contaminated data, where the majority of the data comes from a "nominal" distribution with a small fraction of the data coming from …) from the contaminated data. Our proposed density estimation achieves robustness by combinining a traditional kernel density … design a classifier. In this thesis, we present kernel methods for classification with irregularly sampled and contaminated …