Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Riemannian Submanifold Tracking on Low-Rank Algebraic Variety
Authors: Qian Li, Zhichao Wang
AAAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive comparison experiments demonstrate the accuracy and efficiency of RIST algorithm. |
| Researcher Affiliation | Academia | Qian Li Chinese Academy of Sciences Beijing, China EMAIL Wang Tsinghua University Beijing, China EMAIL |
| Pseudocode | Yes | Algorithm 1 Rank Initialization; Algorithm 2 RIST: Riemann Submanifold Tracking; Algorithm 3 ROM: Riemann Optimization over Mk |
| Open Source Code | No | The paper does not contain any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | Two collaborative filter datasets: the Jester-all dataset (Goldberg et al. 2001) and Movie-10M dataset (Herlocker et al. 1999) are used for the collaborative filtering. |
| Dataset Splits | No | The paper mentions training and test sets but does not explicitly describe a separate validation split, its size, or how it was used. |
| Hardware Specification | Yes | All comparison algorithms are implemented in Matlab and tested on a desktop computer with a 3.20 GHz CPU and 4.00 GB of memory. |
| Software Dependencies | No | The paper states "All comparison algorithms are implemented in Matlab" but does not specify a version number for Matlab or any other software dependencies. |
| Experiment Setup | Yes | The parameters ρ and η of RIST are set as 1.5 and 0.04, respectively. We set the rank parameter of these comparison methods as the ground-truth, namely, 15, 25 and 35. The parameters η of RIST is 0.05. |