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Oznake: computer science;machine learning
Compressed Sensing reconstruction algorithms typically exhibit a zeroth-order phase transition phenomenon for large problem sizes, where there is a domain of problem sizes for which successful recovery occurs with overwhelming probability, and there is a domain of problem sizes for which recovery fa ...
Leto: 2009 Vir: videolectures.net
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Oznake: computer science;digital signal processing;machine learning;computational learning theory;deep learning;information theory;mathematics;statistics
Compressed sensing and matrix completion are techniques by which simplicity in data can be exploited for more efficient data acquisition. For instance, if a matrix is known to be (approximately) low rank then it can be recovered from few of its entries. The design and analysis of computationally eff ...
Leto: 2014 Vir: videolectures.net
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