Automatic Outlier Rectification via Optimal Transport
–Neural Information Processing Systems
In this paper, we propose a novel conceptual framework to detect outliers using optimal transport with a concave cost function. Conventional outlier detection approaches typically use a two-stage procedure: first, outliers are detected and removed, and then estimation is performed on the cleaned data.
Neural Information Processing Systems
Oct-10-2025, 00:05:38 GMT
- Country:
- Europe > United Kingdom
- England > Cambridgeshire > Cambridge (0.04)
- North America
- Canada > British Columbia (0.04)
- United States > California
- Alameda County > Berkeley (0.04)
- Santa Clara County > Palo Alto (0.04)
- Europe > United Kingdom
- Genre:
- Research Report
- Experimental Study (1.00)
- New Finding (1.00)
- Research Report
- Industry:
- Banking & Finance > Trading (1.00)
- Technology: