公开(公告)号：US20230186080A1

公开(公告)日：2023-06-15

申请号：US17936975

申请日：2022-09-30

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Hong Lu ,  Jose Lopez ,  Lama Nachman

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Data analysis and neural network training technology includes generates, based on a sparse neural network, a feature selection ranking representing a ranked list of features from input data, where the sparse neural network is a shallow neural network trained with the input data and then pruned, generates, based on the sparse neural network, a feature set dictionary representing interactions among features from the input data, and performs, based on the feature selection ranking and the feature set dictionary, one or more of generating an output analysis of insights from the input data and the sparse neural network, or training of a second neural network. The technology can also adjust the input data based on the feature set ranking to produce adjusted input data, where the sparse neural network is re-trained based on the adjusted input data and then pruned prior to generating the feature set dictionary.

公开(公告)号：US20240028876A1

公开(公告)日：2024-01-25

申请号：US18477407

申请日：2023-09-28

Applicant: Intel Corporation

Inventor： Anthony Rhodes ,  Hong Lu ,  Lama Nachman

IPC: G06N3/047 ,  G06N3/084

CPC classification number: G06N3/047 ,  G06N3/084

Abstract: Example apparatus disclosed include interface circuitry, machine readable instruction, and programmable circuitry to at least one of instantiate or execute the machine readable instructions to access source input data and target input data, identify a domain shift prediction based on at least one of a feature decorrelation of the source input data or a feature decorrelation of the target input data, the domain shift prediction a source domain prediction or a target domain prediction, initiate gradient propagation of a domain loss to determine data features for the domain shift prediction, and rank input data features for the domain shift prediction.

公开(公告)号：US11793458B2

公开(公告)日：2023-10-24

申请号：US15084670

申请日：2016-03-30

Applicant: Intel Corporation

Inventor： Lama Nachman ,  Hong Lu ,  Jennifer Healey ,  Rahul C. Shah ,  Jonathan J Huang ,  Rita H Wouhaybi ,  Giuseppe Raffa

IPC: A63B22/02 ,  H04W4/029 ,  A61B5/00 ,  H04L67/306 ,  A61B5/11 ,  A61B5/22 ,  A61B5/117 ,  A63B71/06

CPC classification number: A61B5/4866 ,  A61B5/117 ,  A61B5/1118 ,  A61B5/222 ,  A63B22/02 ,  H04L67/306 ,  A63B71/0622 ,  A63B2071/0625 ,  A63B2071/0658 ,  A63B2220/12 ,  A63B2220/20 ,  A63B2220/40 ,  A63B2220/805 ,  A63B2220/806 ,  A63B2225/50 ,  A63B2230/75 ,  H04W4/029

Abstract: System and techniques for tracking caloric expenditure using sensor driven fingerprints are described herein. A set of outputs may be obtained from a plurality of sensors. A fingerprint may be generated using the set of outputs. The fingerprint may correspond to an activity observed by the plurality of sensors. The generated fingerprint may be compared to a set of fingerprints stored in a database. Each fingerprint of the set of fingerprints may correspond to a respective caloric expenditure. A caloric expenditure may be calculated for the activity based on the comparison. An exercise profile of a user may be updated using the caloric expenditure.

公开(公告)号：US10219129B2

公开(公告)日：2019-02-26

申请号：US15722872

申请日：2017-10-02

Applicant: INTEL CORPORATION

Inventor： Chieh-Yih Wan ,  Lei Yang ,  Jonathan J. Huang ,  Hong Lu ,  Rahul C. Shah ,  Lama Nachman

IPC: H04W4/02 ,  H04W4/30 ,  H04L29/08 ,  H04W4/04 ,  H04W4/70 ,  H04W4/80

Abstract: A portable electronic device may generate a (RF) radio frequency fingerprint that includes information representative of at least a portion of RF signals received at a given physical location. The RF fingerprint may include, for example, a unique identifier and a signal strength that are both logically associated with at least a portion of the received RF signals. The portable electronic device may also receive data representative of a number of environmental parameters about the portable electronic device. These environmental parameters may be measured using sensors carried by the portable electronic device. Considered in combination, these environmental parameters provide an environmental signature for a given location. When combined into a data cluster, the RF fingerprint and the environmental signature may provide an indication of the physical subdivision where the portable electronic device is located. The portable electronic device may then generate a proposed semantic label for the physical subdivision.

公开(公告)号：US09781575B1

公开(公告)日：2017-10-03

申请号：US15084799

申请日：2016-03-30

Applicant: Intel Corporation

Inventor： Chieh-Yih Wan ,  Lei Yang ,  Jonathan J. Huang ,  Hong Lu ,  Rahul C. Shah ,  Lama Nachman

IPC: H04W4/04 ,  H04W4/00 ,  H04L29/08 ,  H04W4/02

CPC classification number: H04W4/30 ,  H04L67/303 ,  H04W4/023 ,  H04W4/04 ,  H04W4/70 ,  H04W4/80

Abstract: A portable electronic device may generate a (RF) radio frequency fingerprint that includes information representative of at least a portion of RF signals received at a given physical location. The RF fingerprint may include, for example, a unique identifier and a signal strength that are both logically associated with at least a portion of the received RF signals. The portable electronic device may also receive data representative of a number of environmental parameters about the portable electronic device. These environmental parameters may be measured using sensors carried by the portable electronic device. Considered in combination, these environmental parameters provide an environmental signature for a given location. When combined into a data cluster, the RF fingerprint and the environmental signature may provide an indication of the physical subdivision where the portable electronic device is located. The portable electronic device may then generate a proposed semantic label for the physical subdivision.

公开(公告)号：US20190090756A1

公开(公告)日：2019-03-28

申请号：US15717132

申请日：2017-09-27

Applicant: Intel Corporation

Inventor： Hong Lu ,  Lama Nachman

IPC: A61B5/0205 ,  A61B5/00

Abstract: Technologies for determining a heart rate of a user includes a wearable compute device having a heart rate sensor, a motion sensor, a heart rate determination manager, and a heart rate estimator. The wearable compute device generates sensor data indicative of a heart rate of the user and motion data indicative of a motion presently performed by the user. The wearable compute device determines whether to estimate the heart rate of the user based on the heart rate sensor data. The wearable compute device generates an estimated heart rate of the user using a heart rate estimation model and the motion data as an input to the heart rate estimation model in response to a determination to estimate the heart rate.

公开(公告)号：US10380256B2

公开(公告)日：2019-08-13

申请号：US14866889

申请日：2015-09-26

Applicant: Intel Corporation

Inventor： Lama Nachman ,  Ashwini Asokan ,  Giuseppe Raffa ,  Rita H. Wouhaybi ,  Saurav Sahay ,  Omar U. Florez ,  Rahul C. Shah ,  Chieh-Yih Wan ,  Jonathan J. Huang ,  Hong Lu ,  Sangita Sharma ,  Junaith Ahemed Shahabdeen ,  Douglas P. Bogia ,  Lenitra Durham

IPC: G06F17/27 ,  G06N5/02 ,  G06F16/9535

Abstract: Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.