In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Recently, instead of selecting a single kernel, multiple kernel learning (MKL) has been proposed which uses a convex combination of kernels, where the weight of each kernel is opt...
Natural Language Processing (NLP) for Information Retrieval has always been an interesting and challenging research area. Despite the high expectations, most of the results indica...