Robust Market Equilibria with Uncertain Preferences

Authors: Riley Murray, Christian Kroer, Alex Peysakhovich, Parikshit Shah2192-2199

AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental 5 Experimental Results
Researcher Affiliation Collaboration 1Facebook Core Data Science, 2Facebook Artificial Intelligence Research 3California Institute of Technology, 4Columbia University
Pseudocode No The paper does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for the methodology described in this paper.
Open Datasets Yes We start with the Movie Lens 1M dataset where 6000 individuals give ratings to 4000 movies.
Dataset Splits No The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning.
Hardware Specification No The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments.
Software Dependencies Yes For our implementation we rely on CVXPY 1.0 (Diamond and Boyd 2016; Agrawal et al. 2018) to interface with solvers MOSEK (Mosek 2010; Dahl and Andersen 2019) and ECOS (Domahidi, Chu, and Boyd 2013).
Experiment Setup Yes Experiments here use the 2-norm; refer to supplementary material for the same experiments under 1-norm uncertainty. For our implementation we rely on CVXPY 1.0 (Diamond and Boyd 2016; Agrawal et al. 2018) to interface with solvers MOSEK (Mosek 2010; Dahl and Andersen 2019) and ECOS (Domahidi, Chu, and Boyd 2013).