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..
Randomized Sketches for Clustering: Fast and Optimal Kernel $k$-Means
Authors: Rong Yin, Yong Liu, Weiping Wang, Dan Meng
NeurIPS 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, the numerical experiments on simulated data and real-world datasets validate our theoretical analysis. |
| Researcher Affiliation | Academia | Rong Yin 1,2, Yong Liu 3,4, , Weiping Wang 1,2, Dan Meng 1,2 1 Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China 2 School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China 3 Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China 4 Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China |
| Pseudocode | Yes | Algorithm 1 Unified Randomized Sketches Kernel k-Means |
| Open Source Code | No | We provide Pseudo code, data, and instructions. Lucky to be accepted, the code will be provided. |
| Open Datasets | Yes | The 9 real datasets: dna, segment, mushrooms, pendigits, protein, a8a, w7a, connect-4, and covtype, which are from LIBSVM website 2. 2http://www.csie.ntu.edu.cn/~cjlin/libsvm. |
| Dataset Splits | No | Generating 10,000 samples for training and 10,000 samples for testing. The number of training samples in each clustering is 10000/k. [...] 70 percent of the data in each dataset is used for training experiments, and the rest is used for testing. |
| Hardware Specification | Yes | The server is 32 cores (2.40GHz) and 32 GB of RAM. |
| Software Dependencies | No | The paper does not provide specific software names with version numbers for reproducibility. |
| Experiment Setup | Yes | Each experiment is repeated 5 times. [...] The number of training samples in each clustering is 10000/k. [...] m = 150. The Gaussian kernel is exp x x 2/σ2 , where σ = q Pn . |