1419 search results - page 101 / 284 » Approximation Methods for Supervised Learning |
115
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CSDA
2007
15 years 14 days ago
2007
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
121
Voted
ICML
2001
IEEE
16 years 1 months ago
2001
IEEE
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
119
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JMLR
2012
13 years 3 months ago
2012
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
127
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CVPR
2007
IEEE
16 years 2 months ago
2007
IEEE
This paper presents a new incremental learning solution for Linear Discriminant Analysis (LDA). We apply the concept of the sufficient spanning set approximation in each update st...
119
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CORR
2010
Springer
14 years 11 months ago
2010
Springer
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...