1291 search results - page 220 / 259 » Learning Rules from Distributed Data |
125
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AAAI
2012
13 years 2 months ago
2012
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
159
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FOCS
2010
IEEE
14 years 9 months ago
2010
IEEE
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
103
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AAAI
2011
13 years 11 months ago
2011
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
ICIP
2006
IEEE
16 years 1 months ago
2006
IEEE
In this paper, we present a framework for the design of steganographic schemes that can provide provable security by achieving zero Kullback-Leibler divergence between the cover a...
101
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ICCBR
2005
Springer
15 years 5 months ago
2005
Springer
The problem of heterogeneous case representation poses a major obstacle to realising real-life multi-case-base reasoning (MCBR) systems. The knowledge overhead in developing and ma...