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Patent Agency Ranking
公开(公告)号：US12199956B2
公开(公告)日：2025-01-14
申请号：US18403339
申请日：2024-01-03
Applicant: Google LLC
Inventor： Badih Ghazi , Noah Zeger Golowich , Shanmugasundaram Ravikumar , Pasin Manurangsi , Ameya Avinash Velingker , Rasmus Pagh
Abstract: An encoding method for enabling privacy-preserving aggregation of private data can include obtaining private data including a private value, determining a probabilistic status defining one of a first condition and a second condition, producing a multiset including a plurality of multiset values, and providing the multiset for aggregation with a plurality of additional multisets respectively generated for a plurality of additional private values. In response to the probabilistic status having the first condition, the plurality of multiset values is based at least in part on the private value, and in response to the probabilistic status having the second condition, the plurality of multiset values is a noise message. The noise message is produced based at least in part on a noise distribution that comprises a discretization of a continuous unimodal distribution supported on a range from zero to a number of multiset values included in the plurality of multiset values.
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公开(公告)号：US11902259B2
公开(公告)日：2024-02-13
申请号：US17122638
申请日：2020-12-15
Applicant: Google LLC
Inventor： Badih Ghazi , Noah Zeger Golowich , Shanmugasundaram Ravikumar , Pasin Manurangsi , Ameya Avinash Velingker , Rasmus Pagh
CPC classification number: H04L63/0428 , G06N5/04 , G06N20/00
Abstract: An encoding method for enabling privacy-preserving aggregation of private data can include obtaining private data including a private value, determining a probabilistic status defining one of a first condition and a second condition, producing a multiset including a plurality of multiset values, and providing the multiset for aggregation with a plurality of additional multisets respectively generated for a plurality of additional private values. In response to the probabilistic status having the first condition, the plurality of multiset values is based at least in part on the private value, and in response to the probabilistic status having the second condition, the plurality of multiset values is a noise message. The noise message is produced based at least in part on a noise distribution that comprises a discretization of a continuous unimodal distribution supported on a range from zero to a number of multiset values included in the plurality of multiset values.
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公开(公告)号：US20240236052A1
公开(公告)日：2024-07-11
申请号：US18403339
申请日：2024-01-03
Applicant: Google LLC
Inventor： Badih Ghazi , Noah Zeger Golowich , Shanmugasundaram Ravikumar , Pasin Manurangsi , Ameya Avinash Velingker , Rasmus Pagh
CPC classification number: H04L63/0428 , G06N5/04 , G06N20/00
Abstract: An encoding method for enabling privacy-preserving aggregation of private data can include obtaining private data including a private value, determining a probabilistic status defining one of a first condition and a second condition, producing a multiset including a plurality of multiset values, and providing the multiset for aggregation with a plurality of additional multisets respectively generated for a plurality of additional private values. In response to the probabilistic status having the first condition, the plurality of multiset values is based at least in part on the private value, and in response to the probabilistic status having the second condition, the plurality of multiset values is a noise message. The noise message is produced based at least in part on a noise distribution that comprises a discretization of a continuous unimodal distribution supported on a range from zero to a number of multiset values included in the plurality of multiset values.
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公开(公告)号：US20230281430A1
公开(公告)日：2023-09-07
申请号：US18118061
申请日：2023-03-06
Applicant: Google LLC
Inventor： Ali Kemal Sinop , Sreenivas Gollapudi , Petar Velickovic , Sofia Ira Ktena , Ameya Avinash Velingker
Abstract: Methods and systems for conditioning graph neural networks on affinity features. One of the methods includes obtaining graph data representing an input graph that comprises a set of nodes and a set of edges that each connect a respective pair of nodes, the graph data comprising respective node features for each of the nodes, edge features for each of the edges, and a respective weight for each of the edges; generating one or more affinity features, each affinity feature representing a property of one or more random walks through the graph guided by the respective weights for the edges; and processing the graph data using a graph neural network that is conditioned on the one or more affinity features to generate a task prediction for a machine learning task for the input graph.
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公开(公告)号：US20210243171A1
公开(公告)日：2021-08-05
申请号：US17122638
申请日：2020-12-15
Applicant: Google LLC
Inventor： Badih Ghazi , Noah Zeger Golowich , Shanmugasundaram Ravikumar , Pasin Manurangsi , Ameya Avinash Velingker , Rasmus Pagh
Abstract: An encoding method for enabling privacy-preserving aggregation of private data can include obtaining private data including a private value, determining a probabilistic status defining one of a first condition and a second condition, producing a multiset including a plurality of multiset values, and providing the multiset for aggregation with a plurality of additional multisets respectively generated for a plurality of additional private values. In response to the probabilistic status having the first condition, the plurality of multiset values is based at least in part on the private value, and in response to the probabilistic status having the second condition, the plurality of multiset values is a noise message. The noise message is produced based at least in part on a noise distribution that comprises a discretization of a continuous unimodal distribution supported on a range from zero to a number of multiset values included in the plurality of multiset values.
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