This paper presents the first Rademacher complexity-based error bounds for noni.i.d. settings, a generalization of similar existing bounds derived for the i.i.d. case. Our bounds ...
Abstract: Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of K SVMs can b...
Effective learning in multi-label classification (MLC) requires an ate level of abstraction for representing the relationship between each instance and multiple categories. Curren...
— We have entered an era where chip yields are decreasing with scaling. A new concept called intelligible testing has been previously proposed with the goal of reversing this tre...
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...