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TCC
2009
Springer
117views Cryptology» more  TCC 2009»
16 years 7 months ago
Towards a Theory of Extractable Functions
Extractable functions are functions where any adversary that outputs a point in the range of the function is guaranteed to "know" a corresponding preimage. Here, knowledg...
Ran Canetti, Ronny Ramzi Dakdouk
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 7 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 7 months ago
User grouping behavior in online forums
Online forums represent one type of social media that is particularly rich for studying human behavior in information seeking and diffusing. The way users join communities is a re...
Xiaolin Shi, Jun Zhu, Rui Cai, Lei Zhang
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
16 years 7 months ago
Learning from multi-topic web documents for contextual advertisement
Contextual advertising on web pages has become very popular recently and it poses its own set of unique text mining challenges. Often advertisers wish to either target (or avoid) ...
Yi Zhang, Arun C. Surendran, John C. Platt, Mukund...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 7 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