Learning Structure with the Trace Norm Distribution
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چکیده
We consider the problem of learning model structure. We assume that data is generated by one or more trace norm distributions [3]. We find that, as with other unsupervised problems, there are a number of equallycorrrect solutions. Which solution is best depends on the interpretation of distances in the data space. 1 Trace Norm Distribution Let X ∈ R. The trace norm distribution is defined as P λ (X) = 1 Z λ exp(−λ‖X‖Σ), (1) where the superscript is not exponentiation, but rather a designation that the distribution is specific to the matrix size. ‖X‖Σ is the trace norm of X (the sum of singular values of X), and Z λ = ∫
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تاریخ انتشار 2006