Beyond Shared Subspace: A View-Specific Fusion for Multi-View Multi-Label Learning
Authors: Gengyu Lyu, Xiang Deng, Yanan Wu, Songhe Feng7647-7654
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments have demonstrated that our proposed method significantly outperforms state-of-the-art methods. |
| Researcher Affiliation | Academia | Beijing Key Laboratory of Traffic Data Analysis and Mining School of Computer and Information Technology, Beijing Jiaotong University {18112030, 20120346, 19112034, shfeng}@bjtu.edu.cn |
| Pseudocode | Yes | Algorithm 1: The Training Process of D-VSM |
| Open Source Code | No | The paper does not provide an explicit statement about releasing source code or a link to a code repository. |
| Open Datasets | Yes | Emotions1 http://mulan.sourceforge.net/datasets-mlc.html... Corel5k (Duygulu et al. 2002) and Espgame (Von Ahn and Dabbish 2004)... Pascal (Everingham et al. 2010) and Mirflickr (Huiskes and Lew 2008) |
| Dataset Splits | Yes | Finally, we conduct experimental comparison between our proposed D-VSM and all comparing methods, where five-fold cross-validation is performed on each data set. |
| Hardware Specification | No | The paper does not provide specific hardware details (GPU/CPU models, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not list specific software components with their version numbers. |
| Experiment Setup | Yes | In our experiments, we set k = 5. |