Snap Inc.

Google Inc.

Wisam Dakka

Andre Madeira

Jaewook Chung

Newar Husam Al Majid

Donald Giovannini

Emre Yamangil

Andrei Damian

Ranveer Kunal

Yanping Chen

Yaming Lin

Seyed Reza Mir Ghaderi

Jiwoon Jeon

Jungho Ahn

Congxing Cai

Robson Araujo

Guilherme Fernandes

Xin Chen

Aymeric Damien

Theresa Barton

Lucas Ou-Yang

Keyang Zhang

Michael Brian Murray

Yantao Zheng

Matthew Lee Cook

Yan Wu

Maryam Daneshi

Chunhui Zhu

Yi Liu

Diwakar Punjani

Wesley Evans

Trystan G Upstill

Andre Duque Madeira

Christopher Yale Crutchfield

Zhong Xiu

Various embodiments provide for systems, methods, and computer-readable storage media that improve media content search functionality and curation of media content. For instance, various embodiments described in this document provide features that can present media content items in the form of dynamic collection of media content items upon a user typing into a search bar. In another instance, various embodiments described herein improve media content search functionality by ranking user facing search features using input signals.

Searching social media content

Disclosed are methods and systems for ranking content. In one aspect, a method of ranking content for display includes identifying, via hardware processing circuitry, interactions by a single account with content pairs, each of the content in the content pairs included in a plurality of content, aggregating, via the hardware processing circuitry, the identified interactions across a plurality of accounts, associating, via the hardware processing circuitry, probabilities with each content in the plurality of content based on the aggregated interactions, ranking, via the hardware processing circuitry, the plurality of content based on the associated probabilities; and selecting, via the hardware processing circuitry, content ranked above a threshold for display.

Ranking content for display

Manipulating images using computationally expensive machine learning schemes can be implemented using server-generated models of the machine learning schemes that are transmitted to a client device for application. The schemes can include convolutional neural networks having a kernel comprising a plurality of low-rank matrices.

Fast image style transfers

Various embodiments provide for systems, methods, and computer-readable storage media for annotating a collection of media items, such as digital images. According to some embodiments, an annotation system automatically determines one or more annotations for a plurality of media content items, and generates a collection of media content items that associates the determined annotations with the plurality of media content items. Depending on the embodiment, annotations that may be determined for the plurality of media content (and associated with the collection for the media content items) can include, without limitation, a caption, a geographic location, a category, a novelty measurement, an event, and a highlight media content item representing the collection.

Annotating a collection of media content items

Disclosed are implementations for ranking a feed in a social network. In one aspect, a method of generating a feed includes identifying a group of users associated with a first user, identify notifications for the first user based on the group of users, determine one or more actions that may result from each of the identified notifications, rank the notifications based on the one or more determined actions; and display the notifications to the first user according to the ranking.

Ranking notifications in a social network feed

Various embodiments provide for associating a collection of media items with a graphical element. For instance, a system can: generate corpus data from a set of features of a collection of media content items; determine a set of candidate graphical elements for the collection of media content items based on the corpus data and further based on a set of first mappings associating at least one graphical element and at least one n-gram; determine a set of prediction scores corresponding to the set of candidate graphical elements based on the set of features; determine a ranking for the set of candidate graphical elements based on the set of prediction stores; select a set of predicted graphical elements, from the set of candidate graphical elements, based on the ranking; and provide the set of predicted graphical elements in association with the collection of media content items.

Associating a graphical element to media content item collections

Systems, devices, media, and methods are presented for scaled delivery of media content. The systems and methods assign a set of proposed designations to a plurality of media content. The systems and methods select a set of media content from the plurality of media content based on the set of proposed designations and distribute a subset of media content of the set of media content to a selected user of a plurality of users. The subset of media content is presented at a computing device associated with the selected user. The systems and methods receive a set of indicators for each media content of the subset of media content. Each indicator represents an interaction with a media content of the subset of media content. The systems and methods cause presentation of an interaction notification at the computing device associated with the selected user.

Scaled delivery of media content

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San Francisco, CA, United States of America

Wisam Dakka