Pillsbury Winthrop Shaw Pittman, LLP
Methods and systems for predicting successful data transmission during mass communications across computer networks featuring disparate entities and imbalanced data sets using machine learning models
Methods and systems for predicting successful data transmission during mass communications across computer networks featuring disparate entities and imbalanced data sets using machine learning models. For example, the methods and systems provide a prediction as to whether or not a communication will be successful prior to the transmission being sent. Moreover, in some embodiments, the methods and systems described herein provide probability of a successful transmission as a function of time. For example, the methods and system provide a probability of how likely a communication will succeed (or fail) if it is sent at various times. Additionally, in some embodiments, the methods and systems may alert a sender prior to the transmission of a communication that the transmission is likely to succeed or fail.
THE BANK OF NEW YORK MELLON
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Ganesh Weipeng
Rao Li