Abstract: A simulation test is run on a first machine learning model trained using first training data historically collected over a time period. The first training data includes a set of training inputs and a set of target outputs. In response to a determination that a result of the simulation test run on the first machine learning model satisfies one or more criteria, a size of the set of target outputs of the first training data is determined. Second training data for training a second machine learning model is obtained. A size of a set of target outputs of the second training data meets or exceeds the size of the target outputs of the first training data. The second machine learning model is trained using the second training data.

Abstract: Methods, systems, and media for timing presentation of content are provided.

Abstract: A simulation test is run on a first machine learning model trained using first training data historically collected over a time period. The first training data includes a set of training inputs and a set of target outputs. In response to a determination that a result of the simulation test run on the first machine learning model satisfies one or more criteria, a size of the set of target outputs of the first training data is determined. Second training data for training a second machine learning model is obtained. A size of a set of target outputs of the second training data meets or exceeds the size of the target outputs of the first training data. The second machine learning model is trained using the second training data.

Abstract: Methods, systems, and media for timing presentation of content are provided.

Abstract: A system and method are disclosed for running a plurality of simulation tests on a first machine learning model to obtain a plurality of results that are each produced during a respective simulation test, the first machine learning model gradually trained using first training data historically collected over a period of time, the first training data comprising a plurality of first training data sets each including a subset of first training inputs and first target outputs associated with one of a plurality of points in time during the period of time, determining a simulation test of the plurality of simulation tests at which corresponding results of the first machine learning model satisfy a threshold condition, wherein the threshold condition is based on historical data at a first point in time of the plurality of points in time, identifying a first training data set of the plurality of first training data sets on which the first machine learning model used during the determined simulation test was trained,

Abstract: Methods, systems, and media for timing presentation of content are provided.

Abstract: A system and method are disclosed for running a plurality of simulation tests on a first machine learning model to obtain a plurality of results that are each produced during a respective simulation test, the first machine learning model gradually trained using first training data historically collected over a period of time, the first training data comprising a plurality of first training data sets each including a subset of first training inputs and first target outputs associated with one of a plurality of points in time during the period of time, determining a simulation test of the plurality of simulation tests at which corresponding results of the first machine learning model satisfy a threshold condition, wherein the threshold condition is based on historical data at a first point in time of the plurality of points in time, identifying a first training data set of the plurality of first training data sets on which the first machine learning model used during the determined simulation test was trained,

Abstract: The present disclosure provides systems and methods for determining semantic location information. In particular, one or more computing devices can receive, from an application program executing on at least one of the one or more computing devices, an application programming interface (API) call requesting semantic information about a location of at least one of the one or more computing devices. Responsive to receiving the API call, the one or more computing devices can determine semantic information for the location and can return the semantic information for the location to the application program via the API. The semantic information for the location can comprise data semantically identifying the location and indicating whether a user associated with the one or more computing devices is stationary at the location or in transit from the location.

Abstract: The present disclosure provides systems and methods for determining semantic location information. In particular, one or more computing devices can receive, from an application program executing on at least one of the one or more computing devices, an application programming interface (API) call requesting semantic information about a location of at least one of the one or more computing devices. Responsive to receiving the API call, the one or more computing devices can determine semantic information for the location and can return the semantic information for the location to the application program via the API. The semantic information for the location can comprise data semantically identifying the location and indicating whether a user associated with the one or more computing devices is stationary at the location or in transit from the location.

Abstract: The present disclosure provides systems and methods for determining semantic location information. In particular, one or more computing devices can receive, from an application program executing on at least one of the one or more computing devices, an application programming interface (API) call requesting semantic information about a location of at least one of the one or more computing devices. Responsive to receiving the API call, the one or more computing devices can determine semantic information for the location and can return the semantic information for the location to the application program via the API. The semantic information for the location can comprise data semantically identifying the location and indicating whether a user associated with the one or more computing devices is stationary at the location or in transit from the location.

Abstract: The present disclosure provides systems and methods for determining semantic location information. In particular, one or more computing devices can receive, from an application program executing on at least one of the one or more computing devices, an application programming interface (API) call requesting semantic information about a location of at least one of the one or more computing devices. Responsive to receiving the API call, the one or more computing devices can determine semantic information for the location and can return the semantic information for the location to the application program via the API. The semantic information for the location can comprise data semantically identifying the location and indicating whether a user associated with the one or more computing devices is stationary at the location or in transit from the location.