Scalable Completion of Nonnegative Matrix with Separable Structure
Authors: Xiyu Yu, Wei Bian, Dacheng Tao
AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To demonstrate the effectiveness of NMCSA for completing matrices with separable structures, we conduct empirical valuations both on synthetic and real datasets. |
| Researcher Affiliation | Academia | Xiyu Yu, Wei Bian, Dacheng Tao Center for Quantum Computation and Intelligent Systems, University of Technology Sydney |
| Pseudocode | Yes | Algorithm 1 Basis Selection by Random Projections; Algorithm 2 Scalable Optimisation for F and X |
| Open Source Code | No | The paper does not provide any information about open-source code availability or links to repositories for the described methodology. |
| Open Datasets | Yes | We further evaluate NMCSA on two real datasets, Jester1 and Movie Lens, for collaborative filtering. Both datasets are benchmarks and have been commonly used in the literature for matrix completions. |
| Dataset Splits | No | As no test data are available in these datasets, a common choice is to sample the available ratings by 50% for training and use the resting 50% for test (Wang et al. 2014; Aravkin et al. 2014). The paper explicitly mentions training and testing splits, but not a separate validation split. |
| Hardware Specification | No | All the experiments are performed in Matlab on a desktop computer. This statement is too general and does not specify any particular hardware components like CPU or GPU models. |
| Software Dependencies | No | All the experiments are performed in Matlab on a desktop computer. This only mentions 'Matlab' without a specific version number or other required software dependencies with versions. |
| Experiment Setup | Yes | Here, we fix the size of matrices to be 500 × 500, and vary the rank and sampling ratio in the following ranges, i.e., r ∈ {5, 8, 11, ..., 59} and ρ ∈ {0.01, 0.06, ..., 0.86}, according to (Wen, Yin, and Zhang 2012). Then, 50 independent matrix completion experiments are performed for each pair (r, ρ). |