2100 search results - page 139 / 420 » Learning to rank on graphs |
178
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NIPS
2000
15 years 7 months ago
2000
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
168
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is co...
180
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ICML
2009
IEEE
16 years 7 months ago
2009
IEEE
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
162
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ICPR
2010
IEEE
15 years 4 months ago
2010
IEEE
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
172
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ICML
2010
IEEE
15 years 7 months ago
2010
IEEE
We show that the mistake bound for predicting the nodes of an arbitrary weighted graph is characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the...