1419 search results - page 149 / 284 » Approximation Methods for Supervised Learning |
115
Voted
NIPS
2004
15 years 2 months ago
2004
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
124
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ICML
2004
IEEE
16 years 1 months ago
2004
IEEE
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
134
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KDD
2009
ACM
16 years 1 months ago
2009
ACM
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
130
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KDD
2008
ACM
16 years 1 months ago
2008
ACM
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
149
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ACCV
2010
Springer
14 years 7 months ago
2010
Springer
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...