公开(公告)号：US20240127057A1

公开(公告)日：2024-04-18

申请号：US18467096

申请日：2023-09-14

Applicant: Nokia Technologies Oy

Inventor： Dimitrios SPATHIS ,  Akhil MATHUR

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: There is provided an apparatus, method and computer program for a network node comprising access to a pre-trained neural network node model, for causing the network node to: receive, from an apparatus, a request for a first plurality of embeddings associated with an intermediate layer of the neural network node model; and signal said first plurality of embeddings to the apparatus.

公开(公告)号：US20230222351A1

公开(公告)日：2023-07-13

申请号：US18150941

申请日：2023-01-06

Applicant: Nokia Technologies Oy

Inventor： Wiebke TOUSSAINT ,  Akhil MATHUR ,  Fahim KAWSAR

IPC: G06N3/09 ,  G06F16/28

CPC classification number: G06N3/09 ,  G06F16/285

Abstract: Example embodiments may relate to an apparatus, method and/or computer program for the updating, or tuning, of classifiers. For example, the method may comprise receiving data indicative of a positive or negative classification based on comparing an output value, generated by a computational model responsive to an input data, with a threshold value which divides a range of output values of the computational model into positive and negative classes of output values. A positive or a negative classification may be usable by the apparatus, or another apparatus, to trigger one or more processing operations. Other operations may comprise determining that the positive or negative classification is a false classification based on one or more events detected subsequent to generation of the output value and updating the threshold value responsive to determining that the positive or negative classification is a false classification.

公开(公告)号：US20210089872A1

公开(公告)日：2021-03-25

申请号：US16891697

申请日：2020-06-03

Applicant: Nokia Technologies Oy

Inventor： Shaoduo GAN ,  Akhil MATHUR ,  Anton ISOPOUSSU

IPC: G06N3/063 ,  G06N3/08 ,  H03M7/30

Abstract: An apparatus, method and computer program is described comprising: initialising weights of a target encoder based on a source encoder; initialising weights of a target discriminator associated with the target encoder such that the target discriminator is initialised to match a source discriminator associated with the source encoder; applying some of a target data set to the target encoder to generate target encoder outputs; applying the target encoder outputs to the target discriminator to generate a first local loss function output; training the target encoder to seek to increase the first local loss function output; training the target discriminator to seek to decrease the first local loss function output; and synchronising weights of the target discriminator and the source discriminator.

公开(公告)号：US20200027442A1

公开(公告)日：2020-01-23

申请号：US16513212

申请日：2019-07-16

Applicant: Nokia Technologies Oy

Inventor： Akhil MATHUR ,  Anton ISOPOUSSU ,  Nicholas LANE ,  Fahim KAWSAR

IPC: G10L15/01 ,  G06N20/00 ,  G06N3/08 ,  G10L21/02 ,  G10L15/06 ,  G10L15/18 ,  G10L15/16

Abstract: An apparatus comprising means for: using a generative neural network, trained to translate first sensor data to simulated second sensor data, to translate input first sensor data from a first sensor to simulated second sensor data; and providing the simulated second sensor data to a different, specific-task, machine-learning model for processing at least second sensor data.

公开(公告)号：US20240273404A1

公开(公告)日：2024-08-15

申请号：US18417351

申请日：2024-01-19

Applicant: Nokia Technologies Oy

Inventor： Shohreh DELDARI ,  Dimitrios SPATHIS ,  Akhil MATHUR ,  Mohammad MALEKZADEH

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Apparatus comprising means for: obtaining a first data sample and a second data sample; transforming the first data sample into a first feature embedding using a first machine learning model; transforming the second data sample into a second feature embedding using a second machine learning model; and generating a first global representation by masking at least one of: the first feature embedding or the second feature embedding. The apparatus further comprising means for: transforming the first global representation into a third feature embedding using a third machine learning model; and training at least the third machine learning model based on the third feature embedding.

公开(公告)号：US20240144009A1

公开(公告)日：2024-05-02

申请号：US18489347

申请日：2023-10-18

Applicant: Nokia Technologies Oy

Inventor： Fan MO ,  Soumyajit CHATTERJEE ,  Mohammad MALEKZADEH ,  Akhil MATHUR

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A terminal apparatus comprising capturing data, transmitting information indicative of computational resources available at the apparatus for neural network training, receiving an encoder, defining one or more layers of artificial neurons, to be used as an input portion of a neural network receiving a predictor, defining one or more layers of artificial neurons, to be used as an output portion of the neural network; training the predictor, not the encoder, using at least some of the captured data; and performing inference on captured data using the neural network formed from the encoder and the predictor.

公开(公告)号：US20230368025A1

公开(公告)日：2023-11-16

申请号：US18306513

申请日：2023-04-25

Applicant: Nokia Technologies Oy

Inventor： Ekdeep Singh LUBANA ,  Akhil MATHUR ,  Fahim KAWSAR

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: An apparatus, method and computer program is described comprising: obtaining local data comprising one or more samples at a user device; computing representations of at least some of said samples by passing said one or more samples through a local feature extractor; clustering the computed representations to generate local centroids; providing generated local centroids and parameters of the local feature extractor to a server; receiving global centroids and global feature extractor parameters from said server; updating the parameters of the local feature extractor based on the received global feature extractor parameters; assigning selected samples of one or more samples and one or more augmentations of said selected samples to global clusters; and further updating the updated parameters of the local feature extractor using machine learning principles, thereby generating a trained local feature extractor.

公开(公告)号：US20220330896A1

公开(公告)日：2022-10-20

申请号：US17760629

申请日：2020-08-31

Applicant: Nokia Technologies Oy

Inventor： Chulhong MIN ,  Alessandro MONTANARI ,  Fahim KAWSAR ,  Akhil MATHUR

IPC: A61B5/00 ,  G06N3/08

Abstract: This relates to the use of sensor evaluation in a multi-sensor environment. In a first aspect, this specification describes apparatus comprising: at least one processor; and at least one memory including computer program code. The at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform: receive sensor data from a plurality of sensors collected during a first time period; process the received sensor data through a plurality of layers of a neural network to generate an output indicative of the sensing quality of each of the plurality of sensors for a task; and cause a subset of the plurality of sensors to collect data during a second time period based on the output indicative of the suitability of each of the plurality of sensors for the task.

公开(公告)号：US20240152755A1

公开(公告)日：2024-05-09

申请号：US18491462

申请日：2023-10-20

Applicant: Nokia Technologies Oy

Inventor： Mohammad MALEKZADEH ,  Akhil MATHUR

IPC: G06N3/08 ,  G06N5/04

CPC classification number: G06N3/08 ,  G06N5/04

Abstract: An apparatus comprising: means for providing a first secret and data as inputs to a trained neural network to produce an output by inference; means for sending the output from the trained neural network to a remote server; means for receiving in reply from the server, an encoded label; means for using a second secret to decode the encoded label to obtain a label for the data.

公开(公告)号：US20240135193A1

公开(公告)日：2024-04-25

申请号：US18469997

申请日：2023-09-19

Applicant: Nokia Technologies Oy

Inventor： Akhil MATHUR

IPC: G06N3/098

CPC classification number: G06N3/098

Abstract: An apparatus, method and computer program is described comprising receiving, at an edge device from one or more federated learning (FL) services, one or more FL machine learning (ML) models and capabilities information associated with each FL ML model, computing the utility of each FL ML model based a quality of available training samples at the edge device for training the corresponding FL ML models and said capabilities information, ranking the FL ML models in a descending order of utility of the FL ML models; and performing training of each of the corresponding FL ML models of each FL service in a descending order of utility until a remaining available cost budget of a total available cost budget of the edge device expires.