Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms
Authors: Michael Feldman, David Donoho
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Even for modest-sized tensors, simulations demonstrate close agreement with theory. Figure 1: Simulations of tensor unfolding with k = 3, supersymmetric signal v1 = v2 = v3, and n1 {400, 800, 1200}. Solid lines display empirical cosine similarities (each point is the average of 50 realizations). |
| Researcher Affiliation | Academia | David L. Donoho Department of Statistics Stanford University donoho@stanford.edu Michael J. Feldman Department of Statistics Stanford University feldman6@stanford.edu |
| Pseudocode | Yes | Algorithm 1 Tensor unfolding; Algorithm 2 Partial tracing; Algorithm 3 Power iteration; Algorithm 4 Recursive unfolding |
| Open Source Code | No | The paper does not contain any statements about making its source code publicly available or providing links to a code repository. |
| Open Datasets | No | The paper uses synthetic data generated through simulations rather than a publicly available dataset. For example, Figure 1 describes "Simulations of tensor unfolding with k = 3, supersymmetric signal v1 = v2 = v3, and n1 {400, 800, 1200}." |
| Dataset Splits | No | The paper describes generating synthetic data for simulations and analyzing empirical results (e.g., "each point is the average of 50 realizations"), but it does not mention traditional training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, or cloud computing resources) used to run its simulations. |
| Software Dependencies | No | The paper does not provide specific names or version numbers for any software libraries, frameworks, or tools used in its simulations or analysis. |
| Experiment Setup | Yes | The paper explicitly details the parameters for its simulations, such as in figure captions: "Simulations of tensor unfolding with k = 3, supersymmetric signal v1 = v2 = v3, and n1 {400, 800, 1200}." and "Simulations of tensor unfolding with k = 3, n1 = n2 = 50, and n3 = 10000 (left) or n3 = 20000 (right)." |