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CVPR
2004
IEEE
14 years 12 months ago
Is Bottom-Up Attention Useful for Object Recognition?
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Ueli Rutishauser, Dirk Walther, Christof Koch, Pie...
IS
2010
13 years 7 months ago
Multicriteria reinforcement learning based on a Russian doll method for network routing
The routing in communication networks is typically a multicriteria decision making (MCDM) problem. However, setting the parameters of most used MCDM methods to fit the preferences ...
Alain Pétrowski, Farouk Aissanou, Ilham Ben...
CHI
2010
ACM
14 years 4 months ago
Examining multiple potential models in end-user interactive concept learning
End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
ECML
2004
Springer
14 years 3 months ago
Associative Clustering
This report contains derivations which did not fit into the paper [3]. Associative clustering (AC) is a method for separately clustering two data sets when one-to-one association...
Janne Sinkkonen, Janne Nikkilä, Leo Lahti, Sa...
COLT
2007
Springer
14 years 4 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