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PODS
2011
ACM
238views Database» more  PODS 2011»
14 years 9 months ago
Beyond simple aggregates: indexing for summary queries
Database queries can be broadly classified into two categories: reporting queries and aggregation queries. The former retrieves a collection of records from the database that mat...
Zhewei Wei, Ke Yi
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
16 years 7 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
ASPLOS
2010
ACM
16 years 1 months ago
MacroSS: macro-SIMDization of streaming applications
SIMD (Single Instruction, Multiple Data) engines are an essential part of the processors in various computing markets, from servers to the embedded domain. Although SIMD-enabled a...
Amir Hormati, Yoonseo Choi, Mark Woh, Manjunath Ku...
CORR
2006
Springer
153views Education» more  CORR 2006»
15 years 6 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
DEBU
1998
95views more  DEBU 1998»
15 years 6 months ago
What can you do with a Web in your Pocket?
The amount of information available online has grown enormously over the past decade. Fortunately, computing power, disk capacity, and network bandwidth have also increased dramat...
Sergey Brin, Rajeev Motwani, Lawrence Page, Terry ...