Ensemble methods use multiple models to get better performance. Ensemble methods have
been used in multiple research fields such as computational intelligence, statistics and …

Multiple kernel learning (MKL) is a principled approach for selecting and combining kernels
for a given recognition task. A number of studies have shown that MKL is a useful tool for …

Video based action recognition is one of the important and challenging problems in
computer vision research. Bag of visual words model (BoVW) with local features has been …

With the popularity of Android smartphones, malicious applications targeted Android
platform have explosively increased. Proposing effective Android malware detection method …

Recent years have witnessed the quick progress of the hyperspectral images (HSI)
classification. Most of existing studies either heavily rely on the expensive label information …

Combining multiple low-level visual features is a proven and effective strategy for a range of
computer vision tasks. However, limited attention has been paid to combining such features …

In this paper, we present a new adaptive feature scaling scheme for ultrahigh-dimensional
feature selection on Big Data, and then reformulate it as a convex semi-infinite programming …

The pervasiveness of mobile cameras has resulted in a dramatic increase in food photos,
which are pictures reflecting what people eat. In this paper, we study how taking pictures of …

Abstract Many existing Machine Learning (ML) based Android malware detection
approaches use a variety of features such as security-sensitive APIs, system calls, control …

Multiple kernel learning (MKL) has been proposed for kernel methods by learning the
optimal kernel from a set of predefined base kernels. However, the traditional L 1 MKL …