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Importantly, increasing α also increases the runtime of the algorithm significantly, such that one often needs to compromise on the sparsity of the network to keep computations feasible.
However, for such cases the cross-validation errors are not as good as the one obtained through the learning algorithm on the sparsity parameter.
3. Estimate the source representation based on the sparsity assumption.
More importantly, the optimal value λopt depends approximately monotonously on the sparsity of the training set.
Based on the sparsity of various frequency components, the coefficients are sampled at different sampling rates.
Our model does not require prior knowledge on the sparsity of the signal.
Similar(19)
There are now many published works on the sparsity-based models and methods [5].
When working at the granularity of individual venues in an on-line manner, the sparsity of the data becomes a real concern.
On the contrary, the sparsity penalty forces sMBPLS to focus on 'local' (i.e. across a small subsets of variables and samples) peaks in the covariance, which correspond to (multi-dimensional) modules of relatively small size.
With an appealing sparsity processing framework, CS focuses essentially on the signal sparsity which can be observed in any domain, e.g., time domain, frequency domain, and wavelet domain.
On the other hand, the sparsity constraint cannot reproduce a smooth distribution.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com