Microsoft Technology Licensing, LLC

Witagg, Inc.

Jing Wang

Ryan M Rogers

Hongjun Zhu

Man Chun D Leung

Ryan T Tecco

Parvez Ahammad

Ankit Gupta

Yang Chen

Souvik Ghosh

David Pardoe

John P Moore

Manoj Rameshchandra Thakur

Chencheng Wu

Haifeng Zhao

Xiaojing Chen

Jiashuo Wang

Haowen Cao

Rahul Tandra

Keyi Yu

Mira Thambireddy

Shawn F Ren

Bing Liu

Yajun Wang

Saket Kumar

Sudhanshu Arora

Devang N Jhaveri

Liangzhong Yin

Henry Heyburn Pistell

A device for estimating a fixed position of a wireless communication is provided. The device comprises a radio connected to an antenna array, a memory and a process. The radio can receive a first signal transmitted from a first direction by the wireless communication device to the movable device, and a second signal transmitted from a second direction by the wireless communication device to the movable device. The processor can calculate a first angle of arrival (AOA) a second AOA. The processor can estimate the fixed position of the wireless communication device based on the first AOA, the second AOA, the first position and the second position.

Devices, systems and methods for detecting locations of wireless communication devices

Technologies for secure multi-party computation include computing first double-encrypted data, computing second double-encrypted data, and, in a trusted execution environment, executing a query on the first double-encrypted data and the second double encrypted data to create a query-processed double-encrypted data set. The trusted execution environment can provide the query-processed double-encrypted data set to a requester such as another computer, system, or process.

Secure multi-party computation

Embodiments of the disclosed technologies receive first event data associated with a first party application, receive second event data representing a click, in the first party application, on a link to a third party application, receive third event data from the third party application, convert the third event data to a label, map a compressed format of the labeled third event data to the first event data and the second event data to create multi-party attribution data, group multiple instances of the multi-party attribution data into a batch, add noise to the compressed format of the labeled third event data in the batch, and send the noisy batch to a second computing device. A debiasing algorithm can be applied to the noisy batch. The debiased noisy batch can be used to train at least one machine learning model.

On-device privatization of multi-party attribution data

Techniques for a flexible data security and machine learning system for merging third-party data are provided. In one technique, the system receives a data set from a third-party entity and receives selection data that indicates that the third-party entity selected a set of data security policies that includes an encryption option and a data mixing option from among multiple data mixing options. In response to receiving the selection data, the system stores data that associates the set of data security policies with the data set, encrypts the data set according to the encryption option, and persistently stores the encrypted data set. Later, the system decrypts the encrypted data set in volatile memory, generates, based on the data mixing option, training data based on the decrypted version of the data set, trains a machine-learned model based on the training data, and stores the machine-learned model in association with the data set.

Flexible data security and machine learning system for merging third-party data

Approaches are described for antenna configuration in an antenna array of limited array size and channel state information (CSI) collection and analysis, to improve accuracy of angle of arrival (AoA) estimations for localizing a client device's position. Signals can be received from groups of antennas and CSI data can be generated from the signals. The CSI data can be combined, where the combined CSI data represents CSI data measurements of multiple signals received from a plurality of antenna subsets, without requiring physical installation of additional antennas to the limited antenna array to make the CSI data measurements. The angle of arrival (AoA) of the signals is estimated based on the combined CSI, and the AoA estimation can be used to determine the client device's location, and for other location services, such as identifying a person's location, tracking and managing inventory of objects, commute prediction, and the like.

System and method for estimating the angle of arrival using antenna arrays

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Los Altos, CA, United States of America

Jing Wang