "Movie Lens dataset" which are common, but it does not provide concrete access information (e.g., specific link, DOI, formal citation with authors/year, or repository name) for these datasets. It refers to (Li et al., 2016a) for "dataset construction principles" but not for direct access to the raw datasets. |
| Dataset Splits | No | The paper mentions dataset characteristics but does not provide specific details about training, validation, or test dataset splits (e.g., percentages, sample counts, or citations to predefined splits). |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used to run the experiments, such as GPU/CPU models or memory specifications. |
| Software Dependencies | No | The paper does not provide any specific details about software dependencies, such as library names with version numbers. |
| Experiment Setup | No | The paper states, "We closely implemented the experimental setting and dataset construction principles used in (Li et al., 2016a;b), and for a detailed description of this we refer the reader to (Li et al., 2016a)." This defers the details of the experimental setup, including hyperparameters or system-level training settings, to external papers rather than providing them in the main text. |