Partial Multi-Label Optimal Margin Distribution Machine
Authors: Nan Cao, Teng Zhang, Hai Jin
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on real-world data sets validates the superiority of our proposed method. |
| Researcher Affiliation | Academia | Nan Cao , Teng Zhang and Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab, Cluster and Grid Computing Lab School of Computer Science and Technology, Huazhong University of Science and Technology, China {nan cao, tengzhang, hjin}@hust.edu.cn |
| Pseudocode | Yes | Algorithm 1 summarizes the whole procedure. |
| Open Source Code | No | The paper does not provide an explicit statement or a link to open-source code for the described methodology. |
| Open Datasets | Yes | We conduct the experiments on eight real-world multi-label data sets1 which come from a broad range of field. Footnote 1: http://palm.seu.edu.cn/zhangml/ and http://mulan.sourceforge. net/datasets-mlc.html |
| Dataset Splits | Yes | All the parameters are selected by 5-fold cross validation. |
| Hardware Specification | No | The paper does not explicitly describe the hardware used to run its experiments. |
| Software Dependencies | No | The paper mentions using the solver Mosek but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | Yes | For our method k = 10 and the width of RBF kernel is selected from the set {2 10, 2 9, . . . , 23}. For the ODM based method, the parameters µ and θ are selected from the set {0.1, 0.2, . . . , 0.9}. |