Abstract: Systems and methods for diagnostic visual search can include processing a search query with a plurality of classification models to determine a search query intent and predict potential diagnosis. The search query can include an image that is processed to determine the presence of a body part and may be processed to determine if the search query is descriptive of a diagnostic search query. Based on the intent determination, the image may then be processed by a conditions classification model to determine one or more predicted condition classifications. Condition information can then be obtained and provided based on the one or more predicted condition classifications.

Abstract: Provided is a Face-aware Offset Calculation (FOC) module and method for facial frame interpolation and enhancement and a face video deblurring system and method using the same. The system comprises: a facial frame enhancement device, including a FOC module, for enhancing a target frame; a facial frame interpolation device, including the FOC module, for interpolating the target frame; and a combination device for combining the enhanced target frame with the interpolated target frame.

Abstract: Embodiments include one or more client devices accessible by users, an online system, and one or more partner systems such that the online system is able to identify a user of the online system across different devices and browsers based on the user activity that occurs external to the online system. A user performs user actions (e.g. purchase a product) on a web page of a partner system and may provide personally identifiable information (PII) to the partner system. The partner system provides the hashed PII and user actions performed by the user to the online system. The online system identifies a user profile on the online system by matching personal information in the user profile to the hashed PII. The online system generates a confidence score indicating a likelihood that the identified user of the online system is the individual that performed the external user action.

Abstract: An online system selects advertisements for a user based on characteristics of the user. The online system presents advertisements to the user having targeting criteria satisfied by the characteristics of the user. To increase the number of users eligible to be presented with an advertisement, the online system increases the users eligible to be presented with the advertisement to include users that do not meet targeting criteria included in the advertisement. The online system obtains a percentile of users based on a performance metric associated with the advertisement and determines a cutoff measure of affinity based on the percentile and measures of affinity between various users and the advertisement. A user is eligible to be presented with the advertisement if a measure of affinity between the user and the advertisement is greater than the cutoff measure of affinity for the advertisement.

Abstract: An online system selects advertisements for presentation a user based on characteristics of the user. The online system monitors performance of advertisements based on a goal for the advertisement and a time interval for achieving the goal. During a time period within the time interval, the online system determines an actual performance of the advertisement and compares the actual performance to a portion of the goal associated with the time period. If the actual performance does not satisfy the portion of the goal associated with the time period, the online system expands targeting criteria of the advertisement to increase a number of users eligible to be presented with the advertisement.

Abstract: Embodiments include one or more client devices accessible by users, an online system, and one or more partner systems such that the online system is able to identify a user of the online system across different devices and browsers based on the user activity that occurs external to the online system. A user performs user actions (e.g. purchase a product) on a web page of a partner system and may provide personally identifiable information (PII) to the partner system. The partner system provides the hashed PII and user actions performed by the user to the online system. The online system identifies a user profile on the online system by matching personal information in the user profile to the hashed PII. The online system generates a confidence score indicating a likelihood that the identified user of the online system is the individual that performed the external user action.

Abstract: Embodiments include one or more client devices accessible by users, an online system, and one or more partner systems such that the online system is able to identify a user of the online system across different devices and browsers based on the user activity that occurs external to the online system. A user performs user actions (e.g. purchase a product) on a web page of a partner system and may provide personally identifiable information (PII) to the partner system. The partner system provides the hashed PII and user actions performed by the user to the online system. The online system identifies a user profile on the online system by matching personal information in the user profile to the hashed PII. The online system generates a confidence score indicating a likelihood that the identified user of the online system is the individual that performed the external user action.

Abstract: An online system selects advertisements for presentation a user based on characteristics of the user. The online system monitors performance of advertisements based on a goal for the advertisement and a time interval for achieving the goal. During a time period within the time interval, the online system determines an actual performance of the advertisement and compares the actual performance to a portion of the goal associated with the time period. If the actual performance does not satisfy the portion of the goal associated with the time period, the online system expands targeting criteria of the advertisement to increase a number of users eligible to be presented with the advertisement.

Abstract: An online system selects advertisements for a user based on characteristics of the user. The online system presents advertisements to the user having targeting criteria satisfied by the characteristics of the user. To increase the number of users eligible to be presented with an advertisement, the online system increases the users eligible to be presented with the advertisement to include users that do not meet targeting criteria included in the advertisement. The online system obtains a percentile of users based on a performance metric associated with the advertisement and determines a cutoff measure of affinity based on the percentile and measures of affinity between various users and the advertisement. A user is eligible to be presented with the advertisement if a measure of affinity between the user and the advertisement is greater than the cutoff measure of affinity for the advertisement.