We consider the problem of detecting a large number of different object classes in cluttered scenes. Traditional approaches require applying a battery of different classifiers to ...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
Typestate analysis determines whether a program violates a set of finite-state properties. Because the typestate-analysis problem is statically undecidable, researchers have propo...
Correct and efficient implementation of general real-time applications remains by far an open problem. A key issue is meeting timing constraints whose satisfaction depends on feat...
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...