3449 search results - page 406 / 690 » A Framework for Multiple-Instance Learning |
127
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
148
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...
130
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be expressed as the sum of lower-d...
111
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
The dynamic hierarchical Dirichlet process (dHDP) is developed to model the timeevolving statistical properties of sequential data sets. The data collected at any time point are r...
119
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ICML
2006
IEEE
16 years 5 months ago
2006
IEEE
In this paper we study a new framework introduced by Vapnik (1998) and Vapnik (2006) that is an alternative capacity concept to the large margin approach. In the particular case o...