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CORR
2012
Springer
14 years 7 days ago
2012
Springer
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
161
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CORR
2012
Springer
14 years 7 days ago
2012
Springer
Most theoretical definitions about the complexity of manipulating elections focus on the decision problem of recognizing which instances can be successfully manipulated, rather t...
166
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CORR
2012
Springer
14 years 7 days ago
2012
Springer
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
164
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CORR
2012
Springer
14 years 7 days ago
2012
Springer
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
184
click to vote
CORR
2012
Springer
14 years 7 days ago
2012
Springer
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...