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» On learning with dissimilarity functions
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NIPS
2003
15 years 8 months ago
Semi-Supervised Learning with Trees
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
Charles Kemp, Thomas L. Griffiths, Sean Stromsten,...
CORR
2010
Springer
94views Education» more  CORR 2010»
15 years 6 months ago
Tight Sample Complexity of Large-Margin Learning
We obtain a tight distribution-specific characterization of the sample complexity of large-margin classification with L2 regularization: We introduce the -adapted-dimension, which...
Sivan Sabato, Nathan Srebro, Naftali Tishby
RECOMB
2005
Springer
16 years 7 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
MM
2004
ACM
167views Multimedia» more  MM 2004»
16 years 2 days ago
Learning an image manifold for retrieval
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Xiaofei He, Wei-Ying Ma, HongJiang Zhang
CIKM
2010
Springer
15 years 5 months ago
Learning to rank relevant and novel documents through user feedback
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Abhimanyu Lad, Yiming Yang