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IJON
2011
90views more  IJON 2011»
14 years 8 months ago
Fault tolerant machine learning for nanoscale cognitive radio
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo
ICML
2003
IEEE
16 years 5 months ago
Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
Wee Sun Lee, Bing Liu
COLT
2007
Springer
15 years 11 months ago
Property Testing: A Learning Theory Perspective
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
Dana Ron
NIPS
1997
15 years 6 months ago
Learning to Order Things
There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order, given feedback in the form of ...
William W. Cohen, Robert E. Schapire, Yoram Singer
FUIN
2008
108views more  FUIN 2008»
15 years 3 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel