Twin Learning for Similarity and Clustering: A Unified Kernel Approach
Authors: Zhao Kang, Chong Peng, Qiang Cheng
AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments are performed to demonstrate the effectiveness of our method. In this section, we demonstrate the effectiveness of the proposed method on real world benchmark data sets. |
| Researcher Affiliation | Academia | Zhao Kang, Chong Peng, Qiang Cheng Department of Computer Science, Southern Illinois University, Carbondale, IL 62901, USA {Zhao.Kang, pchong, qcheng}@siu.edu |
| Pseudocode | Yes | Algorithm 1 The algorithm of SCSK |
| Open Source Code | Yes | 7https://github.com/sckangz/AAAI17 |
| Open Datasets | Yes | There are altogether eight benchmark data sets used in our experiments. Table 1 summarizes the statistics of these data sets... 1http://www-users.cs.umn.edu/ han/data/tmdata.tar.gz 2http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase .html 3http://vision.ucsd.edu/content/yale-face-database 4http://www2.ece.ohio-state.edu/ aleix/ARdatabase.html 5http://www.kasrl.org/jaffe.html 6http://www.cs.nyu.edu/ roweis/data.html |
| Dataset Splits | No | The paper does not provide specific details on train/validation/test splits, such as percentages or sample counts. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used for experiments. |
| Software Dependencies | No | The paper mentions 'many existing quadratic programing packages' and links to other methods' codebases but does not provide specific version numbers for software dependencies used in their own implementation. |
| Experiment Setup | Yes | There are two parameters α and β in our models. We let α vary over the range of {1e-5, 1e-4, 1e-3, 0.01, 0.1, 1, 10, 100}, and β over {1e-6, 1e-5}... We set the number of clusters to the true number of classes for all clustering algorithms. |