Invention Grant
- Patent Title: Prediction filtering using intermediate model representations
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Application No.: US15623291Application Date: 2017-06-14
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Publication No.: US11080596B1Publication Date: 2021-08-03
- Inventor: Roshan Harish Makhijani , Soo-Min Pantel , Sanjeev Jain , Gaurav Chanda
- Applicant: Amazon Technologies, Inc.
- Applicant Address: US WA Seattle
- Assignee: Amazon Technologies, Inc.
- Current Assignee: Amazon Technologies, Inc.
- Current Assignee Address: US WA Seattle
- Agency: Knobbe, Martens, Olson & Bear, LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N5/04 ; G06F7/523 ; G06N3/04

Abstract:
The present disclosure is directed to filtering co-occurrence data. In one embodiment, a machine learning model can be trained. An output of an intermediate structure of the machine learning model (e.g., an output of an internal layer of a neural network) can be used as a representation of an event. Similarities between representations of events can be determined and used to generate, augment, or modify co-occurrence data.
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