Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Abstract. Due to its prominence in artificial intelligence and theoretical computer science, the propositional satisfiability problem (SAT) has received considerable attention in...
We set out an object localization scheme based on a convex programming matching method. The proposed approach is designed to match general objects, especially objects with very li...
The k-nearest neighbour (kNN) rule is a simple and effective method for multi-way classification that is much used in Computer Vision. However, its performance depends heavily on ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many appl...