Contrastive Label Enhancement
Authors: Yifei Wang, Yiyang Zhou, Jihua Zhu, Xinyuan Liu, Wenbiao Yan, Zhiqiang Tian
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on LDL benchmark datasets demonstrate the effectiveness and superiority of our method. |
| Researcher Affiliation | Academia | School of Software Engineering, Xi an Jiaotong University, Xi an, China |
| Pseudocode | Yes | Algorithm 1 The optimization of Con LE |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described. |
| Open Datasets | Yes | SJAFFE dataset [Lyons et al., 1998] and SBU-3DFE dataset [Yin et al., 2006] are obtained from the two facial expression databases, JAFFE and BU-3DFE. ... Yeast datasets are derived from biological experiments on gene expression levels of budding yeast at different time points [Eisen et al., 1998]. |
| Dataset Splits | Yes | All algorithms are evaluated by ten times ten-fold cross-validation for fairness. |
| Hardware Specification | Yes | The code of this method is implemented by Py Torch [Paszke et al., 2019] on one NVIDIA Geforce GTX 2080ti GPU with 11GB memory. |
| Software Dependencies | No | The paper mentions "Py Torch [Paszke et al., 2019]" but does not specify a precise version number (e.g., 1.x.x) for reproducibility. It also mentions "SGD optimizer [Ruder, 2016]" and "Leaky Re LU activation function [Maas et al., 2013]" without version numbers. |
| Experiment Setup | Yes | When comparing with other algorithms, the hyperparameters of Con LE are set as follows: λ1 is set to 0.5, λ2 is set to 1 and the temperature parameter τI is 0.5. |