We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Abstract. We show how to represent sets in a linear space data structure such that expressions involving unions and intersections of sets can be computed in a worst-case efficient ...
Radial basis function network (RBF) kernels are widely used for support vector machines (SVMs). But for model selection of an SVM, we need to optimize the kernel parameter and the ...
Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm...
Abstract— A key enabler of the recently popularized, assemblycentric development approach for distributed real-time software systems is QoS-enabled middleware, which provides reu...
Swapna S. Gokhale, Paul J. Vandal, Aniruddha S. Go...