Optimal-er Auctions through Attention

Authors: Dmitry Ivanov, Iskander Safiulin, Igor Filippov, Ksenia Balabaeva

NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We investigate both modifications in an extensive experimental study that includes settings with constant and inconstant numbers of items and participants, as well as novel validation procedures tailored to regret-based approaches.
Researcher Affiliation Collaboration Dmitry Ivanov HSE University & Technion Israel Iskander Safiulin Independent researcher Russia Igor Filippov Independent researcher Russia Ksenia Balabaeva ITMO University & BIOCAD Russia
Pseudocode No The paper includes a figure illustrating the architecture (Figure 1) and describes its components verbally in Section 3.1, but it does not provide structured pseudocode or an algorithm block.
Open Source Code Yes Code is available here
Open Datasets No The paper describes how the data is generated (
Dataset Splits No The paper states that
Hardware Specification No The paper states that research was supported
Software Dependencies No The paper mentions deep learning frameworks and concepts (e.g.,
Experiment Setup No The paper states that