This paper presents a new technique for approximating range images by means of adaptive triangular meshes with a bounded approximation error and without applying optimization. Thi...
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
This paper gives an overview of recent work on machine models for processing massive amounts of data. The main focus is on generalizations of the classical data stream model where...
We present the MBRAM model for static evaluation of the performance of memory-bound programs. The MBRAM model predicts the actual running time of a memory-bound program directly fr...
Fitting statistical 2D and 3D shape models to images is necessary for a variety of tasks, such as video editing and face recognition. Much progress has been made on local fitting...