A device, comprising: a display; a memory; and at least one processor configured to: receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including one or more applications local to the device that are stored in the memory and/or one or more applications external to the device; determine, using a machine learning, ML, model, a relevance score for each of one or more user interface, UI, elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features, wherein each respective one of the variance values indicates a confidence of a relevance of a corresponding one of the features to a user associated with the user activity; sort one or more UI elements based on a ranking of the relevance scores; and provide, as output for display on the display, the one or more UI elements based at least in part on the ranking, wherein at least one of the features is included in at least one of a generalizing group of features or a memorizing group of features, wherein the generalizing group of features corresponds to features that are not specific to a particular application and includes at least one of: a current location, a current time, or a time period of the day, and wherein the memorizing group of features corresponds to features that are specific to a particular application and includes at least one of: a dwell time, a tap through for the particular application, a scroll past the particular application performed by the user, or a likelihood that the user will launch the particular application. a display; a memory; and at least one processor configured to: receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including one or more applications local to the device that are stored in the memory and/or one or more applications external to the device; determine, using a machine learning, ML, model, a relevance score for each of one or more user interface, UI, elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features, wherein each respective one of the variance values indicates a confidence of a relevance of a corresponding one of the features to a user associated with the user activity; sort one or more UI elements based on a ranking of the relevance scores; and provide, as output for display on the display, the one or more UI elements based at least in part on the ranking, wherein at least one of the features is included in at least one of a generalizing group of features or a memorizing group of features, wherein the generalizing group of features corresponds to features that are not specific to a particular application and includes at least one of: a current location, a current time, or a time period of the day, and wherein the memorizing group of features corresponds to features that are specific to a particular application and includes at least one of: a dwell time, a tap through for the particular application, a scroll past the particular application performed by the user, or a likelihood that the user will launch the particular application. receive application data from one or more applications, the application data including features related to user activity from the one or more applications, the one or more applications including one or more applications local to the device that are stored in the memory and/or one or more applications external to the device; determine, using a machine learning, ML, model, a relevance score for each of one or more user interface, UI, elements based on each of the features, wherein the relevance score is based at least in part on weights assigned to features based on the user activity and respective variance values of the features, wherein each respective one of the variance values indicates a confidence of a relevance of a corresponding one of the features to a user associated with the user activity; sort one or more UI elements based on a ranking of the relevance scores; and provide, as output for display on the display, the one or more UI elements based at least in part on the ranking, wherein at least one of the features is included in at least one of a generalizing group of features or a memorizing group of features, wherein the generalizing group of features corresponds to features that are not specific to a particular application and includes at least one of: a current location, a current time, or a time period of the day, and wherein the memorizing group of features corresponds to features that are specific to a particular application and includes at least one of: a dwell time, a tap through for the particular application, a scroll past the particular application performed by the user, or a likelihood that the user will launch the particular application.