Abstract
Similarity measures play a critical role in the solution quality of data analysis methods. Outliers or noise often taint the solution, hence, practical data analysis calls for robust measures. The correntropic loss function is a smooth and robust measure. In this paper, we present the properties of the correntropic loss function that can be utilized in optimization based data analysis methods.
| Original language | English |
|---|---|
| Pages (from-to) | 823-839 |
| Number of pages | 17 |
| Journal | Optimization Letters |
| Volume | 8 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2014 |
| Externally published | Yes |
Bibliographical note
Funding Information:This research is partially supported by NSF.
Keywords
- Classification
- Clustering
- Correntropy
- Invexity
- Pseudoconvexity
- Regression and robust data analysis
ASJC Scopus subject areas
- Business, Management and Accounting (miscellaneous)
- Control and Optimization
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