Scalable Kernel Inverse Optimization
Authors: Youyuan Long, Tolga Ok, Pedro Zattoni Scroccaro, Peyman Mohajerin Mohajerin Esfahani
NeurIPS 2024 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we validate the generalization capabilities of the proposed KIO model and the effectiveness of the SSO algorithm through learning-from-demonstration tasks on the Mu Jo Co benchmark. |
| Researcher Affiliation | Academia | Youyuan Long Delft Center for Systems and Control Delft University of Technology The Netherlands EMAIL Ok Delft Center for Systems and Control Delft University of Technology The Netherlands EMAIL Zattoni Scroccaro Delft Center for Systems and Control Delft University of Technology The Netherlands P.Zattoni EMAIL Mohajerin Esfahani Delft Center for Systems and Control Delft University of Technology The Netherlands P.Mohajerin EMAIL |
| Pseudocode | Yes | Algorithm 1 Sequential Selection Optimization (SSO) |
| Open Source Code | Yes | To foster reproducibility and further research, we provide an opensource implementation of the proposed KIO model and the SSO algorithm, along with the source code of the experiments in Github1. 1https://github.com/Longyouyuan/Scalable-Kernel-Inverse-Optimization |
| Open Datasets | Yes | KIO is implemented in its simplified version (9), incorporating a Gaussian kernel, and tested on continuous control datasets from the D4RL benchmark [18]. [18] Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, and Sergey Levine. D4rl: Datasets for deep data-driven reinforcement learning, 2020. |
| Dataset Splits | No | The paper states that the model is 'trained using the SSO Algorithm 1' and 'assessed over 100 test episodes,' but it does not specify explicit training/validation/test dataset splits (e.g., percentages or sample counts) or cite a specific standard split methodology for D4RL. |
| Hardware Specification | No | The paper mentions that solving certain problems 'requires up to 256GB of memory,' indicating a memory requirement, but it does not specify the actual hardware used such as GPU/CPU models, types, or speeds. |
| Software Dependencies | Yes | The paper mentions using 'CVXPY [13]' and 'off-the-shelf solvers, such as MOSEK [3].' MOSEK is cited with a version number: 'Mosek Ap S. Mosek optimization toolbox for matlab. User s Guide and Reference Manual, Version, 4:1, 2019.' |
| Experiment Setup | Yes | All hyperparameters used in this experiment for KIO are listed in Appendix B. |