We present an algorithm designed for navigating around a performance that was filmed as a “casual” multi-view video collection: real-world footage captured on hand held camer...
Luca Ballan, Gabriel J. Brostow, Jens Puwein, Marc...
The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
In current research, the minimum cycle times of finite state machines are estimated by computing the delays of the combinational logic in the finite state machines. Even though th...
William K. C. Lam, Robert K. Brayton, Alberto L. S...