We analyze a class of estimators based on a convex relaxation for solving highdimensional matrix decomposition problems. The observations are the noisy realizations of the sum of ...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
Whether beloved or despised, XML Schema is momentarily the only industrially accepted schema language for XML and is unlikely to become obsolete any time soon. Nevertheless, many ...
Geert Jan Bex, Wouter Gelade, Wim Martens, Frank N...
We propose a simple distributed algorithm for balancing indivisible tokens on graphs. The algorithm is completely deterministic, though it tries to imitate (and enhance) a random ...
Tobias Friedrich, Martin Gairing, Thomas Sauerwald
— Many deterministic algorithms in the context of constrained optimization require the first-order derivatives, or the gradient vectors, of the objective and constraint function...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...