Importance-aware Co-teaching for Offline Model-based Optimization
Authors: Ye Yuan, Can (Sam) Chen, Zixuan Liu, Willie Neiswanger, Xue (Steve) Liu
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | ICT achieves state-of-the-art results across multiple design-bench tasks, achieving the best mean rank of 3.1 and median rank of 2, among 15 methods. Our source code can be found here. 4 Experimental Results |
| Researcher Affiliation | Academia | 1 Mc Gill University, 2 MILA Quebec AI Institute, 3 University of Washington, 4 Stanford University |
| Pseudocode | Yes | A detailed depiction of the entire algorithm can be found in Algorithm 1. |
| Open Source Code | Yes | Our source code can be found here. |
| Open Datasets | Yes | In this study, we conduct experiments on four continuous tasks and three discrete tasks. The continuous tasks include: (a) Superconductor (Super C)[5]... (b) Ant Morphology (Ant)[1, 14]... (c) D Kitty Morphology (D Kitty)[1, 15]... (d) Hopper Controller (Hopper)[1]... Additionally, our discrete tasks include: (e) TF Bind 8 (TF8)[6]... (f) TF Bind 10 (TF10)[6]... (g) NAS [16]... |
| Dataset Splits | No | The paper describes using an 'offline dataset' and selecting designs from it, but it does not specify explicit train/validation/test splits with percentages or sample counts for the original dataset. |
| Hardware Specification | Yes | All experiments are run on a single NVIDIA GeForce RTX 3090 GPU. |
| Software Dependencies | No | The paper mentions using the 'Adam optimizer [46]' and implicitly deep learning frameworks, but does not specify software dependencies with version numbers (e.g., 'Python 3.8, PyTorch 1.9'). |
| Experiment Setup | Yes | The number of iterations, T, is set to 200 for continuous tasks and 100 for discrete tasks. ... The learning rates are set at 1e 3 and 1e 1 for continuous tasks and discrete tasks, respectively. ... with a learning rate 2e 1 for continuous tasks and 3e 1 for discrete tasks, respectively. |