Copeland Dueling Bandits

Authors: Masrour Zoghi, Zohar S. Karnin, Shimon Whiteson, Maarten de Rijke

NeurIPS 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We include an empirical evaluation of CCB and SCB using a real-life problem arising from information retrieval (IR). The experimental results mirror the theoretical ones.
Researcher Affiliation Collaboration Masrour Zoghi Informatics Institute University of Amsterdam, Netherlands m.zoghi@uva.nl Zohar Karnin Yahoo Labs New York, NY zkarnin@yahoo-inc.com Shimon Whiteson Department of Computer Science University of Oxford, UK shimon.whiteson@cs.ox.ac.uk Maarten de Rijke Informatics Institute University of Amsterdam derijke@uva.nl
Pseudocode Yes Algorithm 1 Copeland Confidence Bound, Algorithm 2 Approximate Copeland Bandit Solver, Algorithm 3 Scalable Copeland Bandits
Open Source Code Yes Sample code and the preference matrices used in the experiments can be found at http://bit.ly/nips15data.
Open Datasets Yes Sample code and the preference matrices used in the experiments can be found at http://bit.ly/nips15data.
Dataset Splits No The paper does not specify exact split percentages or absolute sample counts for training, validation, or test sets, nor does it reference predefined splits with citations for dataset partitioning.
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) needed to replicate the experiment.
Experiment Setup No The paper states, 'Due to lack of space, the details of the experimental setup have been included in Appendix B4.' As the appendix is not provided in the main text, specific experimental setup details are not accessible.