Learning on the Edge: Online Learning with Stochastic Feedback Graphs
Authors: Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our work is primarily theoretical and we do not foresee any potential negative societal impacts of our work. If you are including theoretical results... Did you include complete proofs of all theoretical results? [Yes] Although some proofs may only appear in the appendix. If you ran experiments... Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [N/A] |
| Researcher Affiliation | Academia | Emmanuel Esposito Dept. of Computer Science Università degli Studi di Milano, Italy & Istituto Italiano di Tecnologia, Italy emmanuel@emmanuelesposito.it Federico Fusco Dept. of Computer, Control and Management Engineering Sapienza Università di Roma, Italy fuscof@diag.uniroma1.it Dirk van der Hoeven Dept. of Computer Science Università degli Studi di Milano, Italy dirk@dirkvanderhoeven.com Nicolò Cesa-Bianchi Dept. of Computer Science Università degli Studi di Milano, Italy nicolo.cesa-bianchi@unimi.it |
| Pseudocode | Yes | Algorithm 1: Round Robin, Algorithm 2: Block Reduction, Algorithm 3: Edge Catcher |
| Open Source Code | No | The paper does not include any statements about releasing source code, nor does it provide a link to a code repository. Under the 'If you ran experiments' section of the ethics review, it states '[N/A]' for code and data reproduction. |
| Open Datasets | No | The paper is theoretical and does not involve experimental evaluation on datasets. Therefore, it does not mention the use of any publicly available or open datasets. |
| Dataset Splits | No | The paper is theoretical and does not conduct empirical studies, thus it does not provide details on training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup involving specific hardware. The ethics review section explicitly states '[N/A]' for hardware details. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers. The ethics review section confirms that no experimental details are provided. |
| Experiment Setup | No | The paper is theoretical and does not include details about an experimental setup, hyperparameters, or system-level training settings, as no empirical studies were conducted. |