Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting
Authors: Yudong Chen, Jiaming Xu
ICML 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our theorems establish the first minimax recovery results for the high-dimensional setting, and provide the best known guarantees for polynomial-time algorithms. |
| Researcher Affiliation | Academia | Yudong Chen YUDONG.CHEN@EECS.BERKELEY.EDU Department of EECS, University of California, Berkeley, Berkeley, CA 94704, USA Jiaming Xu JXU18@ILLINOIS.EDU Department of ECE, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA |
| Pseudocode | Yes | Algorithm 1 Maximum Likelihood Estimator (p > q) |
| Open Source Code | No | The paper does not provide any statements or links regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper and does not involve empirical studies with datasets, thus no dataset access information is provided. |
| Dataset Splits | No | This is a theoretical paper and does not involve empirical studies with datasets, thus no dataset split information is provided. |
| Hardware Specification | No | This is a theoretical paper and does not report on empirical experiments that would require specific hardware. No hardware specifications are mentioned. |
| Software Dependencies | No | This is a theoretical paper and does not report on empirical experiments that would require specific software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not report on empirical experiments that would involve hyperparameter settings or experimental setup details. |