Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.

Abstract: Automatically determining, with reduced (or no) input from the users of a group, a set of activity instances that the group of users has interest in performing. A representation of the set of activity instances can be rendered for consideration by a group, and the set of activity instances can be determined even when only limited criteria are specified. Optionally, in response to affirmative user interface input(s) directed to a rendered representation of the set of activity instances, one or more of the activity instances of the set can be confirmed through limited input(s) of one or more users of the group. Further, the automatic determination of the set of activity instances is optionally performed using one or more trained machine learning models that are trained to optimize a likelihood that the users of the group will find the set satisfactory.