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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 7 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
STOC
2004
ACM
61views Algorithms» more  STOC 2004»
14 years 7 months ago
The zero-one principle for switching networks
Recently, approximation analysis has been extensively used to study algorithms for routing weighted packets in various network settings. Although different techniques were applied...
Yossi Azar, Yossi Richter
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
14 years 7 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
DAC
2008
ACM
13 years 8 months ago
DeMOR: decentralized model order reduction of linear networks with massive ports
Model order reduction is an efficient technique to reduce the system complexity while producing a good approximation of the input-output behavior. However, the efficiency of reduc...
Boyuan Yan, Lingfei Zhou, Sheldon X.-D. Tan, Jie C...
IHI
2010
197views Healthcare» more  IHI 2010»
13 years 1 months ago
Beyond safe harbor: automatic discovery of health information de-identification policy alternatives
Regulations in various countries permit the reuse of health information without patient authorization provided the data is "de-identified". In the United States, for ins...
Kathleen Benitez, Grigorios Loukides, Bradley Mali...