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» Random Sampling Techniques in Parallel Computation
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ICICS
2005
Springer
15 years 3 months ago
Private Itemset Support Counting
Private itemset support counting (PISC) is a basic building block of various privacy-preserving data mining algorithms. Briefly, in PISC, Client wants to know the support of her i...
Sven Laur, Helger Lipmaa, Taneli Mielikäinen
ICDE
2007
IEEE
167views Database» more  ICDE 2007»
15 years 4 months ago
Load Shedding for Window Joins on Multiple Data Streams
We consider the problem of semantic load shedding for continuous queries containing window joins on multiple data streams and propose a robust approach that is effective with the ...
Yan-Nei Law, Carlo Zaniolo
ICS
2009
Tsinghua U.
15 years 4 months ago
Fast and scalable list ranking on the GPU
General purpose programming on the graphics processing units (GPGPU) has received a lot of attention in the parallel computing community as it promises to offer the highest perfo...
M. Suhail Rehman, Kishore Kothapalli, P. J. Naraya...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
15 years 10 months ago
Practical guide to controlled experiments on the web: listen to your customers not to the hippo
The web provides an unprecedented opportunity to evaluate ideas quickly using controlled experiments, also called randomized experiments (single-factor or factorial designs), A/B ...
Ron Kohavi, Randal M. Henne, Dan Sommerfield
73
Voted
AAAI
2007
14 years 12 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...