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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 7 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 23 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 6 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