HIGH-CAPACITY MACHINE LEARNING SYSTEM
First Claim
Patent Images
1. A method, comprising:
- applying at least two learning models to multiple data sets indicative of features associated with tuples of objects, each tuple being a pairing of a first object and a second object;
updating parameters of a prediction model based on a linear combination of at least two result sets corresponding to the at least two learning models;
receiving a request for identifying a compatible object for a given object based on respective features of the compatible object and the given object;
responsive to the received request, determining, based on the updated parameters of the prediction model, a prediction value associated with the given object, the prediction value indicative of a probability of compatibility based on the respective features; and
identifying the compatible object for the given object based on the prediction value.
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Abstract
The present disclosure is directed to a high-capacity training and prediction machine learning platform that can support high-capacity parameter models (e.g., with 10 billion weights). The platform implements a generic feature transformation layer for joint updating and a distributed training framework utilizing shard servers to increase training speed for the high-capacity model size. The models generated by the platform can be utilized in conjunction with existing dense baseline models to predict compatibilities between different groupings of objects (e.g., a group of two objects, three objects, etc.).
35 Citations
20 Claims
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1. A method, comprising:
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applying at least two learning models to multiple data sets indicative of features associated with tuples of objects, each tuple being a pairing of a first object and a second object; updating parameters of a prediction model based on a linear combination of at least two result sets corresponding to the at least two learning models; receiving a request for identifying a compatible object for a given object based on respective features of the compatible object and the given object; responsive to the received request, determining, based on the updated parameters of the prediction model, a prediction value associated with the given object, the prediction value indicative of a probability of compatibility based on the respective features; and identifying the compatible object for the given object based on the prediction value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A system, comprising:
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a training system configured to; preprocess multiple data sets associated with tuples of objects; and analyze the multiple data sets to update parameters of a prediction model, wherein to analyze includes; apply a first learning model to generate a first result set; and apply a second learning model to generate a second result set, wherein the parameters are updated based on a linear combination of the first and second result sets; and a prediction system configured to; determine, responsive to a request for identifying a compatible object for a given object, a prediction value associated with the given object based on the updated parameters of the prediction mode; and identify the compatible object for the given object based on the prediction value. - View Dependent Claims (17, 18)
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19. A computer readable storage medium storing instructions that when executed by a processor causes the processor to implement a process, the instructions comprising:
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instructions for preprocessing multiple data sets by parsing at least a first data set and a second data set, the first data set including data indicative of a first feature shared between the first object and the second object, the second data set including a second feature shared between the first object and the second object; instructions for applying a first learning model to the multiple data sets to generate a first result set; instructions for applying a second learning model to the multiple data sets to generate a second result set; instructions for updating parameters of a prediction model based on a linear combination of the first result set and the second result set; instructions for determining, in response to a request for identifying a compatible object for a given object, a prediction value associated with the given object based on the updated parameters of the prediction model, the prediction value indicative of a probability of compatibility; and identifying the compatible object for the given object based on the prediction value. - View Dependent Claims (20)
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Specification