Efficient Symmetric Norm Regression via Linear Sketching
Authors: Zhao Song, Ruosong Wang, Lin Yang, Hongyang Zhang, Peilin Zhong
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical Evaluation. In Section E of the supplementary material, we test our algorithms on real datasets. Our empirical results quite clearly demonstrate the practicality of our methods. |
| Researcher Affiliation | Academia | Zhao Song University of Washington, Ruosong Wang Carnegie Mellon University, Lin F. Yang University of California, Los Angeles, Hongyang Zhang Toyota Technological Institute at Chicago, Peilin Zhong Columbia University |
| Pseudocode | Yes | Figure 1: Algorithm for Orlicz norm regression |
| Open Source Code | No | The paper states that empirical evaluation was performed (Section E of supplementary material) but does not provide any explicit statement about releasing the source code for the described methodology or a link to a code repository. |
| Open Datasets | No | The paper mentions testing algorithms on 'real datasets' in Section E of the supplementary material, but does not specify the datasets or provide concrete access information (link, DOI, citation with authors/year, or specific names of well-known public datasets) in the main paper. |
| Dataset Splits | No | The paper does not provide specific details on training, validation, or test dataset splits, percentages, or sample counts. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU/GPU models, memory) used to run the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependency details, such as library names with version numbers, needed to replicate the experiments. |
| Experiment Setup | No | The paper does not provide specific experimental setup details, such as concrete hyperparameter values, training configurations, or system-level settings, in the main text. |