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» Privacy-Preserving k-NN for Small and Large Data Sets
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EMNLP
2007
15 years 24 days ago
Bootstrapping Feature-Rich Dependency Parsers with Entropic Priors
One may need to build a statistical parser for a new language, using only a very small labeled treebank together with raw text. We argue that bootstrapping a parser is most promis...
David A. Smith, Jason Eisner
NIPS
2007
15 years 23 days ago
Learning Bounds for Domain Adaptation
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
ICDM
2006
IEEE
146views Data Mining» more  ICDM 2006»
15 years 5 months ago
Boosting Kernel Models for Regression
This paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. Our main approach is built on...
Ping Sun, Xin Yao
NIPS
2001
15 years 22 days ago
Active Learning in the Drug Discovery Process
We investigate the following data mining problem from Computational Chemistry: From a large data set of compounds, find those that bind to a target molecule in as few iterations o...
Manfred K. Warmuth, Gunnar Rätsch, Michael Ma...
FUIN
2007
100views more  FUIN 2007»
14 years 11 months ago
Interpreted Nets
The nets considered here are an extension of Petri nets in two aspects. In the semantical aspect, there is no one firing rule common to all transitions, but every transition is tr...
Ludwik Czaja