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» Model Kit for Lightweight Data Compression Algorithms
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KDD
2007
ACM
137views Data Mining» more  KDD 2007»
16 years 2 months ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
ICNC
2009
Springer
15 years 9 months ago
Estimating Strength of Concrete Using a Grammatical Evolution
The main purpose of this paper is to propose an incorporating a grammatical evolution (GE) into the genetic algorithm (GA), called GEGA, and apply it to estimate the compressive s...
Hsun-Hsin Hsu, Li Chen, Chang-Huan Kou, Tai-Sheng ...
ICASSP
2011
IEEE
14 years 6 months ago
Group testing meets traitor tracing
This paper links two a priori different topics, group testing and traitor tracing. Group testing, as an instantiation of a compressed sensing problem over binary data, is indeed e...
Peter Meerwald, Teddy Furon
125
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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 2 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
SIGMOD
2009
ACM
197views Database» more  SIGMOD 2009»
16 years 2 months ago
Secure kNN computation on encrypted databases
Service providers like Google and Amazon are moving into the SaaS (Software as a Service) business. They turn their huge infrastructure into a cloud-computing environment and aggr...
Wai Kit Wong, David Wai-Lok Cheung, Ben Kao, Nikos...