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ICALP
2010
Springer
15 years 11 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
15 years 10 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»
15 years 10 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»
15 years 10 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
15 years 8 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...