Online MAP Inference of Determinantal Point Processes
Authors: Aditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam
NeurIPS 2020 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments demonstrating the efficiency of online methods for MAP inference. We demonstrate how even the simple algorithm ONLINE-LS finds solutions that compete favorably with offline algorithms (that store the entire dataset in memory). |
| Researcher Affiliation | Collaboration | Aditya Bhaskara School of Computing University of Utah EMAIL Amin Karbasi School of Engineering & Applied Science Yale University EMAIL Silvio Lattanzi Google Research Zürich EMAIL Morteza Zadimoghaddam Google Research Cambridge EMAIL |
| Pseudocode | Yes | Algorithm 1 Local Search with Stash (ONLINE-LS) and Algorithm 2 Online Coreset for Additive Error Approximation (ONLINE-DPP) are presented. |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | In our experiments we consider three standard datasets: the Spambase dataset [Dua and Graff, 2017], the Statlog(or Shuttle) dataset [Dua and Graff, 2017] and the Pen-Based Recognition dataset [Dua and Graff, 2017]. |
| Dataset Splits | No | The paper mentions using standard datasets but does not specify the train/validation/test splits, nor does it refer to predefined splits with citations. |
| Hardware Specification | No | All our experiments have been carried out on a standard desktop computer. |
| Software Dependencies | No | The paper does not provide specific software dependencies or version numbers. |
| Experiment Setup | Yes | In Figure 1 we show a comparison of the three algorithms on the Spambase dataset and the Statlog dataset for k = 8 and = 0.1. ... we report how the number of swaps and quality of the solution change as changes (experiments on other datasets are available in supplementary material). |