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US 11,392,796 B2Granted
Feature dictionary for bandwidth enhancement
AssigneeMicron Technology, Inc.
InventorsKenneth Marion Curewitz, Ameen D. Akel, Hongyu Wang, Sean Stephen Eilert
Life of this patent
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Abstract
A system having multiple devices that can host different versions of an artificial neural network (ANN) as well as different versions of a feature dictionary. In the system, encoded inputs for the ANN can be decoded by the feature dictionary, which allows for encoded input to be sent to a master version of the ANN over a network instead of an original version of the input which usually includes more data than the encoded input. Thus, by using the feature dictionary for training of a master ANN there can be reduction of data transmission.
Claims18
A method, comprising:
- hosting, by a first computing device, a master version of an artificial neural network (ANN);
- hosting, by the first computing device, a master version of a feature dictionary;
- receiving, by the first computing device, encoded features from a second computing device, wherein the received encoded features are encoded by the second computing device according to a local version of the feature dictionary hosted by the second computing device;
- decoding, by the first computing device, the received encoded features according to the master version of the feature dictionary;
- and
- training, by the first computing device, the master version of the ANN based on the decoded features using machine learning;
- wherein, in response to the local version of the feature dictionary of the second computing device not including features extracted from user data hosted by the second computing device, the local version of the feature dictionary is changed to be based on the extracted features and the extracted features are encoded according to the changed local version of the feature dictionary.
4 more elements
A method, comprising:
- hosting, by a second computing device, a local version of an artificial neural network (ANN);
- hosting, by the second computing device, a local version of a feature dictionary;
- extracting, by the second computing device, features from user data hosted by the second computing device;
- determining, by the second computing device, whether the extracted features are included in the local version of the feature dictionary;
- in response to the local version of the feature dictionary including the extracted features, encoding, by the second computing device, the extracted features according to the local version of the feature dictionary;
- in response to the local version of the feature dictionary not including the extracted features, changing the local version of the feature dictionary based on the extracted features and encoding the extracted features according to the changed local version of the feature dictionary;
- and
- transmitting, by the second computing device, the encoded features to a first computing device that hosts a master version of the ANN so that the encoded features are decoded by a master version of the feature dictionary hosted by the first computing device and then used as input to train the master version of the ANN using machine learning.
5 more elements
A system, comprising:
- a first computing device comprising:
- memory configured to:
- store a master version of an artificial neural network (ANN);
- and
- store a master version of a feature dictionary;
- transceiver configured to receive encoded features from a second computing device;
- and
- a processor configured to:
- decode the received encoded features according to the master version of the feature dictionary;
- and
- train the master version of the ANN based on the decoded features using machine learning;
- and
- the second computing device comprises:
- memory configured to:
- store user data;
- store a local version of the ANN;
- and
- store the local version of the feature dictionary;
- a processor configured to:
- extract features from the stored user data;
- and
- encode the extracted features according to the local version of the feature dictionary;
- and
- a transceiver configured to transmit the encoded features to the first computing device so that the encoded features are decoded by the master version of the feature dictionary and then used as input to train the master version of the ANN using the machine learning.
21 more elements
Dependencies are inferred from the claim text.