Patel, Nikesh

In some embodiments, a method includes extracting one or more request features from request data for a transaction, generating one or more derived features based on the request features, encoding the one or more request features and the one or more derived features into a format for a security decision model, and generating, using the security decision model, a security protocol decision based on model features including the one or more request features and the one or more derived features.

Systems and methods are disclosed for integrated data optimization for processing an electronic message. The method includes receiving a request from a first system for an electronic transaction; analyzing the request for the electronic transaction using one or more outcomes generated by a machine learning system that is trained based on a set of randomized training data processed using a plurality platforms, determining a plurality of possible combinations of paths for processing the electronic transaction based on the analysis of the request; determining a plurality of possible combination of tasks for processing the electronic transaction based on the analysis of the request; determining an optimized path among the plurality of possible combinations of paths; determining an optimal combination of tasks among the possible combination of tasks; and transmitting the electronic transaction via the optimized path using the optimal combination of tasks.

A system and method of predicting a team's formation on a playing surface are disclosed herein. A computing system retrieves one or more sets of event data for a plurality of events. Each set of event data corresponds to a segment of the event. A deep neural network, such as a mixture density network, learns to predict an optimal permutation of players in each segment of the event based on the one or more sets of event data. The deep neural network learns a distribution of players for each segment based on the corresponding event data and optimal permutation of players. The computing system generates a fully trained prediction model based on the learning. The computing system receives target event data corresponding to a target event. The computing system generates, via the trained prediction model, an expected position of each player based on the target event data.

A smart forms solution that enables transactions institutions to provide configuration parameters in a streamlined manner so that developers can construct end-to-end solutions in an automated manner includes performing, by a processor, operations including: receiving data from a form in a webpage; validating the received data; saving the validated data; determining a location to send the saved data; sending the saved data to the determined location; invoking an API at the determined location with the saved data; and using the saved data to perform a manual operation.

A method of generating predictions for teams and players for each team associated with a sporting event, the method including: receiving one or more top-down predictions for the sporting event; providing the top-down predictions as one or more top-down feature vectors to a computing system; receiving, by the computing system, a second set of feature vectors comprising data for one or more players associated with one or more respective teams and data for one or more teams associated with a sporting event; inputting the one or more top-down feature vectors and second set of feature vectors into a transformer-based neural network; and generating, using the transformer-based neural network, one or more predictions for the sporting event based on the one or more top-down feature vectors and the second set of feature vectors.

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …

Zusammenfassung wird geladen …