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NIPS
2007
15 years 2 months ago
Statistical Analysis of Semi-Supervised Regression
Semi-supervised methods use unlabeled data in addition to labeled data to construct predictors. While existing semi-supervised methods have shown some promising empirical performa...
John D. Lafferty, Larry A. Wasserman
86
Voted
ICML
2010
IEEE
15 years 1 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
105
Voted
COLT
2010
Springer
14 years 10 months ago
Learning to Create is as Hard as Learning to Appreciate
We explore the relationship between a natural notion of unsupervised learning studied by Kearns et al. (STOC '94), which we call here "learning to create" (LTC), an...
David Xiao
109
Voted
JMLR
2008
107views more  JMLR 2008»
15 years 17 days ago
A Library for Locally Weighted Projection Regression
In this paper we introduce an improved implementation of locally weighted projection regression (LWPR), a supervised learning algorithm that is capable of handling high-dimensiona...
Stefan Klanke, Sethu Vijayakumar, Stefan Schaal
COLING
2002
15 years 13 days ago
Identifying Anaphoric and Non-Anaphoric Noun Phrases to Improve Coreference Resolution
We present a supervised learning approach to identification of anaphoric and non-anaphoric noun phrases and show how such information can be incorporated into a coreference resolu...
Vincent Ng, Claire Cardie