公开(公告)号：US20250007858A1

公开(公告)日：2025-01-02

申请号：US18342516

申请日：2023-06-27

Applicant: ADOBE INC.

Inventor： Kanak MAHADIK ,  Tong YU ,  Junda WU

IPC: H04L47/78 ,  H04L41/16

Abstract: Methods for determining optimal cloud service resource include determining a reward function for a set of resource configurations identifying cloud service resource parameters. The cloud service resource parameters include a source parameter and a target parameter of services to provide a client computing device. A source parameter dataset for the source parameter and a target parameter dataset is generated using the reward function and historical source parameter data. The matrices are then subject to SVD and clustering. A target parameter reward dataset is learned from output of the SVD and clustering. The target parameter dataset is used to determine the parameters for the target parameter for providing corresponding cloud service resources.

公开(公告)号：US20240273296A1

公开(公告)日：2024-08-15

申请号：US18625884

申请日：2024-04-03

Applicant: Adobe Inc.

Inventor： Sungchul KIM ,  Subrata MITRA ,  Ruiyi Zhang ,  Rui Wang ,  Handong ZHAO ,  Tong YU

IPC: G06F40/295 ,  G06N20/00

CPC classification number: G06F40/295 ,  G06N20/00

Abstract: Embodiments of the technology described herein describe a machine classifier capable of continually learning new classes through a continual few-shot learning approach. A natural language processing (NLP) machine classifier may initially be trained to identify a plurality of other classes through a conventional training process. In order to learn a new class, natural-language training data for a new class is generated. The training data for the new class may be few-shot training data. The training also uses synthetic training data that represents each of the plurality of other classes. The synthetic training data may be generated through a model inversion of the original classifier. The synthetic training data and the natural-language training data are used to retrain the NLP classifier to identify text in the plurality of other classes and the new class using.

公开(公告)号：US20240303569A1

公开(公告)日：2024-09-12

申请号：US18120088

申请日：2023-03-10

Applicant: Adobe Inc.

Inventor： Tong YU ,  Kanak MAHADIK

IPC: G06Q10/0631 ,  G06N20/00

CPC classification number: G06Q10/06316 ,  G06N20/00

Abstract: Embodiments of the present disclosure provide systems, methods, and computer storage media for resource provisioning of microservices using guided order of learning in a reinforcement learning framework. In embodiments, service resource information relating to microservices operating in a computing environment is received and used to perform a similarity analysis to generate similarity scores for each of the services. The service resource information is ordered based on a closeness between the similarity scores of the services. The ordered service resource information is inputted into a reinforcement learning agent to generate a resource configuration determination of at least one service of the services. The resource configuration determination is then provided to a provisioning component associated with the computing environment for provisioning the microservice.