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» Pseudorandomness for network algorithms
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STOC
2005
ACM
129views Algorithms» more  STOC 2005»
16 years 7 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
STOC
2004
ACM
150views Algorithms» more  STOC 2004»
16 years 7 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
2009
ACM
125views Database» more  SIGMOD 2009»
16 years 7 months ago
Top-k queries on uncertain data: on score distribution and typical answers
Uncertain data arises in a number of domains, including data integration and sensor networks. Top-k queries that rank results according to some user-defined score are an important...
Tingjian Ge, Stanley B. Zdonik, Samuel Madden
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Voted
SIGMOD
2007
ACM
167views Database» more  SIGMOD 2007»
16 years 6 months ago
Data currency in replicated DHTs
Distributed Hash Tables (DHTs) provide a scalable solution for data sharing in P2P systems. To ensure high data availability, DHTs typically rely on data replication, yet without ...
Reza Akbarinia, Esther Pacitti, Patrick Valduriez
PODS
2008
ACM
109views Database» more  PODS 2008»
16 years 6 months ago
Time-decaying aggregates in out-of-order streams
Processing large data streams is now a major topic in data management. The data involved can be truly massive, and the required analyses complex. In a stream of sequential events ...
Graham Cormode, Flip Korn, Srikanta Tirthapura
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