Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Authors: Yuzhe Yang, Zhi Xu
NeurIPS 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on large-scale imbalanced datasets verify our theoretically grounded strategies, showing superior performance over previous state-of-the-arts. |
| Researcher Affiliation | Academia | Yuzhe Yang EECS Massachusetts Institute of Technology yuzhe@mit.edu Zhi Xu EECS Massachusetts Institute of Technology zhixu@mit.edu |
| Pseudocode | No | The paper does not contain any explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | Yes | Code is available at https://github.com/Yyz Harry/imbalanced-semi-self. |
| Open Datasets | Yes | We conduct thorough experiments on artificially created long-tailed versions of CIFAR-10 [7] and SVHN [36]... 80 Million Tiny Images [48] for CIFAR-10, and SVHN s own extra set [36]... Image Net-LT [33] and real-world dataset i Naturalist 2018 [24]. |
| Dataset Splits | No | The paper mentions using standard benchmark datasets and states 'We follow [7,25,33] to evaluate models on corresponding balanced test datasets', implying predefined splits, but does not explicitly provide specific percentages, sample counts, or a detailed splitting methodology for training, validation, and test sets within the paper itself. |
| Hardware Specification | No | The paper does not provide specific hardware details such as GPU or CPU models used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies or version numbers for the libraries or frameworks used in the experiments. |
| Experiment Setup | Yes | In the classifier learning stage, we follow [7,25] to train all models for 200 epochs on CIFAR-LT, and 90 epochs on Image Net-LT and i Naturalist. We use Rotation [16] as SSP method on CIFAR-LT, and Mo Co [19] on Image Net-LT and i Naturalist. |