Facebook, Inc.

Meta Platforms, Inc.

Nicolas Emilio Stier Moses

Ismail Onur Filiz

Balmanohar Paluri

Vishakan Ponnampalam

Brian Christopher Karrer

Timothy Eric Danford

Birce Tezel

Guan Pang

Jing Huang

Karthik Subbian

Killian Murphy

Josue Israel Kuri Obregon

Eric Michael Sodomka

Okke Joost Schrijvers

Christopher Albert Wilkens

Dominic Coey

Paige Alexandra Oliver Maas

In one embodiment, a method may include accessing, from a data store of a social network, historical data of a social-networking metric, and generating a historical-data plot for a pre-determined period of time based on the historical data. The method may include determining one or more events associated with fluctuations in the social-networking metric based on the historical-data plot, and determining a metric-effect of the events on the social-networking metric. Each event may be associated with a sub-period of time within the pre-determined period of time, and the metric-effect for each event may include a rate of change of the social-networking metric over the sub-period of time associated with the event and a magnitude of change of the social-networking metric. Then, the method includes generating a fluctuation model for the social-networking metric, the fluctuation model including the calculated metric-effects for each of the events over the pre-determined period of time.

Analyzing social-networking metrics of online social networks

An online system identifies an opportunity to present content to a viewing user and sends candidate content items eligible for presentation to the viewing user for display to a client device associated with the viewing user. The online system computes an estimated value associated with presenting a candidate content item to the viewing user based at least in part on a bid amount associated with the candidate content item and communicates the value to a content-providing user associated with the candidate content item. Based on information received from the client device describing the placement of one or more candidate content items within a feed of content items presented to the viewing user, the online system calculates a detrimental effect of presenting the candidate content item on user engagement with the online system by the viewing user and computes an adjusted value associated with its presentation based on the detrimental effect.

Computing a value associated with presenting a content item to a user of an online system based on a detrimental effect of a placement of the content item within a feed of content items

In one embodiment, a method includes accessing a point cloud comprising a plurality of point-cloud points, each point-cloud point corresponding to a location on a surface of an object located in a region in a three-dimensional space, identifying, from the point cloud, a plurality of point clusters, each point cluster comprising a plurality of point-cloud points located within a grid segment on a two-dimensional grid derived from the three-dimensional space, selecting, for each point cluster, a set of point-cloud points from the plurality of point-cloud points in the point cluster, the set of point-cloud points being selected based on a predetermined threshold number of point-cloud points associated with an acceptable reduction in an error detection rate, and determining, for each point cluster, a structure classification based on the selected set of point-cloud points from the point cluster.

Multi-hop wireless network plannning

Systems, methods, and non-transitory computer readable media can determine a time at which to prefetch one or more content items to be included in a feed associated with a user. The feed can be provided by a social networking system. A number of content items to prefetch at the determined time can be determined. One or more content items to be included in the feed associated with the user can be prefetched based at least in part on the determined time and the determined number of content items. The determined time can be prior to a time at which the user is expected to access an application associated with the social networking system.

Systems and methods for prefetching content items for a feed in a social networking system

In one embodiment, a method includes accessing a point cloud comprising several points, wherein each point corresponds to a location on a surface of an object located in three-dimensional space; determining whether each point in the point cloud is part of a linear structure, a planar structure, or a volumetric structure; identifying a plurality of point clusters, wherein each point cluster comprises one or more points that are located within a grid segment on a two-dimensional grid derived from the three-dimensional space; determining, for each point cluster, whether the point cluster represents a vertical-linear structure or a portion of a vertical-linear structure; identifying one or more point-cluster pairs, wherein each point-cluster pair includes two point clusters corresponding to one or more vertical-linear structures within a threshold distance in the three-dimensional space; and determining, for each point-cluster pair, whether a line-of-sight exists between each point-cluster in the point-cluster pair.

Multi-hop wireless network planning

A system and method for fault-tolerant and long-term network capacity planning is disclosed. The system receives projected data, such as available network supply and network demand, characterizing a backbone network for a set of time periods. The system also receives failure data describing different failure scenarios that may occur. Based on the received network characterization data the system generates a capacity provisioning plan, describing how capacity is added to the backbone network over time, that satisfies the network demand of each time period while providing fault-tolerance under any of the failure scenarios described in the failure data. The capacity provisioning plan is also optimized, based on cost data associated with the backbone network, to minimize total costs.

Capacity planning in a backbone network

Growing community of inventors

Palo Alto, CA, United States of America

Nicolas Emilio Stier Moses