On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification

By Isaac Triguero, José A. Sáez, Julián Luengo, Salvador Garcia, Francisco Herrera. 2014

85 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability, Representation & Self-Supervised Learning

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Xin He
2. Kaiyong Zhao
3. Xiaowen Chu
4. Marco F. Huber
5. Marc-André Zöller

In Computer Vision and Pattern Recognition

1. Xin He
2. Kaiyong Zhao
3. Xiaowen Chu

In Statistics and Probability

1. Xin He
2. Kaiyong Zhao
3. Xiaowen Chu

In Representation & Self-Supervised Learning

1. Xin He
2. Kaiyong Zhao
3. Xiaowen Chu

Citations in the corpus

• AutoML: A Survey of the State-of-the-Art (2019, methodology): “[67] summarize the self-labeling methods into the following categories: selftraining [68, 69], co-training [70, 71], and co-learning [72].”