ReLU Regression with Massart Noise
Authors: Ilias Diakonikolas, Jong Ho Park, Christos Tzamos
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate that our algorithm significantly outperforms naive applications of 1 and 2 regression on both synthetic and real data. In this section, we apply our algorithms that are based on radial-isotropic transformations to both synthetic and real datasets and compare robustness in regression with other baseline methods of 1 and 2-regression. Our experiments demonstrate the efficacy of radial-isotropic transformations in robust regression and how our algorithms outperform baseline regression methods. |
| Researcher Affiliation | Academia | Ilias Diakonikolas University of Wisconsin-Madison ilias@cs.wisc.edu Jongho Park University of Wisconsin-Madison jongho.park@wisc.edu Christos Tzamos University of Wisconsin-Madison tzamos@wisc.edu |
| Pseudocode | Yes | Algorithm 1 Linear function recovery via radial isotropy |
| Open Source Code | No | The paper does not contain any explicit statement about making the source code available or provide a link to a code repository. |
| Open Datasets | Yes | The drug discovery dataset was originally curated by (40) and we used the same dataset as the one used in (14). |
| Dataset Splits | Yes | The dataset has a training and test set of 3084 and 1000 points of 410 dimensions. |
| Hardware Specification | Yes | All experiments were done on a laptop computer with a 2.3 GHz Dual-Core Intel Core i5 CPU and 8 GB of RAM. |
| Software Dependencies | No | The paper mentions 'CVXPY s linear program solver' but does not specify a version number or other software dependencies with versions. |
| Experiment Setup | Yes | The experiment is set up with = 0.4, w = 9e2 + Pd i=1 ei, w0 = 0, 240 samples from Dx, and gradient descent step size of one. For Original , we use a step size of 1/465 to keep the magnitude of the points xi comparable to that of the transformed points xi. |