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» On learning with dissimilarity functions
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COLT
2001
Springer
15 years 10 months ago
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
Peter L. Bartlett, Shahar Mendelson
PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
16 years 21 days ago
Subspace Regularization: A New Semi-supervised Learning Method
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-L...
170
Voted
AI
2008
Springer
15 years 6 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...
SIGIR
2008
ACM
15 years 6 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
FOCS
2002
IEEE
15 years 11 months 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