Adaptive Monte Carlo methods are simulation efficiency improvement techniques designed to adaptively tune simulation estimators. Most of the work on adaptive Monte Carlo methods h...
This paper proposes a new connectionist approach to numeric law discovery; i.e., neural networks (law-candidates) are trained by using a newly invented second-order learning algor...
Shared and mutable data-structures pose major problems in static analysis and most analyzers are unable to keep track of the values of numeric variables stored in the heap. In this...
We propose a method to recover the global structure with local details around a point. To handle a large scale of motion i.e. 360 degree around the point, we use an optimization-b...
Siu-Hang Or, Kin-hong Wong, Michael Ming-Yuen Chan...
We describe how to teach deformable models to maximize image segmentation correctness based on user-specified criteria, and we present a method for evaluating which criteria work ...