Instrumental Variable Regression with Confounder Balancing
Authors: Anpeng Wu, Kun Kuang, Bo Li, Fei Wu
ICML 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments show that our algorithm outperforms the existing approaches. |
| Researcher Affiliation | Collaboration | 1Department of Computer Science and Technology, Zhejiang University, China 2School of Economics and Managemen, Tsinghua University, China 3Shanghai Institute for Advanced Study, Zhejiang University, China 4Shanghai AI Laboratory, China. |
| Pseudocode | Yes | The details of pseudo-code (Algorithm 1) and the network structures (Table 5) of CB-IV are provided in Section E.1 in Appendix. |
| Open Source Code | Yes | 2The code is available at: https://github.com/anpwu/CB-IV |
| Open Datasets | Yes | IHDP3: The Infant Health and Development Program (IHDP) [...] 3http://www.fredjo.com/ [...] Twins4: Twins dataset is derived from all twins born in the USA between the years 1989 and 1991 (Almond et al., 2005). [...] 4http://www.nber.org/data/ |
| Dataset Splits | Yes | We conduct our experiments over the 100 realizations of IHDP and 10 realizations of Twins with a 63/27/10 proportion of train/validation/test splits. |
| Hardware Specification | Yes | Hardware used: Ubuntu 16.04.5 LTS operating system with 2 * Intel Xeon E5-2678 v3 CPU, 384GB of RAM, and 4 * Ge Force GTX 1080Ti GPU with 44GB of VRAM. |
| Software Dependencies | Yes | Software used: Python with Tensor Flow 1.15.0, Num Py 1.17.4, and Matplot Lib 3.1.1. |
| Experiment Setup | Yes | Table 5 shows the details of the structure networks of CB-IV in different datasets. [...] Learning Rate 0.0005 Optimizer Adam α 0.01/0.001 |