Many distributed software systems allow participation by large numbers of untrusted, potentially faulty components on an open network. As faults are inevitable in this setting, th...
Yuriy Brun, George Edwards, Jae Young Bang, Nenad ...
Abstract. Workload characterization is important for understanding how systems and services are used in practice and to help identify design improvements. To better understand the ...
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Modeling representations of image patches that are quasi-invariant to spatial deformations is an important problem in computer vision. In this paper, we propose a novel concept, t...
Jan Ernst, Maneesh Kumar Singh, Visvanathan Ramesh