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STOC
2004
ACM
150views Algorithms» more  STOC 2004»
14 years 8 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking
SIGMOD
2008
ACM
164views Database» more  SIGMOD 2008»
14 years 8 months ago
Finding frequent items in probabilistic data
Computing statistical information on probabilistic data has attracted a lot of attention recently, as the data generated from a wide range of data sources are inherently fuzzy or ...
Qin Zhang, Feifei Li, Ke Yi
MOBIHOC
2008
ACM
14 years 7 months ago
Localized distance-sensitive service discovery in wireless sensor networks
In this paper, we identify a new problem in wireless sensor networks, distance sensitive service discovery, where nearby or closest service selection guarantee is expected. We pro...
Xu Li, Nicola Santoro, Ivan Stojmenovic
MOBIHOC
2005
ACM
14 years 7 months ago
Low-coordination topologies for redundancy in sensor networks
Tiny, low-cost sensor devices are expected to be failure-prone and hence in many realistic deployment scenarios for sensor networks these nodes are deployed in higher than necessa...
Rajagopal Iyengar, Koushik Kar, Suman Banerjee
SODA
2010
ACM
189views Algorithms» more  SODA 2010»
14 years 5 months ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy
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