Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents
an accessible treatment of the two main components of support vector machines (SVMs) …

Automatic recognition system for medical images is challenging task in the field of medical
image processing. Medical images acquired from different modalities such as Computed …

Careful design and preparation of drilling fluids with appropriate rheology and filtration
properties, combined with operational monitoring, is essential for successful drilling …

The learning speed of classical Support Vector Regression (SVR) is low, since it is
constructed based on the minimization of a convex quadratic function subject to the pair …

The objective of this study is to explore and compare the least square support vector
machine (LSSVM) and multiclass alternating decision tree (MADT) techniques for the spatial …

The support vector machine (SVM) is a powerful classifier which has been used successfully
in many pattern recognition problems. It has also been shown to perform well in the …

Learning from data is one of the basic ways humans perceive the world and acquire the
knowledge. Support vector machine (SVM for short) has emerged as a good classification …

Kernel methods, such as the support vector machine (SVM), are often formulated as
quadratic programming (QP) problems. However, given m training patterns, a naive …

This research paper proposes an intelligent classification technique to identify normal and
abnormal slices of brain MRI data. The manual interpretation of tumor slices based on visual …

In this paper, we present two fast sparse approximation schemes for least squares support
vector machine (LS-SVM), named FSALS-SVM and PFSALS-SVM, to overcome the …