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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 1 days 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
76
Voted
ICNC
2009
Springer
15 years 6 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 ...
100
Voted
ICASSP
2011
IEEE
14 years 3 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
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 5 days 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»
15 years 12 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...