We describe spectral estimation principles that are useful for color balancing, color conversion, and sensor design. The principles extend conventional estimation methods, which r...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
We propose a view-dependent adaptive subdivision algorithm for rendering parametric surfaces on parallel hardware. Our framework allows us to bound the screen space error of a pie...
Christian Eisenacher, Quirin Meyer, Charles T. Loo...
The evolution strategy is one of the strongest evolutionary algorithms for optimizing real-value vectors. In this paper, we study how to use it for the evolution of prediction wei...
Hierarchical matrices (H-matrices) approximate matrices in a data-sparse way, and the approximate arithmetic for H-matrices is almost optimal. In this paper we present an algebrai...