— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
While Bayesian methods can significantly improve the quality of tomographic reconstructions, they require the solution of large iterative optimization problems. Recent results ind...
Statistical timing analysis has been widely applied to predict the timing yield of VLSI circuits when process variations become significant. Existing statistical latch timing met...
We give an unified convergence analysis of ensemble learning methods including e.g. AdaBoost, Logistic Regression and the Least-SquareBoost algorithm for regression. These methods...
We investigate a new, fast and provably convergentMAP reconstruction algorithm for emission tomography. The new algorithm, termed C-OSEM has its origin in the alternating algorith...