Continuous learning techniques with machine learning systems to adapt to new input data sets
Number of patents in Portfolio can not be more than 2000
United States of America Patent
Stats
-
Nov 29, 2022
Grant Date -
N/A
app pub date -
Oct 25, 2019
filing date -
Oct 25, 2019
priority date (Note) -
In Force
status (Latency Note)
Importance
Abstract
Continuous learning may include receiving a first neural network trained using a first training data set to predict outputs; determining whether the first neural network has a successful prediction rate greater than a prediction threshold; and responsive to determining the first neural network does not have a successful prediction rate greater than the prediction threshold, performing processing. The processing may include training the first neural network using a second training data set different than the first training data set; determining that a trigger condition has occurred, wherein the trigger condition includes detecting, during training of the first neural network using the second training data set, that a first weight of the first neural network has a corresponding weight change exceeding a threshold weight change; responsive to determining the trigger condition has occurred, reconfiguring the first neural network; and training the reconfigured first neural network using the second training data set.
First Claim
Family
International Classification(s)
Cited Art Landscape
Patent Citation Ranking
Advertisement
Advertisement
Advertisement
Recipient Email Address
Recipient Email Address
Comment
Recipient Email Address
Add to Portfolio(s)
To add this patent to one, or more, of your portfolios, simply click the add button.
This Patent is in these Portfolios:
Add to additional portfolios:
Last Refreshed On:
Changes done successfully