A. M. Andrew, An introduction to support vector machines and other kernel-based learning methods by nello christianini and john shawe-taylor, cambridge university press, cambridge, 2000, xiii+ 189 pp., isbn 0-521-78019-5 (hbk,...
A. M. Andrew, An introduction to support vector machines and other kernel-based learning methods by nello christianini and john shawe-taylor, cambridge university press, cambridge, 2000, xiii+ 189 pp., isbn 0-521-78019-5 (hbk,...
A. M. Andrew, An introduction to support vector machines and other kernel-based learning methods by nello christianini and john shawe-taylor, cambridge university press, cambridge, 2000, xiii+ 189 pp., isbn 0-521-78019-5 (hbk,...
A. M. Andrew, An introduction to support vector machines and other kernel-based learning methods by nello christianini and john shawe-taylor, cambridge university press, cambridge, 2000, xiii+ 189 pp., isbn 0-521-78019-5 (hbk,...
A. M. Andrew, An introduction to support vector machines and other kernel-based learning methods by nello christianini and john shawe-taylor, cambridge university press, cambridge, 2000, xiii+ 189 pp., isbn 0-521-78019-5 (hbk,...
A. M. Andrew, An introduction to support vector machines and other kernel-based learning methods by nello christianini and john shawe-taylor, cambridge university press, cambridge, 2000, xiii+ 189 pp., isbn 0-521-78019-5 (hbk,...
克里斯蒂亚尼尼 - 支持向量机导论 = An Introduction to support vector machines and other kernel-based learning methods
We introduce the concept of span of support vectors (SV) and show that the generalization ability of support vector machines (SVM) depends on this new geom...
In this paper we give a new fast iterative algorithm for support vector machine (SVM) classifier design. The basic problem treated is one that does not all...
The main purpose of this paper is to show that new formulations of support vector machines can generate nonlinear separating surfaces which can discriminat...
This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike sta...
Identification of transcription factor binding sites within regulatory segments of genomic DNA is an important step toward understanding of the regulatory ...
Classification can be considered as nonparametric estimation of sets, where the risk is defined by means of a specific distance between sets associated wit...
, we then obtain risk tail bounds for kernel perceptron algorithms in terms of the spectrum of the empirical kernel matrix. These bounds reveal that the li...
The problem of constructing an adaptive multiuser detector (MUD) is considered for direct sequence code division multiple access (DS-CDMA) signals transmit...
We study the problem of classifying data in a given taxonomy when classifications associated with multiple and/or partial paths are allowed. We introduce a...
Cytotoxic T lymphocyte (CTL) epitopes are potential candidates for subunit vaccine design for various diseases. Most of the existing T cell epitope prediction methods are indirect methods that predict MHC class I binders instead of CTL e...
We introduce a variant of the Perceptron algorithm called second-order Perceptron algorithm, which is able to exploit certain spectral properties of the da...
