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US Patent 10223635 Model compression and fine-tuning

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10223635
Patent Inventor Names
David Jonathan Julian12
Venkata Sreekanta Reddy Annapureddy12
Daniel Hendricus Franciscus Dijkman12
Date of Patent
March 5, 2019
Patent Application Number
14846579
Date Filed
September 4, 2015
Patent Citations Received
‌
US Patent 11972108 Parameter redundancy reduction method
1
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US Patent 11620435 Domain specific model compression
2
‌
US Patent 11651198 Data processing method and apparatus for neural network
3
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US Patent 11663476 Method and device for providing compression and transmission of training parameters in distributed processing environment
4
‌
US Patent 11842265 Processor chip and control methods thereof
5
‌
US Patent 11948062 Compressed recurrent neural network models
6
‌
US Patent 11462033 Method and system for performing classification of real-time input sample using compressed classification model
‌
US Patent 10716089 Deployment of trained neural network based RSS fingerprint dataset
9
...
Patent Primary Examiner
‌
Dave Misir
Patent abstract

Compressing a machine learning network, such as a neural network, includes replacing one layer in the neural network with compressed layers to produce the compressed network. The compressed network may be fine-tuned by updating weight values in the compressed layer(s).

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