Abstract: Methods and systems are disclosed. At a respective computing system, a request to run a program on first data stored within the respective computing system may be received. In some examples, the first data may be stored in association with a data access policy that defines access restrictions for the first data. In response to receiving the request, whether the request to run the program on the first data satisfies the access restrictions defined by the data access policy may be determined. In response to determining whether the request to run the program satisfies the access restrictions, in accordance with a determination that the access restrictions are satisfied, the program may be run, including performing one or more operations on the first data in an environment within the respective computing system, where a contents of the environment cannot be accessed from outside of the environment.

Abstract: A system and method for utilizing weak supervision and a generative adversarial network to identify a location that includes receiving location data and time based data associated with locations of a vehicle and analyzing the location data and the time based data to filter noisy data associated with the locations of the vehicle. The system and method also include determining a plurality of labeling functions that are associated with at least one center point that is associated with a point of interest location that is regularly visited by the vehicle and the time based data. The system and method further include inputting the plurality of labeling functions to the generative adversarial network to train at least one model of the generative adversarial network to identify the point of interest location that is regularly visited by the vehicle.

Abstract: A system and method for home identification is provided. The system selects a set of locations corresponding to a set of calendar dates from user's location history. Each location is associated with a dwell time period which is greater than a first threshold time-period. The system creates a location table by including the set of locations against the set of calendar dates and selects a first location from the location table based on whether a total number of day-wise occurrences of the first location in the location table is above a threshold number in a week period. The system determines a first count of weeks for which the total number of day-wise occurrences of the first location is above the threshold number and determines the first location as a user's home location based on whether the determined first count of weeks is above a threshold number of weeks.

Abstract: Methods and systems are disclosed. At a respective computing system, a request to run a program on first data stored within the respective computing system may be received. In some examples, the first data may be stored in association with a data access policy that defines access restrictions for the first data. In response to receiving the request, whether the request to run the program on the first data satisfies the access restrictions defined by the data access policy may be determined. In response to determining whether the request to run the program satisfies the access restrictions, in accordance with a determination that the access restrictions are satisfied, the program may be run, including performing one or more operations on the first data in an environment within the respective computing system, where a contents of the environment cannot be accessed from outside of the environment.

Abstract: A system and method for utilizing weak supervision and a generative adversarial network to identify a location that includes receiving location data and time based data associated with locations of a vehicle and analyzing the location data and the time based data to filter noisy data associated with the locations of the vehicle. The system and method also include determining a plurality of labeling functions that are associated with at least one center point that is associated with a point of interest location that is regularly visited by the vehicle and the time based data. The system and method further include inputting the plurality of labeling functions to the generative adversarial network to train at least one model of the generative adversarial network to identify the point of interest location that is regularly visited by the vehicle.

Abstract: A system and method for home identification is provided. The system selects a set of locations corresponding to a set of calendar dates from user's location history. Each location is associated with a dwell time period which is greater than a first threshold time-period. The system creates a location table by including the set of locations against the set of calendar dates and selects a first location from the location table based on whether a total number of day-wise occurrences of the first location in the location table is above a threshold number in a week period. The system determines a first count of weeks for which the total number of day-wise occurrences of the first location is above the threshold number and determines the first location as a user's home location based on whether the determined first count of weeks is above a threshold number of weeks.