Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
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...
The Collect problem for an asynchronous shared-memory system has the objective for the processors to learn all values of a collection of shared registers, while minimizing the tot...
Bogdan S. Chlebus, Dariusz R. Kowalski, Alexander ...
We propose a mathematical framework for query selection as a mechanism for reducing the cost of constructing information retrieval test collections. In particular, our mathematica...
Mehdi Hosseini, Ingemar J. Cox, Natasa Milic-Frayl...
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...