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» Approximate Data Structures with Applications
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ECML
2006
Springer
15 years 10 months ago
Margin-Based Active Learning for Structured Output Spaces
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Dan Roth, Kevin Small
KDD
2006
ACM
146views Data Mining» more  KDD 2006»
16 years 6 months ago
Structure and evolution of online social networks
In this paper, we consider the evolution of structure within large online social networks. We present a series of measurements of two such networks, together comprising in excess ...
Ravi Kumar, Jasmine Novak, Andrew Tomkins
167
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RSKT
2010
Springer
15 years 4 months ago
Ordered Weighted Average Based Fuzzy Rough Sets
Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied t...
Chris Cornelis, Nele Verbiest, Richard Jensen
KDD
2008
ACM
224views Data Mining» more  KDD 2008»
16 years 6 months ago
The structure of information pathways in a social communication network
Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dyn...
Gueorgi Kossinets, Jon M. Kleinberg, Duncan J. Wat...
ACSAC
2004
IEEE
15 years 10 months ago
Vulnerabilities and Security Threats in Structured Overlay Networks: A Quantitative Analysis
1 A number of recent applications have been built on distributed hash tables (DHTs) based overlay networks. Almost all DHT-based schemes employ a tight deterministic data placement...
Mudhakar Srivatsa, Ling Liu