Best Arm Identification in Graphical Bilinear Bandits
Authors: Geovani Rizk, Albert Thomas, Igor Colin, Rida Laraki, Yann Chevaleyre
ICML 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We propose a decentralized allocation strategy based on random sampling with theoretical guarantees. In particular, we characterize the influence of the graph structure (e.g. star, complete or circle) on the convergence rate and propose empirical experiments that confirm this dependency. Finally, Section 7 evidences the theoretical findings on numerical experiments. |
| Researcher Affiliation | Collaboration | 1PSL Universit e Paris Dauphine, CNRS, LAMSADE, Paris, France 2Huawei Noah s Ark Lab 3Liverpool University. Correspondence to: Geovani Rizk <geovani.rizk@dauphine.psl.eu>. |
| Pseudocode | Yes | Algorithm 1 Bipartite graph algorithm for Best Arm Identification in Graphical Bilinear Bandits Algorithm 2 Randomized G-Allocation strategy for Graphical Bilinear Bandits |
| Open Source Code | No | The paper does not provide any concrete access to source code (e.g., specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described. |
| Open Datasets | No | The paper describes the creation of the experimental setup and the parameters used (e.g., node-arms, parameter matrix M, noise distribution) but does not refer to a publicly available dataset with concrete access information (link, DOI, formal citation). |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., 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 like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | Yes | We consider d + 1 node-arms in X Rd where d 2. This node-arm set is made of the d vectors (e1, . . . , ed) forming the canonical basis of Rd and one additional arm xd+1 = (cos(ω), sin(ω), 0, . . . , 0) with ω ]0, π/2]. The parameter matrix M has its first coordinate equal to 2 and the others equal to 0 which makes θ = vec (M ) = (2, 0, . . . , 0) Rd2. We set η(i,j) t N(0, 1), for all edges (i, j) and round t. We consider the two cases where ω = 0.1 and ω = π/2. |