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» Practical Preference Relations for Large Data Sets
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VLDB
2007
ACM
181views Database» more  VLDB 2007»
16 years 5 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...
IUI
2006
ACM
15 years 11 months ago
Enabling context-sensitive information seeking
1 Information seeking is an important but often difficult task especially when involving large and complex data sets. We hypothesize that a context-sensitive interaction paradigm c...
Michelle X. Zhou, Keith Houck, Shimei Pan, James S...
BMCBI
2006
165views more  BMCBI 2006»
15 years 5 months ago
Improved variance estimation of classification performance via reduction of bias caused by small sample size
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
Ulrika Wickenberg-Bolin, Hanna Göransson, M&a...
VISUALIZATION
1997
IEEE
15 years 9 months ago
Multiresolution compression and reconstruction
This paper presents a framework for multiresolution compression and geometric reconstruction of arbitrarily dimensioned data designed for distributed applications. Although being ...
Oliver G. Staadt, Markus H. Gross, Roger Weber
ESA
2004
Springer
105views Algorithms» more  ESA 2004»
15 years 11 months ago
Time Dependent Multi Scheduling of Multicast
Many network applications that need to distribute content and data to a large number of clients use a hybrid scheme in which one (or more) multicast channel is used in parallel to...
Rami Cohen, Dror Rawitz, Danny Raz