Invention Grant
- Patent Title: Automatic tuning of machine learning parameters for non-stationary e-commerce data
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Application No.: US16659092Application Date: 2019-10-21
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Publication No.: US11521254B2Publication Date: 2022-12-06
- Inventor: Tomer Lancewicki , Selcuk Kopru
- Applicant: eBay Inc.
- Applicant Address: US CA San Jose
- Assignee: eBay Inc.
- Current Assignee: eBay Inc.
- Current Assignee Address: US CA San Jose
- Agency: FIG. 1 Patents
- Main IPC: G06Q30/06
- IPC: G06Q30/06 ; G06N20/00 ; G06F17/16 ; G06N3/04 ; G06F40/58

Abstract:
Techniques are disclosed for automatically adjusting machine learning parameters in an e-commerce system. Hyperparameters of a machine learning component are tuned using a gradient estimator and a first training set representative of an e-commerce context. The machine learning component is trained using the tuned hyperparameters and the first training set. The hyperparameters are automatically re-tuned using the gradient estimator and a second training set representative of a changed e-commerce context. The machine learning component is re-trained using the re-tuned hyperparameters and the second training set.
Public/Granted literature
- US20210042811A1 AUTOMATIC TUNING OF MACHINE LEARNING PARAMETERS FOR NON-STATIONARY E-COMMERCE DATA Public/Granted day:2021-02-11
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