Sensor networks are unattended deeply distributed systems whose schema can be conceptualized using the relational model. Aggregation queries on the data sampled at each ode are th...
A general-purpose deformable registration algorithm referred
to as ”DRAMMS” is presented in this paper. DRAMMS adds to the
literature of registration methods that bridge betw...
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...