A novel method and a framework called Memory-Based Forecasting are proposed to forecast complex and timevarying natural patterns with the goal of supporting experts' decision...
This paper presents a new technique which incrementally builds a hierarchical discriminant regression (IHDR) tree for generation of motion based robot reactions. The robot learned...
In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
We propose a novel approach to encapsulate non-deterministic computations in functional logic programs. Our approach is based on set functions that return the set of all the resul...