Tolerant Algorithms for Learning with Arbitrary Covariate Shift
Authors: Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our paper does not have any experiments. |
| Researcher Affiliation | Academia | Surbhi Goel Department of Computer Science University of Pennsylvania surbhig@seas.upenn.edu Abhishek Shetty Department of EECS UC Berkeley shetty@berkeley.edu Konstantinos Stavropoulos Department of Computer Science UT Austin kstavrop@utexas.edu Arsen Vasilyan Department of EECS UC Berkeley arsenvasilyan@gmail.com |
| Pseudocode | Yes | Algorithm 1: Outlier Removal Procedure |
| Open Source Code | No | Our paper does not have any experiments requiring code. |
| Open Datasets | No | Our paper does not have any experiments. |
| Dataset Splits | No | Our paper does not have any experiments. |
| Hardware Specification | No | Our paper does not have any experiments. |
| Software Dependencies | No | Our paper does not have any experiments requiring code. |
| Experiment Setup | No | Our paper does not have any experiments. |