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111
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JMLR
2010
14 years 9 months ago
2010
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
150
Voted
CVPR
2012
IEEE
13 years 5 months ago
2012
IEEE
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
155
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UAI
1998
15 years 4 months ago
1998
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
117
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ICML
2002
IEEE
16 years 3 months ago
2002
IEEE
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
118
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GECCO
2004
Springer
15 years 8 months ago
2004
Springer
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...