A multiresolution data decomposition offers a fundamental framework supporting compression, progressive transmission, and level-of-detail (LOD) control for large two or three dime...
Wenli Cai, Georgios Sakas, Roberto Grosso, Thomas ...
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. ...
Complexity theory is a useful tool to study computational issues surrounding the elicitation of preferences, as well as the strategic manipulation of elections aggregating togethe...
—Autonomic Computing (AC) is an emerging paradigm aiming at simplifying the administration of complex computer systems. Efforts required to deploy and maintain complex systems ar...
Cornel Klein, Reiner N. Schmid, Christian Leuxner,...
Abstract. A Solovay function is a computable upper bound g for prefixfree Kolmogorov complexity K that is nontrivial in the sense that g agrees with K, up to some additive constan...