Other

Igor Reshynsky

Kanika Vij

Jingyi Gao

Diane Elizabeth Fenton

Gladys Leung

Esther Choi

Hameet Jassal

Rowan Comish

Min Liang

Emma Hu

Adam Lazure

Systems and methods of monitoring for anomalous data records. The system conducts a method including: receiving a data record associated with at least one meta attribute to determine whether subsequent processing of the data record is warranted; generating an anomaly prediction for the data record based on a detection model and the at least one meta attribute associated with the data record, the detection model defined by a plurality of score distribution representations based on quantile bins and a dynamic quantile weight for providing an interim anomaly measure corresponding to respective score distribution representations, wherein the anomaly prediction is generated based on a combination of interim anomaly measures associated with respective meta attributes associated with the data record; and transmitting a signal representing the anomaly prediction for presentation at a user device for identifying one or more data records for subsequent data processes.

Systems and methods for dynamically managing data sets

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Toronto, Canada

Igor Reshynsky