# Machine Learning and Data Classification

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/machine-learning-and-data-classification-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 707,385 |
| Description | This cluster of papers focuses on the challenges and techniques for learning with noisy labels in machine learning, including methods for hyperparameter optimization, instance selection, robust learning, and automated machine learning. It also explores the use of meta-learning and deep neural networks in handling noisy label problems, particularly in the context of classification tasks and learning from positive and unlabeled data. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | https://openalex.org/T12535 |
| Works | 41,719 |

## Topic researchers

Showing 12 of 20.

- [Yoshua Bengio](https://scholariq.org/researchers/yoshua-bengio/)
- [Geoffrey E. Hinton](https://scholariq.org/researchers/geoffrey-e-hinton/)
- [Robert Tibshirani](https://scholariq.org/researchers/robert-tibshirani/)
- [Steven L. Salzberg](https://scholariq.org/researchers/steven-l-salzberg/)
- [Ross Girshick](https://scholariq.org/researchers/ross-girshick/)
- [Trevor Hastie](https://scholariq.org/researchers/trevor-hastie/)
- [Andrew Zisserman](https://scholariq.org/researchers/andrew-zisserman/)
- [Yann LeCun](https://scholariq.org/researchers/yann-lecun/)
- [Leo Breiman](https://scholariq.org/researchers/leo-breiman/)
- [Vladimir Vapnik](https://scholariq.org/researchers/vladimir-vapnik/)
- [Li Fei-Fei](https://scholariq.org/researchers/li-fei-fei/)
- [Ilya Sutskever](https://scholariq.org/researchers/ilya-sutskever/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.