SYSTEM AND METHOD FOR LEARNING SPARSE FEATURES FOR SELF-SUPERVISED LEARNING WITH CONTRASTIVE DUAL GATING
Number of patents in Portfolio can not be more than 2000
United States of America
Stats
-
N/A
Issued Date -
Apr 25, 2024
app pub date -
Oct 25, 2023
filing date -
Oct 25, 2023
priority date (Note) -
Published
status (Latency Note)
Importance
Abstract
A method of training a machine learning algorithm comprises providing a set of input data, performing transforms on the input data to generate augmented data, to provide transformed base paths into machine learning algorithm encoders, segmenting the augmented data, calculating main base path outputs by applying a weighting to the segmented augmented data, calculating pruning masks from the input and augmented data to apply to the base paths of the machine learning algorithm encoders, the pruning masks having a binary value for each segment in the segmented augmented data, calculating sparse conditional path outputs by performing a computation on the segments of the segmented augmented data, and calculating a final output as a sum of the main base path outputs and the sparse conditional path outputs. A computer-implemented system for learning sparse features of a dataset is also disclosed.
First Claim
Family
International Classification(s)
Cited Art Landscape
Patent Citation Ranking
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