Microsoft Technology Licensing, LLC

Qingyun Wan

Qing Duan

The disclosed embodiments provide a system for processing scoring requests. During operation, the system matches an identifier for an entity in a scoring request to a cache entry in a score cache. Next, the system retrieves, from the cache entry, a previous value of a score generated by a machine learning model from previous values of features for the entity and a first encoded representation of the previous values of a subset of the features with greater than a threshold effect on the score. The system then compares the first encoded representation with a second encoded representation of the most recent values of the subset of the features for the entity. When the comparison indicates that the most recent values match the previous values, the system outputs the previous value of the score for the entity in a response to the scoring request.

Data-driven online score caching for machine learning

Techniques for user-defined quality control of resource usage are provided. In one technique, resource split data is received that indicates a split of a total resource amount that is associated with a content delivery campaign. In response, based on the split, a first resource amount and a second resource amount is determined, each a subset of the total resource amount. The first resource amount is associated with a first utilization strategy and a first mapping function and the second resource amount is associated with a second utilization strategy and a second mapping function. In response to receiving a request from a client device, an entity of the client device is determined and associated with the first mapping function. A quality score of the entity is determined and, based on the first mapping function and the quality score, an adjustment factor is determined. A content item selection event is conducted based on the adjustment factor.

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Sunnyvale, CA, United States of America

Qingyun Wan