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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
KDD
2007
ACM
141views Data Mining» more  KDD 2007»
14 years 8 months ago
Mining favorable facets
The importance of dominance and skyline analysis has been well recognized in multi-criteria decision making applications. Most previous studies assume a fixed order on the attribu...
Raymond Chi-Wing Wong, Jian Pei, Ada Wai-Chee Fu, ...
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 8 months ago
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...
CHI
2003
ACM
14 years 8 months ago
With similar visual angles, larger displays improve spatial performance
Large wall-sized displays are becoming prevalent. Although researchers have articulated qualitative benefits of group work on large displays, little work has been done to quantify...
Desney S. Tan, Darren Gergle, Peter Scupelli, Rand...
STOC
2007
ACM
137views Algorithms» more  STOC 2007»
14 years 8 months ago
Testing k-wise and almost k-wise independence
In this work, we consider the problems of testing whether a distribution over {0, 1}n is k-wise (resp. ( , k)-wise) independent using samples drawn from that distribution. For the...
Noga Alon, Alexandr Andoni, Tali Kaufman, Kevin Ma...