A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Abstract— This work considers a combination classificationregression based framework with the proposal of using learned kernels in modified support vector regression to provide...
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detec...
Longin Jan Latecki, Aleksandar Lazarevic, Dragolju...
This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM by introducing semi-supervised learning technique and the kernel method simultaneously into...
Abstract. Consider the online regression problem where the dependence of the outcome yt on the signal xt changes with time. Standard regression techniques, like Ridge Regression, d...