公开(公告)号：US20240112039A1

公开(公告)日：2024-04-04

申请号：US18238998

申请日：2023-08-28

Applicant: QUALCOMM Incorporated

Inventor： Seunghan YANG ,  Seokeon CHOI ,  Hyunsin PARK ,  Sungha CHOI ,  Sungrack YUN

IPC: G06N3/098 ,  H04L67/10

CPC classification number: G06N3/098 ,  H04L67/10

Abstract: Example implementations include methods, apparatuses, and computer-readable mediums of federated learning by a federated client device, comprising identifying client invariant information of a neural network for performing a machine learning (ML) task in a first domain known to a federated server. The implementations further comprising transmitting the client invariant information to the federated server, the federated server configured to generate a ML model for performing the ML task in a domain unknown to the federated server based on the client invariant information and other client invariant information of another neural network for performing the ML task in a second domain known to the federated server.

公开(公告)号：US20250068662A1

公开(公告)日：2025-02-27

申请号：US18454456

申请日：2023-08-23

Applicant: QUALCOMM Incorporated

Inventor： Seokeon CHOI ,  Juntae LEE ,  Jaewon CHOI

IPC: G06F16/33

Abstract: Various embodiments include systems and methods for generating a privacy-aware multi-modal autoreply to an incoming communication. A processing system of a computing device may collect multi-modal information, determine a current user circumstance based on the collected information, determine a user privacy preference for autoreply responses, and generate a prompt that is input to a generative large language model (LLM) to generate optional autoreply responses, receive a list of personalized response suggestions from the generative LLM, and perform an autoreply action based on a selected personalized response suggestion.

公开(公告)号：US20230376753A1

公开(公告)日：2023-11-23

申请号：US18157723

申请日：2023-01-20

Applicant: QUALCOMM Incorporated

Inventor： Seokeon CHOI ,  Sungha CHOI ,  Seunghan YANG ,  Hyunsin PARK ,  Debasmit DAS ,  Sungrack YUN

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: Systems and techniques are provided for training a neural network model or machine learning model. For example, a method of augmenting training data can include augmenting, based on a randomly initialized neural network, training data to generate augmented training data and aggregating data with a plurality of styles from the augmented training data to generate aggregated training data. The method can further include applying semantic-aware style fusion to the aggregated training data to generate fused training data and adding the fused training data as fictitious samples to the training data to generate updated training data for training the neural network model or machine learning model.

公开(公告)号：US20230281509A1

公开(公告)日：2023-09-07

申请号：US18086586

申请日：2022-12-21

Applicant: QUALCOMM Incorporated

Inventor： Sungha CHOI ,  Seunghan YANG ,  Seokeon CHOI ,  Sungrack YUN

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: A processor-implemented method includes training a machine learning model on a source domain. The method also includes testing the machine learning model on a target domain, after training. The method further includes training the machine learning model on the target domain by regularizing weights of the machine learning model such that shift-agnostic weights are subjected to a higher penalty than shift-biased weights.