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CORR
2008
Springer
118views Education» more  CORR 2008»
13 years 8 months ago
Learning Low-Density Separators
Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
Shai Ben-David, Tyler Lu, Dávid Pál,...
CORR
2010
Springer
112views Education» more  CORR 2010»
13 years 8 months ago
Transdichotomous Results in Computational Geometry, II: Offline Search
We reexamine fundamental problems from computational geometry in the word RAM model, where input coordinates are integers that fit in a machine word. We develop a new algorithm fo...
Timothy M. Chan, Mihai Patrascu
ALGORITHMICA
2007
93views more  ALGORITHMICA 2007»
13 years 8 months ago
Random 2-SAT with Prescribed Literal Degrees
Two classic “phase transitions” in discrete mathematics are the emergence of a giant component in a random graph as the density of edges increases, and the transition of a rand...
Colin Cooper, Alan M. Frieze, Gregory B. Sorkin
IPSN
2005
Springer
14 years 1 months ago
QoM and lifetime-constrained random deployment of sensor networks for minimum energy consumption
— We consider the problem of energy efficient random deployment of sensor network. Our goal is to find the sensor node density, or alternatively, the energy resource density at e...
Morteza Maleki, Massoud Pedram
IJCNN
2008
IEEE
14 years 2 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris