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» Optimizing the distribution of large data sets in theory and...
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VLDB
2007
ACM
181views Database» more  VLDB 2007»
14 years 7 months ago
STAR: Self-Tuning Aggregation for Scalable Monitoring
We present STAR, a self-tuning algorithm that adaptively sets numeric precision constraints to accurately and efficiently answer continuous aggregate queries over distributed data...
Navendu Jain, Michael Dahlin, Yin Zhang, Dmitry Ki...
SDM
2003
SIAM
129views Data Mining» more  SDM 2003»
13 years 9 months ago
Approximate Query Answering by Model Averaging
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
Dmitry Pavlov, Padhraic Smyth
GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
14 years 14 days ago
The maximum hypervolume set yields near-optimal approximation
In order to allow a comparison of (otherwise incomparable) sets, many evolutionary multiobjective optimizers use indicator functions to guide the search and to evaluate the perfor...
Karl Bringmann, Tobias Friedrich
INFOCOM
2009
IEEE
14 years 2 months ago
Distributed Opportunistic Scheduling With Two-Level Channel Probing
Distributed opportunistic scheduling (DOS) is studied for wireless ad-hoc networks in which many links contend for the channel using random access before data transmissions. Simpl...
P. S. Chandrashekhar Thejaswi, Junshan Zhang, Man-...
TON
2010
136views more  TON 2010»
13 years 2 months ago
Distributed Opportunistic Scheduling With Two-Level Probing
Distributed opportunistic scheduling (DOS) is studied for wireless ad-hoc networks in which many links contend for the channel using random access before data transmissions. Simpl...
P. S. Chandrashekhar Thejaswi, Junshan Zhang, Man-...