公开(公告)号：US10540519B2

公开(公告)日：2020-01-21

申请号：US16169403

申请日：2018-10-24

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Li Zhang ,  Kunal Talwar ,  Aleksandar Nikolov

IPC: H04L9/00 ,  G06F21/62 ,  G06F21/60 ,  G06F16/248 ,  G06F16/2455 ,  G06F17/18

Abstract: The privacy of linear queries on histograms is protected. A database containing private data is queried. Base decomposition is performed to recursively compute an orthonormal basis for the database space. Using correlated (or Gaussian) noise and/or least squares estimation, an answer having differential privacy is generated and provided in response to the query. In some implementations, the differential privacy is ε-differential privacy (pure differential privacy) or is (ε,δ)-differential privacy (i.e., approximate differential privacy). In some implementations, the data in the database may be dense. Such implementations may use correlated noise without using least squares estimation. In other implementations, the data in the database may be sparse. Such implementations may use least squares estimation with or without using correlated noise.

公开(公告)号：US09852133B2

公开(公告)日：2017-12-26

申请号：US14986997

申请日：2016-01-04

Applicant: Microsoft Technology Licensing, LLC

Inventor： Dharma Shukla ,  Madhan Gajendran ,  Quetzalcoatl Bradley ,  Shireesh Kumar Thota ,  Li Zhang ,  Mihai Dan Budiu ,  Yuan Yu

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30011 ,  G06F17/30321 ,  G06F17/30486 ,  G06F17/30554 ,  G06F17/30964

Abstract: Query models for document sets (such as XML documents or records in a relational database) typically involve a schema defining the structure of the documents. However, rigidly defined schemas often raise difficulties with document validation with even inconsequential structural variations. Additionally, queries developed against schema-constrained documents are often sensitive to structural details and variations that are not inconsequential to the query, resulting in inaccurate results and development complications, and that may break upon schema changes. Instead, query models for hierarchically structured documents that enable “twig” queries specifying only the structural details of document nodes that are relevant to the query (e.g., students in a student database having a sibling named “Lee” and a teacher named “Smith,” irrespective of unrelated structural details of the document). Such “twig” query models may enable a more natural query development, and continued accuracy of queries in the event of unrelated schema variations and changes.

公开(公告)号：US10121024B2

公开(公告)日：2018-11-06

申请号：US15587164

申请日：2017-05-04

Applicant: Microsoft Technology Licensing, LLC

Inventor： Li Zhang ,  Kunal Talwar ,  Aleksandar Nikolov

IPC: G06F17/18 ,  G06F21/62 ,  G06F17/30

Abstract: The privacy of linear queries on histograms is protected. A database containing private data is queried. Base decomposition is performed to recursively compute an orthonormal basis for the database space. Using correlated (or Gaussian) noise and/or least squares estimation, an answer having differential privacy is generated and provided in response to the query. In some implementations, the differential privacy is ε-differential privacy (pure differential privacy) or is (ε,δ)-differential privacy (i.e., approximate differential privacy). In some implementations, the data in the database may be dense. Such implementations may use correlated noise without using least squares estimation. In other implementations, the data in the database may be sparse. Such implementations may use least squares estimation with or without using correlated noise.

公开(公告)号：US20190057224A1

公开(公告)日：2019-02-21

申请号：US16169403

申请日：2018-10-24

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Li Zhang ,  Kunal Talwar ,  Aleksandar Nikolov

IPC: G06F21/62 ,  G06F17/30 ,  G06F21/60 ,  G06F17/18

CPC classification number: G06F21/6245 ,  G06F16/2455 ,  G06F16/248 ,  G06F17/18 ,  G06F21/60

Abstract: The privacy of linear queries on histograms is protected. A database containing private data is queried. Base decomposition is performed to recursively compute an orthonormal basis for the database space. Using correlated (or Gaussian) noise and/or least squares estimation, an answer having differential privacy is generated and provided in response to the query. In some implementations, the differential privacy is ε-differential privacy (pure differential privacy) or is (ε,δ)-differential privacy (i.e., approximate differential privacy). In some implementations, the data in the database may be dense. Such implementations may use correlated noise without using least squares estimation. In other implementations, the data in the database may be sparse. Such implementations may use least squares estimation with or without using correlated noise.

公开(公告)号：US20180137660A1

公开(公告)日：2018-05-17

申请号：US15349836

申请日：2016-11-11

Applicant: Microsoft Technology Licensing, LLC

Inventor： Juan Carlos De Abreu Rodriguez ,  Wallace E. Greathouse ,  Li Zhang ,  Soohoon Cho ,  Shannon Kao ,  Vincent Leung ,  Arun Sacheti

IPC: G06T11/60

CPC classification number: G06T11/60 ,  G06F16/532 ,  G06Q50/01 ,  H04M1/72555

Abstract: Data regarding a base digital image and a request to generate one or more customized digital stickers for the base digital image can be received. In response to the received request, a customized digital sticker can be generated for the base digital image using results of analysis of the data regarding the base digital image, with the customized sticker including multiple visual features. The generating can include generating a customized digital sticker using a set of sticker generation rules, with the layout of multiple visual features of the digital sticker being dictated by the sticker generation rules, and with the generating of the sticker including combining the multiple visual features in the digital sticker. The digital sticker can be overlaid on the base digital image to produce a composite digital image.

公开(公告)号：US20160117320A1

公开(公告)日：2016-04-28

申请号：US14986997

申请日：2016-01-04

Applicant: Microsoft Technology Licensing, LLC

Inventor： Dharma Shukla ,  Madhan Gajendran ,  Quetzalcoatl Bradley ,  Shireesh Kumar Thota ,  Li Zhang ,  Mihai Dan Budiu ,  Yuan Yu

IPC: G06F17/30

CPC classification number: G06F17/30011 ,  G06F17/30321 ,  G06F17/30486 ,  G06F17/30554 ,  G06F17/30964

Abstract: Query models for document sets (such as XML documents or records in a relational database) typically involve a schema defining the structure of the documents. However, rigidly defined schemas often raise difficulties with document validation with even inconsequential structural variations. Additionally, queries developed against schema-constrained documents are often sensitive to structural details and variations that are not inconsequential to the query, resulting in inaccurate results and development complications, and that may break upon schema changes. Instead, query models for hierarchically structured documents that enable “twig” queries specifying only the structural details of document nodes that are relevant to the query (e.g., students in a student database having a sibling named “Lee” and a teacher named “Smith,” irrespective of unrelated structural details of the document). Such “twig” query models may enable a more natural query development, and continued accuracy of queries in the event of unrelated schema variations and changes.

Abstract translation: 文档集（如关系数据库中的XML文档或记录）的查询模型通常涉及定义文档结构的模式。 然而，刚性定义的模式通常会导致文档验证的困难，甚至无关紧要的结构变化。 另外，针对模式约束的文档开发的查询通常对结构细节和对查询不重要的变体敏感，导致不准确的结果和开发复杂性，并且可能会破坏模式更改。 相反，用于分层结构化文档的查询模型，使得“twig”查询仅指定与查询相关的文档节点的结构细节（例如，具有名为“Lee”的兄弟姐妹的学生数据库中的学生和名为“Smith”的教师， “不管文件的不相关的结构细节如何）。 这种“twig”查询模型可以实现更自然的查询开发，以及在不相关的模式变化和变化的情况下，查询的持续准确性。