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ICALP
2010
Springer
14 years 1 months ago
Network Design via Core Detouring for Problems without a Core
Some of the currently best-known approximation algorithms for network design are based on random sampling. One of the key steps of such algorithms is connecting a set of source nod...
Fabrizio Grandoni, Thomas Rothvoß
COLT
1999
Springer
14 years 1 months ago
Uniform-Distribution Attribute Noise Learnability
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
Nader H. Bshouty, Jeffrey C. Jackson, Christino Ta...
KDD
1998
ACM
145views Data Mining» more  KDD 1998»
14 years 1 months ago
Coincidence Detection: A Fast Method for Discovering Higher-Order Correlations in Multidimensional Data
Wepresent a novel, fast methodfor associationminingill high-dimensionaldatasets. OurCoincidence Detection method, which combines random sampling and Chernoff-Hoeffding bounds with...
Evan W. Steeg, Derek A. Robinson, Ed Willis
COCO
2009
Springer
113views Algorithms» more  COCO 2009»
14 years 1 months ago
Extractors for Low-Weight Affine Sources
We give polynomial time computable extractors for low-weight affince sources. A distribution is affine if it samples a random points from some unknown low dimensional subspace of ...
Anup Rao
AAAI
2007
13 years 11 months ago
Combining Multiple Heuristics Online
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...