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Even in the case that training frames are sparse and imbalance, according to maximum likelihood estimation (MLE) of the EM auxiliary function defined in the proof of proposition 3 in [2], entire Gaussian components are adapted at same weight, adapting weight corresponding to entire Gaussian components is denoted by i-vector.
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CS takes advantage of the fact that the difference between two correlated frames is sparse and uses this information to again compressively sample the difference between two encoded frames.
The sentences are sparse.
Crowds are sparse or nonexistent.
So laughs are sparse there.
Some are sparse, some poetic.
True, vivifying details are sparse.
Inside, things are sparse enough.
For now, amenities are sparse.
Again, the statistics are sparse.
Entertainment offerings in Maya are sparse.
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