Deduplication of accounts using account data collision detected by machine learning models.

Deduplication of accounts using account data collision detected by machine learning models

Номер патента: AU2022420862A1
Опубликовано: 18-07-2024
Автор(ы): Eric Shiu
Принадлежит: Brex Inc
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Рисунок 1. Взаимосвязь патентов (ближайшие 20).

Deduplication of accounts using account data collision detected by machine learning models

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Deduplication of accounts using account data collision detected by machine learning models

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Augmenting machine learning models to incorporate incomplete datasets

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Predicting data tampering using augmented machine learning models

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Systems and methods for automated insertion of supplemental content into a virtual environment using a machine learning model

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Machine learning systems for automated database element processing and prediction output generation

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Explainable classifications with abstention using client agnostic machine learning models

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Machine learning computer system architecture

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System using artificial intelligence and machine learning to determine an impact of an innovation associated with an enterprise

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Systems and methods for determining a user specific mission operational performance metric, using machine-learning processes

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Systems and methods for automated insertion of supplemental content into a virtual environment using a machine learning model

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Systems and methods for automated insertion of supplemental content into a virtual environment using a machine learning model

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Systems and methods for automated insertion of supplemental content into a virtual environment using a machine learning model

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System and method for machine learning based detection of fraud

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Automated concept drift detection in live machine learning systems for machine learning model updating

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Method and apparatus for implementing a role-based access control clustering machine learning model execution module

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Method and apparatus for implementing a role-based access control clustering machine learning model execution module

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Method and apparatus for implementing a role-based access control clustering machine learning model execution module

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Generating a transformed dataset for use by a machine learning model in an artificial intelligence infrastructure

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Non-intrusive load monitoring using machine learning and processed training data

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Utilizing a machine learning model for predicting issues associated with a closing process of an entity

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System and method for mitigating bias in classification scores generated by machine learning models

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No-coding machine learning pipeline

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Method And Device For Drug Combination Design By High-Throughput Platform And Machine Learning For Optimizing

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Techniques for balancing dynamic inferencing by machine learning models

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Machine Learning Model Adversarial Attack Monitoring

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Machine learning model adversarial attack monitoring

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Authenticating Usage Data For Processing By Machine Learning Models

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Detection of runtime errors using machine learning

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Reducing semantic errors in code generated by machine learning models

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Reducing semantic errors in code generated by machine learning models

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Passive data collection and use of machine-learning models for event prediction

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Differential diagnosis feature engineering for machine learning applications

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Identification of input features used by machine learning model in providing output score

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Shared network learning for machine learning enabled text classification

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Method for securing a machine learning based decision system

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Method for securing a machine learning based decision system

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Control device, operation control device, server, management server, computer program, learning model, control method and operation control method

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System for controlling devices in iot networks using self-learning machine learning models

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Systems and methods detecting and mitigating anomalous shifts in a machine learning model

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No-coding machine learning pipeline

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Computer-implemented systems, methods and computer programs for adapting a machine-learning-architecture and for processing input data

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Techniques for validating machine learning models

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Integration of learning models into a software development system

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Machine learning model fingerprinting

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Validation of a machine learning model

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Semantics preservation for machine learning models deployed as dependent on other machine learning models

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Software model testing for machine learning models

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Method for securing a machine learning based decision system

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Learning method using machine learning to generate correct sentences, extraction method, and information processing apparatus

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Machine-learned model system

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Utilizing models to generate identifiers that identify and provide authentication for machine learning models

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Trust related management of artificial intelligence or machine learning pipelines in relation to the trustworthiness factor explainability

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Decision boundary enhancement for learning models

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Federated learning service in a provider network and training machine learning models using devices external to the provider network

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Automated problem detection for machine learning models

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Technical injection system for injecting a retrained machine learning model

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Data sovereignty compliant machine learning

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Systems and methods for generating dynamic conversational responses using ensemble prediction based on a plurality of machine learning models

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Computer-based systems, computing components and computing objects configured to implement dynamic outlier bias reduction in machine learning models

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Protecting machine learning models from privacy attacks

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Systems and methods for subscriber-based adaptation of production-implemented machine learning models of a service provider using a training application

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Machine learning method

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Dynamic allocation and re-allocation of learning model computing resources

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Dynamic allocation and re-allocation of learning model computing resources

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Computer-based systems, computing components and computing objects configured to implement dynamic outlier bias reduction in machine learning models

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Intelligently optimized machine learning models

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Machine learning model training method and device, and expression image classification method and device

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Storage medium, machine learning method, and machine learning device

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Methods for transforming categorical source data distributions into target data distributions for use by machine learning model training

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Meta-learning and auto-labeling for machine learning

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Computer-based systems, computing components and computing objects configured to implement dynamic outlier bias reduction in machine learning models

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Debugging Correctness Issues in Training Machine Learning Models

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Automatic testing with feature tags trained by machine learning for updates in version control systems

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Systems and methods for generating dynamic conversational responses using ensemble prediction based on a plurality of machine learning models

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Computer-based systems, computing components and computing objects configured to implement dynamic outlier bias reduction in machine learning models

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Machine learning model training method, service data processing method, apparatuses, and systems

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Systems and methods for rapidly building, managing, and sharing machine learning models

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Federated learning technique for applied machine learning

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Providing application programming interface endpoints for machine learning models

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Identification of idle network connections based on machine learning

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No-coding machine learning pipeline

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No-coding machine learning pipeline

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Machine learning model adversarial attack monitoring

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Chain schedule management for machine learning model-based processing in computing environment

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Multi-stage machine learning model training for key-value extraction

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Detecting anomalies in physical access event streams by computing probability density functions and cumulative probability density functions for current and future events using plurality of small scale machine learning models and historical context of events obtained from stored event stream history via transformations of the history into a time series of event counts or via augmenting the event stream records with delay/lag information

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Monitoring of edge- deployed machine learning models

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System and method for machine learning for system deployments without performance regressions

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Architecture to employ machine-learning model

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Machine learning model training using an analog processor

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New features for black-box machine-learning models

Номер патента: EP4416639A1. Автор: Christian Eggenberger,Patrick Lustenberger,Frederik Flöther,Saurabh Yadav. Владелец: International Business Machines Corp. Дата публикации: 2024-08-21.

Learning parameter sampling configuration for automated machine learning

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Executing unsupervised pre-training tasks with a machine learning model to predict document graph attributes

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Deployment of machine learned models to plurality of devices

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Dynamic input-sensitive validation of machine learning model outputs and methods and systems of the same

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Biological image transformation using machine-learning models

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Generation of findings in radiology reports by machine learning based on impressions

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Anomaly detection by classifying past behavior

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Generation of findings in radiology reports by machine learning based on impressions

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Apparatus and method for performing color conversions using machine learning

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Apparatus and method for performing color conversions using machine learning

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Machine learning devce

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Automated Explanation of Machine Learning Predictions Using Classification Score Targeting

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System for machine learning-based acceleration of a topology optimization process

Номер патента: WO2020160099A9. Автор: Le SONG,Yuyu Zhang,Lucia MIRABELLA,Heng CHI,Tsz Ling Elaine Tang,Janani VENUGOPALAN,Glaucio PAULINO. Владелец: GEORGIA TECH RESEARCH CORPORATION. Дата публикации: 2021-08-26.

Machine learning systems and methods for document recognition and analytics

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Machine learning device, data processing system, machine learning method, and data processing method

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Digital object library management system for machine learning applications

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Context enabled machine learning

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Explanatory dropout for machine learning models

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Machine learning model creation

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Implementing machine learning in a resource-constrained environment

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Implementing machine learning in a resource-constrained environment

Номер патента: WO2021005379A1. Автор: Sotiris MOSCHOYIANNIS,Angelos CHRISTIDIS. Владелец: UNIVERSITY OF SURREY. Дата публикации: 2021-01-14.

Machine learning research platform for automatically optimizing life sciences experiments

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Machine learning framework for tuning interactive voice response systems

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Scrubbing account data accessed via links to applications or devices

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System, user interface and method for interactive negative explanation of machine learning localization models in health care applications

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Responding to machine learning requests from multiple clients

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System for machine learning-based acceleration of a topology optimization process

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Scrubbing account data accessed via links to applications or devices

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De-noising using multiple threshold-expert machine learning models

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Machine learning program, machine learning method, and information processing apparatus

Номер патента: EP3995999A1. Автор: Yasushi Hara,Yutaka Kai,Akihiko Kasagi,Takumi DANJO. Владелец: Fujitsu Ltd. Дата публикации: 2022-05-11.

Using machine learning and/or neural networks to validate stem cells and their derivatives for use in cell therapy, drug discovery, and diagnostics

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Classification Evaluation and Improvement in Machine Learning Models

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System and method for increasing efficiency of gradient descent while training machine-learning models

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Machine learning models for electrical power simulations

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Active surveillance and learning for machine learning model authoring and deployment

Номер патента: EP3789929A1. Автор: Gopal B. Avinash,Junpyo Hong,Venkata Ratnam Saripalli,Karley Marty Yoder,Keith Bigelow. Владелец: GE Precision Healthcare LLC. Дата публикации: 2021-03-10.

Machine learning models for detecting the causes of conditions of a satellite communication system

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Automatic anomaly thresholding for machine learning

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Designing a fair machine learning model through user interaction

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Digital watermarking of machine-learning models

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Determining optimal machine learning models

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Detecting out-of-distribution data sample in a machine learning operation

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Automated explanation of machine learning predictions using classification score targeting

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Methods and apparatus for low precision training of a machine learning model

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Scanning and detecting threats in machine learning models

Номер патента: US20240289436A1. Автор: Thomas Bonner,James Ballard,Tanner Burns,Chris Sestito,Marta Janus,Eoin Wickens. Владелец: Hiddenlayer Inc. Дата публикации: 2024-08-29.

System, method, and computer program for a machine learning model-agnostic cloud-agnostic no-code onboarding platform

Номер патента: US12045698B1. Автор: Pavel Yefim MAY. Владелец: Amdocs Development Ltd. Дата публикации: 2024-07-23.

Data compression techniques for machine learning models

Номер патента: EP4413495A1. Автор: Bo Guo,Rajkumar BONDUGULA. Владелец: Equifax Inc. Дата публикации: 2024-08-14.

Automated generation of machine learning models

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Systems and Methods for Generating Names Using Machine-Learned Models

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Interactive adaptation of machine learning models for time series data

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Dynamic Machine Learning Model Selection

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Analysis-data analyzing device and analysis-data analyzing method that calculates or updates a degree of usefulness of each dimension of an input in a machine-learning model

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Automated localized machine learning training

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Training machine learning models to perform aligner damage prediction

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Probability distribution assessment for classifying subterranean formations using machine learning

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Machine learning model compression using weighted low-rank factorization

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Unattended object detection using machine learning

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Hybrid machine learning architecture and associated methods

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Violation checking method by machine learning based classifier

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Enhancing synergy between machine learning models and annotators

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Scanning and detecting threats in machine learning models

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Failure prediction in a computing system based on machine learning applied to alert data

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Machine learning driven teleprompter

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Machine learning controller and method for machine learning controller

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Monitoring of edge-deployed machine learning models

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Failure prediction in a computing system based on machine learning applied to alert data

Номер патента: WO2023136952A9. Автор: Baskar Jayaraman,Dinesh Kumar Kishorkumar Surapaneni,Matthew Lawrence Watkins. Владелец: ServiceNow, Inc.. Дата публикации: 2024-07-11.

Enhanced precision machine learning prediction

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Machine learning model validation and authentication

Номер патента: US12106212B2. Автор: Amir Mohammad TAHMASEBI MARAGHOOSH,Shawn Arie Peter Stapleton. Владелец: Koninklijke Philips NV. Дата публикации: 2024-10-01.

Automated machine learning system

Номер патента: US20240346375A1. Автор: Daniel J. Wallace,Killian B. Dent,James M. Friedman,Allan D. Johnson,Shauna J. Moran,Tyler P. Cooper,Chris K. Knoch,Nicholas R. Magnuson. Владелец: Big Squid Inc. Дата публикации: 2024-10-17.

Ephemeral learning of machine learning model(s)

Номер патента: US12126845B2. Автор: Francoise Beaufays,Trevor Strohman,Khe Chai Sim,Oren Litvin. Владелец: Google LLC. Дата публикации: 2024-10-22.

Video-based analysis of stapling events during a surgical procedure using machine learning

Номер патента: US12076005B2. Автор: Taylor W. Aronhalt,Darrick Tyler Sturgeon,Jocelyn Elaine Barker,Varun Kejriwal Goel. Владелец: Verb Surgical Inc. Дата публикации: 2024-09-03.

Explainable classifications with abstention using client agnostic machine learning models

Номер патента: US20240345905A1. Автор: Upendra Sharma,Rohit Khandekar,Arun A. Ayachitula. Владелец: Kyndryl Inc. Дата публикации: 2024-10-17.

System and method for training non-parametric machine learning model instances in a collaborative manner

Номер патента: US12131256B2. Автор: Krishnaprasad Lingadahalli Shastry,Suresh SOUNDARARAJAN,Sathyanarayanan MANAMOHAN,Patrick Leon Gartenbach,Markus Philipp Wuest. Владелец: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP. Дата публикации: 2024-10-29.

Transforming conversational training data for different machine learning models

Номер патента: US12136043B1. Автор: Mark William Davis,Milo Davis. Владелец: Likehuman LLC. Дата публикации: 2024-11-05.

Data compression techniques for machine learning models

Номер патента: US12061671B2. Автор: Bo Guo,Rajkumar BONDUGULA. Владелец: Equifax Inc. Дата публикации: 2024-08-13.

Meta-automated machine learning with improved multi-armed bandit algorithm for selecting and tuning a machine learning algorithm

Номер патента: US12056587B2. Автор: Mischa Schmidt,Julia Gastinger. Владелец: NEC Corp. Дата публикации: 2024-08-06.

Detection of runtime errors using machine learning

Номер патента: US20220342800A1. Автор: Neelakantan Sundaresan,Shaun Miller,Roshanak Zilouchian Moghaddam,Kalpathy Sitaraman Sivaraman,Yijin Wei. Владелец: Microsoft Technology Licensing LLC. Дата публикации: 2022-10-27.

Reducing semantic errors in code generated by machine learning models

Номер патента: US20230024047A1. Автор: Kavitha Srinivas,Louis Mandel,Julian Timothy Dolby,Martin Hirzel,Avraham Ever Shinnar,Kiran A Kate. Владелец: International Business Machines Corp. Дата публикации: 2023-01-26.

Executing Machine-Learning Models

Номер патента: US20220327428A1. Автор: Bin Sun,Konstantinos Vandikas,Rafia Inam,Aneta VULGARAKIS FELJAN. Владелец: Telefonaktiebolaget LM Ericsson AB. Дата публикации: 2022-10-13.

Detection of runtime errors using machine learning

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System and method for mitigating bias in classification scores generated by machine learning models

Номер патента: US12002258B2. Автор: Alexey Miroshnikov,Konstandinos Kotsiopoulos,Arjun Ravi Kannan,Raghu Kulkarni,Steven Dickerson. Владелец: Discover Financial Services Inc. Дата публикации: 2024-06-04.

Passive data collection and use of machine-learning models for event prediction

Номер патента: EP3890598A1. Автор: Amit Shah,Gari CLIFFORD,Ayse Cakmak,Erik REINERTSEN. Владелец: Georgia Tech Research Institute. Дата публикации: 2021-10-13.

Executing machine-learning models

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Simulation of electronic circuitry with machine learning augmentation

Номер патента: US20230394200A1. Автор: Neal J. Tuffy. Владелец: Skyworks Solutions Inc. Дата публикации: 2023-12-07.

Machine learning models with multi-budget differential privacy

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Machine learning system for analyzing the quality and efficacy of essays for higher education admissions

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Method for determining class of data to be determined using machine learning model, information processing device, and computer program

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Machine-learning based gesture recognition using multiple sensors

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Model optimization and data analysis using machine learning techniques

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Multiple sources of signals for hybrid metrology using physical modeling and machine learning

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Value over replacement feature (VORF) based determination of feature importance in machine learning

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Classifying a source of a login attempt to a user account using machine learning

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Hybrid machine learning methods of training and using models to predict formulation properties

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Methods, apparatus and machine-readable mediums relating to machine learning models

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