Deep Learning Through Sparse And Low-rank Modeling

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Deep Learning Through Sparse And Low-rank Modeling

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Deep Learning Through Sparse And Low-rank Modeling

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Deep Learning Through Sparse And Low-rank Modeling

Deep Learning Through Sparse Representation And Low-rank Modeling Bridges Classical Sparse And Low Rank Models-those That Emphasize Problem-specific Interpretability-with Recent Deep Network Models That Have Enabled A Larger Learning Capacity And Better Utilization Of Big Data. It Shows How The Toolkit Of Deep Learning Is Closely Tied With The Sparselow Rank Methods And Algorithms, Providing A Rich Variety Of Theoretical And Analytic Tools To Guide The Design And Interpretation Of Deep Learning Models. The Development Of The Theory And Models Is Supported By A Wide Variety Of Applications In Computer Vision, Machine Learning, Signal Processing, And Data Mining.
  • Brand: Elsevier Inc
  • Category: Computing & Internet
  • Format: Paperback
  • Language: English
  • Publication Date: 2019-04-12
  • Publisher / Label: Elsevier Inc
  • Author: Zhangyan Wang
  • Number of Pages: 296
  • Fruugo ID: 550905470-1115583445
  • ISBN: 9780128136591
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