Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
Abstract. Littlestone developed a simple deterministic on-line learning algorithm for learning k-literal disjunctions. This algorithm (called Winnow) keeps one weight for each of t...
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
We present a novel parallel algorithm for fast continuous collision detection (CCD) between deformable models using multi-core processors. We use a hierarchical representation to ...