Fast Classification Rates for High-dimensional Gaussian Generative Models
Authors: Tianyang Li, Adarsh Prasad, Pradeep K. Ravikumar
NeurIPS 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section we describe experiments which illustrate the rates for excess 0-1 risk given in Theorem 2. In our experiments we use Glmnet [19] where we set the option to penalize the intercept term along with all other parameters. |
| Researcher Affiliation | Academia | Tianyang Li Adarsh Prasad Department of Computer Science, UT Austin {lty,adarsh,pradeepr}@cs.utexas.edu Pradeep Ravikumar |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper mentions using 'Glmnet [19]' which is a third-party package, but does not provide concrete access to source code for the methodology described in this paper. |
| Open Datasets | No | The paper uses simulated data defined by parameters (e.g., Σ = Ip, µ1 = 1p + 1 s and µ0 = 0) but does not provide concrete access information for a publicly available or open dataset. |
| Dataset Splits | No | The paper mentions using 'n training samples' but does not provide specific dataset split information (percentages, sample counts, or citations to predefined splits) needed to reproduce the data partitioning for training, validation, or test. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper mentions 'Glmnet [19]' but does not provide specific version numbers for software dependencies. |
| Experiment Setup | Yes | In all experiments we set the regularization parameter λ = q log p n . In our experiments we use Glmnet [19] where we set the option to penalize the intercept term along with all other parameters. |