Sequential Strategic Screening

Authors: Lee Cohen, Saeed Sharifi -Malvajerdi, Kevin Stangl, Ali Vakilian, Juba Ziani

ICML 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical This work is primarily theoretical.
Researcher Affiliation Academia 1Toyota Technological Institute at Chicago, Chicago, IL, USA 2H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
Pseudocode No The paper does not contain structured pseudocode or algorithm blocks clearly labeled as such. It describes algorithms and optimization problems in prose and mathematical formulations.
Open Source Code No The paper does not provide concrete access to source code (no specific repository link, explicit code release statement, or mention of code in supplementary materials) for the methodology described.
Open Datasets No The paper is theoretical and does not conduct experiments on a specific dataset. Therefore, it does not provide concrete access information for a publicly available or open dataset.
Dataset Splits No The paper is theoretical and does not conduct experiments on a specific dataset. Therefore, it does not provide specific dataset split information for training, validation, or testing.
Hardware Specification No The paper is theoretical and does not describe computational experiments. Therefore, no specific hardware details are provided.
Software Dependencies No The paper is theoretical and does not describe an implementation requiring specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe empirical experiments or specific experimental setup details with concrete hyperparameter values or training configurations.