Linear Discriminant Analysis(LDA) is well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional data,...
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...
Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jor...
Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
This paper presents a new discriminative model for information retrieval (IR), referred to as linear discriminant model (LDM), which provides a flexible framework to incorporate a...
Residual gradient (RG) was proposed as an alternative to TD(0) for policy evaluation when function approximation is used, but there exists little formal analysis comparing them ex...