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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 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
FOCS
2002
IEEE
14 years 17 days ago
Learning Intersections and Thresholds of Halfspaces
We give the first polynomial time algorithm to learn any function of a constant number of halfspaces under the uniform distribution on the Boolean hypercube to within any constan...
Adam Klivans, Ryan O'Donnell, Rocco A. Servedio
KAIS
2006
126views more  KAIS 2006»
13 years 7 months ago
Fast and exact out-of-core and distributed k-means clustering
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Ruoming Jin, Anjan Goswami, Gagan Agrawal
TMC
2008
112views more  TMC 2008»
13 years 7 months ago
Throughput Analysis and Measurements in IEEE 802.11 WLANs with TCP and UDP Traffic Flows
There is a vast literature on the throughput analysis of the IEEE 802.11 media access control (MAC) protocol. However, very little has been done on investigating the interplay betw...
Raffaele Bruno, Marco Conti, Enrico Gregori
POPL
2011
ACM
12 years 10 months ago
Dynamic inference of static types for ruby
There have been several efforts to bring static type inference to object-oriented dynamic languages such as Ruby, Python, and Perl. In our experience, however, such type inference...
Jong-hoon (David) An, Avik Chaudhuri, Jeffrey S. F...