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    Trade platform with reinforcement learning network and matching engine
    1.
    发明授权
    Trade platform with reinforcement learning network and matching engine 有权

    公开(公告)号：US12099874B2

    公开(公告)日：2024-09-24

    申请号：US18227079

    申请日：2023-07-27

    申请人： ROYAL BANK OF CANADA

    发明人： Hasham Burhani ,  Zichang Long ,  Jonathan Cupillari

    IPC分类号： G06F9/50 ,  G06F9/48 ,  G06N5/00 ,  G06N20/00 ,  G06Q40/00

    CPC分类号： G06F9/50 ,  G06F9/48 ,  G06F9/4881 ,  G06F9/5005 ,  G06N5/00 ,  G06N20/00 ,  G06Q40/00

    摘要： A system for reinforcement learning in a dynamic resource environment includes at least one memory and at least one processor configured to provide an electronic resource environment comprising: a matching engine and the resource generating agent configured for: obtaining from a historical data processing task database a plurality of historical data processing tasks, each historical data processing task including respective task resource requirement data; for a historical data processing task of the plurality of historical data processing tasks, generating layers of data processing tasks wherein a first layer data processing task has an incremental variant in its resource requirement data relative to resource requirement data for a second layer data processing task; and providing the layers of data processing tasks for matching by the machine engine.

    Targeted training of inductive multi-organization recommendation models for enterprise applications
    4.
    发明授权
    Targeted training of inductive multi-organization recommendation models for enterprise applications 有权

    公开(公告)号：US11983649B2

    公开(公告)日：2024-05-14

    申请号：US17510523

    申请日：2021-10-26

    申请人： Microsoft Technology Licensing, LLC

    发明人： Kiran Tomlinson ,  Longqi Yang ,  Mengting Wan ,  Cao Lu ,  Brent Jaron Hecht ,  Jaime Teevan

    IPC分类号： G06Q10/00 ,  G06N5/00 ,  G06N5/022 ,  G06N5/04 ,  G06Q10/063

    CPC分类号： G06Q10/063 ,  G06N5/022 ,  G06N5/04

    摘要： An enterprise system server, a computer-readable storage medium, and a method for targeted training of inductive multi-organization recommendation models for enterprise applications are described herein. The method includes receiving enterprise application data from remote organization computing systems executing the enterprise application, training per-organization recommendation models for a subset of the organizations, and validating each per-organization recommendation model on enterprise application data corresponding to one or more other organizations. The method also includes calculating a transferability metric for each per-organization recommendation model based on results obtained during validation, determining a specified number of organizations including the best-transferring per-organization recommendation models based on the calculated transferability metrics, and training an inductive multi-organization recommendation model using the enterprise application data from the specified number of organizations. The method further includes utilizing the trained inductive multi-organization recommendation model to provide user recommendations to the remote organization computing systems during execution of the enterprise application.

    MANAGED SOLVER EXECUTION USING DIFFERENT SOLVER TYPES
    5.
    发明公开
    MANAGED SOLVER EXECUTION USING DIFFERENT SOLVER TYPES 审中-公开

    公开(公告)号：US20240112067A1

    公开(公告)日：2024-04-04

    申请号：US17936793

    申请日：2022-09-29

    申请人： Amazon Technologies, Inc.

    发明人： Shreyas Vathul Subramanian ,  Amey K Dhavle ,  Guvenc Degirmenci ,  Kai Fan Tang ,  Daniel Romero

    IPC分类号： G06N20/00 ,  G06N5/00

    CPC分类号： G06N20/00 ,  G06N5/003

    摘要： A multitenant solver execution service provides managed infrastructure for defining and solving large-scale optimization problems. In embodiments, the service executes solver jobs on managed compute resources such as virtual machines or containers. The compute resources can be automatically scaled up or down based on client demand and are assigned to solver jobs in a serverless manner. Solver jobs can be initiated based on configured triggers. In embodiments, the service allows users to select from different types of solvers, mix different solvers in a solver job, and translate a model from one solver to another solver. In embodiments, the service provides developer interfaces to, for example, run solver experiments, recommend solver types or solver settings, and suggest model templates. The solver execution service relieves developers from having to manage infrastructure for running optimization solvers and allows developers to easily work with different types of solvers via a unified interface.

    CONTINUOUS GROUNDWATER MONITORING USING MACHINE LEARNING
    7.
    发明公开
    CONTINUOUS GROUNDWATER MONITORING USING MACHINE LEARNING 审中-公开

    公开(公告)号：US20240053508A1

    公开(公告)日：2024-02-15

    申请号：US17886812

    申请日：2022-08-12

    申请人： Akhila Ram

    发明人： Akhila Ram

    IPC分类号： G01W1/10 ,  G01W1/14 ,  G01W1/02 ,  G06V20/13 ,  G06V20/10 ,  G06N5/00

    CPC分类号： G01W1/10 ,  G01W1/14 ,  G01W1/02 ,  G06V20/13 ,  G06V20/182 ,  G06N5/003

    摘要： Techniques are described for predicting groundwater for a locale, which is a subregion of a geographic region for which measurements of water storage are available at a coarse level. In a method, in response to receiving an input locale, a prediction of groundwater level for the input locale is provided. The prediction of groundwater level at the input locale is computed using a machine learning model. The machine learning model uses a plurality of parameters, which are weighted during a training phase of the machine learning model, and water storage measurements for a geographic region that encompasses the locale, the geographic region being larger than the locale, and wherein a resolution of the water storage measurements is downscaled. The prediction of groundwater level is outputted for the input locale.

    MACHINE-LEARNING MODEL TO PREDICT LIKELIHOOD OF EVENTS IMPACTING A PRODUCT
    9.
    发明公开
    MACHINE-LEARNING MODEL TO PREDICT LIKELIHOOD OF EVENTS IMPACTING A PRODUCT 审中-公开

    公开(公告)号：US20240046347A1

    公开(公告)日：2024-02-08

    申请号：US17883807

    申请日：2022-08-09

    申请人： Tide Platform Limited

    发明人： Natalia Koupanou

    IPC分类号： G06Q40/02 ,  G06N5/00

    CPC分类号： G06Q40/025 ,  G06N5/003

    摘要： A risk-evaluation model is trained using historical data to predict the likelihoods of future events in a future time period that impact a product. The time period may correspond to the time period over which the product is provided. On receiving a request for the product, the model is used to predict the likelihood of an event occurring and a recommendation of whether to provide the product is made to a provider of the product. The product may be provided based on the recommendation.