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» On Deterministic Approximation of DNF
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CORR
2011
Springer
202views Education» more  CORR 2011»
13 years 2 months ago
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
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...
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
11 years 10 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
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
SIGMOD
2009
ACM
158views Database» more  SIGMOD 2009»
14 years 8 months ago
Simplifying XML schema: effortless handling of nondeterministic regular expressions
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...
SODA
2010
ACM
197views Algorithms» more  SODA 2010»
14 years 5 months ago
Quasirandom Load Balancing
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
CEC
2008
IEEE
14 years 2 months ago
A study on constrained MA using GA and SQP: Analytical vs. finite-difference gradients
— 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...