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：US20240338574A1

公开(公告)日：2024-10-10

申请号：US18623569

申请日：2024-04-01

Applicant: Nokia Technologies Oy

Inventor： Soumyajit CHATTERJEE ,  Akhil MATHUR

IPC: G06N3/098 ,  G06N3/04

CPC classification number: G06N3/098 ,  G06N3/04

Abstract: Example embodiments relate to an apparatus, method and computer program relating to federated learning for computational models. In an example, an apparatus comprises means for determining, based on one or more resources of a client device, whether a first computational model architecture can be trained locally by the client device within a target training time. The apparatus may also comprise means for selecting, if the first computational model architecture cannot be trained locally by the client device within the target training time, a modified version of the first computational model architecture that can be trained by the client device within the target training time. The apparatus may also comprise means for providing the selected modified version of the first computational model architecture for local training by the client device.

公开(公告)号：US20250156763A1

公开(公告)日：2025-05-15

申请号：US18944800

申请日：2024-11-12

Applicant: Nokia Technologies Oy

Inventor： Ryuhaerang CHOI ,  Soumyajit CHATTERJEE ,  Dimitrios SPATHIS ,  Mohammad MALEKZADEH

IPC: G06N20/00

Abstract: Example embodiments may relate to systems, methods and/or computer programs for reusing data for training machine learning models. In an example, an apparatus comprises means for receiving a request to collect new user data for training a machine learning model associated with an application. The apparatus may also comprise means for identifying existing stored data suitable for training the machine learning model based upon an ontology. The apparatus may also comprise means for providing access to the identified existing stored data in response to identifying that the data is suitable for training the machine learning model.

公开(公告)号：US20250021822A1

公开(公告)日：2025-01-16

申请号：US18768285

申请日：2024-07-10

Applicant: Nokia Technologies Oy

Inventor： Soumyajit CHATTERJEE ,  Mohammad MALEKZADEH

IPC: G06N3/0895

Abstract: A process for labelling of a time-series of un-labelled data for self-supervised training of a machine learning by analyzing the time series of un-labelled data to identify transition points where there is a change, in the time series, of the un-labelled data that exceeds a defined threshold value, segmenting the time-series of un-labelled data into segments at the transition points, identifying multiple features in the time-series of un-labelled data, and performing clustering of the identified features, segment-by-segment, to provide a label for a segment, segment-by-segment.