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MACHINE LEARNING MODEL UPDATES TO ML ACCELERATORS

Номер патента: US20200341941A1
Опубликовано: 29-10-2020
Автор(ы): Dastidar Jaideep, Mittal Millind
Принадлежит: XILINX, INC.
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Machine learning for generative geometric modelling

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

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Machine learning model to preload search results

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Natural language analysis of a command line using a machine learning model to generate a natural language description of the command line

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Augmenting machine learning models to incorporate incomplete datasets

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Machine learning hyperparameter tuning

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Machine learning hyperparameter tuning

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Machine learning systems for predictive modeling and related methods

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Adding a fingerprint to a machine learning model

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Unattended object detection using machine learning

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Method and system for predicting performance in electronic design based on machine learning

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

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

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Automated Explanation of Machine Learning Predictions Using Classification Score Targeting

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System and method for autonomous learning of contents using a machine learning algorithm

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AMD-Data Analysis:ACADEMY DATA ANALYSIS USING MACHINE LEARNING, DEEP LEARNING PROGRAMMING

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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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De-noising using multiple threshold-expert machine learning models

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Dynamic gradient deception against adversarial examples in machine learning models

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Systems and Methods for Generating Names Using Machine-Learned Models

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No-coding machine learning pipeline

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Learning Parameter Sampling Configuration for Automated Machine Learning

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

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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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Automated explanation of machine learning predictions using classification score targeting

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Malleable confidence models and machine learning prediction

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Machine learning model operation management system and method

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Systems and methods for retraining machine-learning models to perform alert grouping

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Method, apparatus, and system for providing a location-aware evaluation of a machine learning model

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

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Machine learning model compression using weighted low-rank factorization

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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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Generation of digital standards using machine-learning model

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Text Classification via Term Mapping and Machine-learning Classification Model

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Training machine learning models using quantile and median ranking distillation

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Monitoring of edge- deployed machine learning models

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Machine learning model training using an analog processor

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New features for black-box machine-learning models

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Learning parameter sampling configuration for automated machine learning

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Monitoring of edge-deployed machine learning models

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Combined wide and deep machine learning models for automated database element processing systems, methods and apparatuses

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Explainable classifications with abstention using client agnostic machine learning models

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

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Explainable classifications with abstention using client agnostic machine learning models

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Transforming conversational training data for different machine learning models

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Biological image transformation using machine-learning models

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Digital object library management system for machine learning applications

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Responding to machine learning requests from multiple clients

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

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Classification Evaluation and Improvement in Machine Learning Models

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Protecting deep learned models

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Systems and Methods for Generating Names Using Machine-Learned Models

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Gating machine learning predictions on medical ultrasound images via risk and uncertainty quantification

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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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Access control for on-device machine learning models

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Measuring the generalization ability of a trained machine learning model with respect to given measurement data

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Measuring the generalization ability of a trained machine learning model with respect to given measurement data

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Explainable classifications with abstention using client agnostic machine learning models

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Explainable classifications with abstention using client agnostic machine learning models

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

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Determining data relevance and labeling, model updating, and deployment

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Identifying a classification hierarchy using a trained machine learning pipeline

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Root cause analysis for deterministic machine learning model

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Machine learning systems and methods for document recognition and analytics

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Explanatory dropout for machine learning models

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Machine learning model creation

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Machine learning research platform for automatically optimizing life sciences experiments

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Machine Learning Methods and Systems for Variety Profile Index Crop Characterization

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Machine learning methods and systems for variety profile index crop characterization

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Machine learning computer system architecture

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

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Anomaly and fraud detection with fake event detection using machine learning

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

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Determining optimal machine learning models

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Training and inference management for composite machine learning scenarios

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

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

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Using graph queries to obtain results from machine learning models

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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

Номер патента: US11341404B2. Автор: Akira Noda. Владелец: Shimadzu Corp. Дата публикации: 2022-05-24.

System and method for ensuring that the results of machine learning models can be audited

Номер патента: US20240265308A1. Автор: Kenny C. Gross,Kenneth P. Baclawski,Zhen Hua Liu,Dieter Gawlick,Guang C. Wang,Edward R. Wetherbee,Richard Paul SONDEREGGER,Anna MORAV. Владелец: Oracle International Corp. Дата публикации: 2024-08-08.

Incognito mode for personalized machine-learned models

Номер патента: EP4435598A2. Автор: Victor Carbune,Sandro Feuz. Владелец: Google LLC. Дата публикации: 2024-09-25.

Enhanced precision machine learning prediction

Номер патента: US12106189B2. Автор: Dongjin Lee,Dongyun Jin,Rezwana Karim,Rishikesh Sanjay Ghewari. Владелец: SAMSUNG ELECTRONICS CO LTD. Дата публикации: 2024-10-01.

Facilitating machine learning using remote data

Номер патента: US12039416B2. Автор: Siar Sarferaz. Владелец: SAP SE. Дата публикации: 2024-07-16.

Machine learning methods and systems for variety profile index crop characterization

Номер патента: US20230126363A1. Автор: William Kess Berg,Jon J. Fridgen,Andrew James WOODYARD,Jonathan Michael BOKMEYER. Владелец: Advanced Agrilytics Holdings LLC. Дата публикации: 2023-04-27.

Method and a system for testing machine learning and deep learning models for robustness, and durability against adversarial bias and privacy attacks

Номер патента: US20210357508A1. Автор: Yuval Elovici,Oleg BRODT,Michael Khavkin,Asaf Shabtai,David Mimran,Edita Grolman. Владелец: DEUTSCHE TELEKOM AG. Дата публикации: 2021-11-18.

Data compression techniques for machine learning models

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

Method, apparatus, and system for providing a location representation for machine learning tasks

Номер патента: US20220180184A1. Автор: Christopher CERVANTES,Srikrishna KOMPELLA. Владелец: Here Global BV. Дата публикации: 2022-06-09.

System and method for procedurally synthesizing datasets of objects of interest for training machine-learning models

Номер патента: US12039423B2. Автор: Jesse Clayton,Vladimir Glavtchev. Владелец: Nvidia Corp. Дата публикации: 2024-07-16.

Dynamically adjusting a serverless execution container pool for training and utilizing online machine-learning models

Номер патента: US12045701B2. Автор: Kanak Mahadik. Владелец: Adobe Inc. Дата публикации: 2024-07-23.

Metadata-based feature expansion for automated machine learning processes

Номер патента: US20240256552A1. Автор: Stephen James Todd,Robert Anthony Lincourt, Jr.,Eloy Francisco Macha. Владелец: Dell Products LP. Дата публикации: 2024-08-01.

Enhancing synergy between machine learning models and annotators

Номер патента: US20230177115A1. Автор: Pierpaolo Tommasi,Debasis GANGULY,Stephane DEPARIS,Charles Arthur Jochim. Владелец: International Business Machines Corp. Дата публикации: 2023-06-08.

Metadata-based feature expansion for automated machine learning processes

Номер патента: US12086144B2. Автор: Stephen James Todd,Robert Anthony Lincourt, Jr.,Eloy Francisco Macha. Владелец: Dell Products LP. Дата публикации: 2024-09-10.

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.

Machine-learning based gesture recognition using multiple sensors

Номер патента: US12118443B2. Автор: Charles MAALOUF,Christopher B. Fleizach,Behrooz Shahsavari,Hojjat Seyed Mousavi,Michael J. Beyhs,Shawn R. Scully,Tu K. NGUYEN,Lilian H. LIANG,Warren J. SETO,Julian QUINTANA. Владелец: Apple Inc. Дата публикации: 2024-10-15.

Data compression techniques for machine learning models

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

Machine Learning Feature Stability Alerts

Номер патента: US20220198319A1. Автор: Priya Singh,Shantanu Lodh,Cole Brendel. Владелец: Bottomline Technologies Inc. Дата публикации: 2022-06-23.

System and method for machine learning based detection of fraud

Номер патента: CA3108609A1. Автор: Yifan Wang,Lu Zou,Keitong Wong. Владелец: Toronto Dominion Bank. Дата публикации: 2022-08-11.

System and method for electronic compliance evaluation of transmitted object data via a machine learning model

Номер патента: US20240232693A1. Автор: Yogi Ahuja,Geetha Dwarakapuram. Владелец: Bank of America Corp. Дата публикации: 2024-07-11.

Automated data integration, reconciliation, and self healing using machine learning

Номер патента: US20210303547A1. Автор: Markus Goeppert,Daniel Zimmermann,Apoorv Bhargava,Syed Aleemuddin Noor,Gowthami Agumamidi. Владелец: SAP SE. Дата публикации: 2021-09-30.

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

Номер патента: US20220245450A1. Автор: Shin Nishimura,Hikaru KURASAWA,Ryoki Watanabe. Владелец: Seiko Epson Corp. Дата публикации: 2022-08-04.

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

Номер патента: AU2021312671A1. Автор: Yehezkel Shraga RESHEFF,Talia Tron,Tzvi Itzhak BARNHOLTZ. Владелец: Intuit Inc. Дата публикации: 2022-06-02.

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

Номер патента: CA3162546A1. Автор: Yehezkel Shraga RESHEFF,Talia Tron,Tzvi Itzhak BARNHOLTZ. Владелец: Intuit Inc. Дата публикации: 2022-01-27.

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

Номер патента: EP4049198A1. Автор: Yehezkel Shraga RESHEFF,Talia Tron,Tzvi Itzhak BARNHOLTZ. Владелец: Intuit Inc. Дата публикации: 2022-08-31.

Methods and systems for facilitating feature engineering for machine learning models

Номер патента: US20240202576A1. Автор: Olli Pekka Kostamaa,Ahmad Said Ghazal,Hanumath Rao Maduri. Владелец: Individual. Дата публикации: 2024-06-20.

Machine-learned model training for pedestrian attribute and gesture detection

Номер патента: US12051276B1. Автор: Yi Xu,XIN Wang,Vasiliy Karasev,Kratarth Goel,Sarah Tariq,Oytun Ulutan. Владелец: Zoox Inc. Дата публикации: 2024-07-30.

Systems and methods for detecting drift between data used to train a machine learning model and data used to execute the machine learning model

Номер патента: US20220383038A1. Автор: Karthik Rao,Keegan E. HINES,John P. Dickerson,Rowan CHEUNG,Reese M. E. HYDE. Владелец: Arthur Ai Inc. Дата публикации: 2022-12-01.

Machine learning model for storage system

Номер патента: US20230039564A1. Автор: Andrew R. Bernat,Prakash Darji. Владелец: Pure Storage Inc. Дата публикации: 2023-02-09.

Digital watermarking of machine-learning models

Номер патента: US20220050888A1. Автор: Peter Zatloukal. Владелец: Xnor AI Inc. Дата публикации: 2022-02-17.

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

Номер патента: US11768636B2. Автор: Igor Ostrovsky,Roy Kim,Brian Gold,Emily Watkins,Ivan Jibaja. Владелец: Pure Storage Inc. Дата публикации: 2023-09-26.

Machine learned model for contract generation in a document management system

Номер патента: US20240248934A1. Автор: Johan Hegardh. Владелец: Docusign Inc. Дата публикации: 2024-07-25.

Automated and optimal encoding of text data features for machine learning models

Номер патента: US20200097545A1. Автор: Shubhashis Sengupta,Milind Savagaonkar,Ajay Chatterjee. Владелец: Accenture Global Solutions Ltd. Дата публикации: 2020-03-26.

Machine learning model for storage system

Номер патента: US11775491B2. Автор: Andrew R. Bernat,Prakash Darji. Владелец: Pure Storage Inc. Дата публикации: 2023-10-03.

Machine learning to generate and evaluate visualizations

Номер патента: US11756245B2. Автор: Scott Rigney,Timothy Lang,Saurabh Abhyankar,Glenn Boysko. Владелец: Microstrategy Inc. Дата публикации: 2023-09-12.

Machine learning document classification

Номер патента: US12051255B1. Автор: Apoorv Sharma,Brian Holligan. Владелец: States Title LLC. Дата публикации: 2024-07-30.

Code completion with machine learning

Номер патента: EP4147122A1. Автор: Neelakantan Sundaresan,Xiaoyu Liu,Shengyu Fu. Владелец: Microsoft Technology Licensing LLC. Дата публикации: 2023-03-15.

Crowd-sourced data collection and labelling using gaming mechanics for machine learning model training

Номер патента: US12064697B2. Автор: Kang Zhang,Kevin Yu,Simone REBAUDENGO,Nick PITTOM,Matt AU. Владелец: Sidechef Group Ltd. Дата публикации: 2024-08-20.

Method for providing a training dataset for training and/or testing a machine learning model, method for training a machine learning model, and method for predicting timing and/or resource requirements of an unknown application running on an electronic device

Номер патента: EP4231154A1. Автор: Pengcheng HUANG,Thanikesavan Sivanthi,Andrea RUEETSCHI,Georgia Giannopoulou,Oliver SCHEUSS. Владелец: ABB Schweiz AG. Дата публикации: 2023-08-23.

Machine Learning Model Explanation Apparatus and Methods

Номер патента: US20200074331A1. Автор: Dustin Arendt,Zhuanyi Huang. Владелец: Battelle Memorial Institute Inc. Дата публикации: 2020-03-05.

Database query processing for hardware component identification using multi-ordered machine learning models

Номер патента: US20240228058A1. Автор: Jason W Buhro,Heather O Levesque,Lisa K Garcia,Ashley B Neeley,Sean M Lanagan,John P Herrman. Владелец: Camp Systems International Inc. Дата публикации: 2024-07-11.

Dynamic Machine Learning Model Selection

Номер патента: US20210264025A1. Автор: Aankur Bhatia,Gary I. Givental,Joel Rajakumar. Владелец: International Business Machines Corp. Дата публикации: 2021-08-26.

Automated process execution based on evaluation of machine learning models

Номер патента: US20210110293A1. Автор: Dennis Lehr. Владелец: SAP SE. Дата публикации: 2021-04-15.

Privacy enhanced machine learning

Номер патента: WO2021055046A1. Автор: Olga Ohrimenko,Sebastian TSCHIATSCHEK,Shruti Shrikant Tople. Владелец: Microsoft Technology Licensing, LLC. Дата публикации: 2021-03-25.

Refactoring code using a machine learning model

Номер патента: US20240289126A1. Автор: Kavitha Srinivas,Julian Timothy Dolby,Martin Hirzel,Kiran A. Kate,Jason Tsay. Владелец: International Business Machines Corp. Дата публикации: 2024-08-29.

Machine learned model for contract generation in a document management system

Номер патента: WO2024158594A1. Автор: Johan Hegardh. Владелец: DOCUSIGN, INC.. Дата публикации: 2024-08-02.

Stochastic data augmentation for machine learning

Номер патента: EP3789924A1. Автор: Dan Zhang,Emiel Hoogeboom. Владелец: ROBERT BOSCH GMBH. Дата публикации: 2021-03-10.

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

Номер патента: US11748350B2. Автор: Shi Qiao,Abhishek Roy,Soundararajan Srinivasan,Marc T. Friedman,Alekh Jindal,Irene Rogan Shaffer,Hiren Shantilal Patel,Gilbert Antonius,Markus Weimer,Remmelt Herbert Lieve Ammerlaan,Lucas Rosenblatt,Vijay Kumar Ramani,Peter Orenberg,H M Sajjad Hossain. Владелец: Microsoft Technology Licensing LLC. Дата публикации: 2023-09-05.

Privacy enhanced machine learning

Номер патента: US11366980B2. Автор: Olga Ohrimenko,Sebastian TSCHIATSCHEK,Shruti Shrikant Tople. Владелец: Microsoft Technology Licensing LLC. Дата публикации: 2022-06-21.

Hybrid machine learning architecture and associated methods

Номер патента: US20230385384A1. Автор: Gregor PAVLIN,Lennard JANSEN,Franck MIGNET. Владелец: Thales Nederland BV. Дата публикации: 2023-11-30.

Machine learning database memory use prediction and adaptation

Номер патента: US20230376202A1. Автор: Jing He,Xiaotao Wang. Владелец: SAP SE. Дата публикации: 2023-11-23.

Machine-learning model that recommends virtual experiences based on graphs and clustering

Номер патента: US20240177013A1. Автор: Xiaohong Gong,Xusheng Sun,Nemanja Petrovic,Shervin SHAHIDI,Nipun PARASRAMPURIA,Nishanth Rao Palimar RAGHUPATHI. Владелец: Roblox Corp. Дата публикации: 2024-05-30.

Machine learned model for generating opinionated threat assessments of security vulnerabilities

Номер патента: US12093397B1. Автор: Wah-Kwan Lin. Владелец: Rapid7 Inc. Дата публикации: 2024-09-17.

Validation of machine learning models using coreset trees

Номер патента: WO2024150230A1. Автор: Eitan NETZER,Oren Netzer,Liran SIGALAT. Владелец: Dataheroes, Ltd.. Дата публикации: 2024-07-18.

Apparatus and methods for training an educational machine-learning model

Номер патента: US20240311688A1. Автор: Michael Everest. Владелец: Edyou. Дата публикации: 2024-09-19.

Method for providing a training dataset for training and/or testing a machine learning model, method for training a machine learning model, and method for predicting timing and/or resource requirements of an unknown application running on an industrial automation and control system platform

Номер патента: WO2023156494A1. Автор: Pengcheng HUANG,Thanikesavan Sivanthi,Andrea RUEETSCHI,Georgia Giannopoulou,Oliver SCHEUSS. Владелец: ABB Schweiz AG. Дата публикации: 2023-08-24.

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

Номер патента: US12093255B2. Автор: Shi Qiao,Abhishek Roy,Soundararajan Srinivasan,Marc T. Friedman,Alekh Jindal,Irene Rogan Shaffer,Hiren Shantilal Patel,Gilbert Antonius,Markus Weimer,Remmelt Herbert Lieve Ammerlaan,Lucas Rosenblatt,Vijay Kumar Ramani,Peter Orenberg,H M Sajjad Hossain. Владелец: Microsoft Technology Licensing LLC. Дата публикации: 2024-09-17.

Machine learning model lineage tracking

Номер патента: WO2024173449A1. Автор: Wei Hao,Amar Phanishayee,Deepak Narayanan,Daniel Marcos MENDOZA. Владелец: Microsoft Technology Licensing, LLC. Дата публикации: 2024-08-22.

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

Номер патента: US12112388B2. Автор: Kaushik Dey,Chiranjit SEAL,Bula ROY,Atrayee CHATTERJEE,Punitha NITHYANANDAM. Владелец: Accenture Global Solutions Ltd. Дата публикации: 2024-10-08.

Machine learning model for calculating confidence scores associated with potential security vulnerabilities

Номер патента: US12118095B1. Автор: Stuart Millar,Denis Podgurskii. Владелец: Rapid7 Inc. Дата публикации: 2024-10-15.

Apparatus and methods for training an educational machine-learning model

Номер патента: WO2024192244A2. Автор: Michael Everest. Владелец: Edyou. Дата публикации: 2024-09-19.

Apparatus and methods for training an educational machine-learning model

Номер патента: WO2024192244A3. Автор: Michael Everest. Владелец: Edyou. Дата публикации: 2024-10-24.

Mask correction method, mask correction device for double patterning and training method for layout machine learning model

Номер патента: US12147155B2. Автор: Chung-Yi Chiu,Min-Cheng Yang. Владелец: United Microelectronics Corp. Дата публикации: 2024-11-19.

Integration verteilter Machine-Learning Modelle

Номер патента: DE102021117711A1. Автор: Manfred Paeschke,Andreas Wilke,Ilya Komarov. Владелец: BUNDESDRUCKEREI GMBH. Дата публикации: 2023-01-12.

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

Номер патента: US20230133843A1. Автор: Atul Verma,Himanshu Maurya,Ashish Shriram Tulsankar,Ashish Fernando. Владелец: Ischoolconnect Inc. Дата публикации: 2023-05-04.

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

Номер патента: WO2023250152A1. Автор: Jie Li,Wei Ming CHIEW,Pei Fen TEH,Jingsheng SHI. Владелец: Onto Innovation Inc.. Дата публикации: 2023-12-28.

Quality and efficacy analysis of statement of purpose in higher education admissions using machine learning

Номер патента: US20240281607A1. Автор: Atul Verma,Himanshu Maurya,Ashish Shriram Tulsankar,Ashish Fernando. Владелец: Ischoolconnect Inc. Дата публикации: 2024-08-22.

Machine learning with an intelligent continuous learning service in a big data environment

Номер патента: US11755951B2. Автор: Reghuram VASANTHAKUMARI,Aishwary Thakur,Ayesha Karim,Dinesh Babu Thirukondan Gnaneswaran,Naveen Adarsh Petla. Владелец: VMware LLC. Дата публикации: 2023-09-12.

Recommendation generation using machine learning data validation

Номер патента: GB2627119A. Автор: GAWLICK DIETER,CHYSTIAKOVA Anna,Charles Rohrkemper James,Paul Sonderegger Richard,Paul Baclawski Kenneth,C Gross Kenny,Hua Liu Zhen,Chao Wang Guang. Владелец: Oracle International Corp. Дата публикации: 2024-08-14.

Data meta-model based feature vector set generation for training machine learning models

Номер патента: EP3859645A1. Автор: Gautam Shroff,Mayank Mishra,Pankaj Malhotra,Rekha Singhal,Manoj Karunakaran Nambiar,Shruti Kunde,Amey PANDIT,Sharod ROY CHOUDHURY,Siddharth VERMA. Владелец: Tata Consultancy Services Ltd. Дата публикации: 2021-08-04.

Recommendation generation using machine learning data validation

Номер патента: US20230153680A1. Автор: Kenny C. Gross,Zhen Hua Liu,Dieter Gawlick,Kenneth Paul Baclawski,Guang Chao Wang,Anna CHYSTIAKOVA,Richard Paul SONDEREGGER,James Charles ROHRKEMPER. Владелец: Oracle International Corp. Дата публикации: 2023-05-18.

Probability distribution assessment for classifying subterranean formations using machine learning

Номер патента: GB2599881A. Автор: BAINES Graham,ZHANG Jiazuo. Владелец: Landmark Graphics Corp. Дата публикации: 2022-04-13.

Explainable machine learning based on wavelet analysis

Номер патента: EP4449311A1. Автор: Jeffery Dugger. Владелец: Equifax Inc. Дата публикации: 2024-10-23.

Chart building user interface providing machine learned chart recommendations

Номер патента: US11853858B2. Автор: Frank Mitchell. Владелец: Rapid7 Inc. Дата публикации: 2023-12-26.

Machine learned chart recommendation system

Номер патента: US11526727B1. Автор: Frank Mitchell. Владелец: Rapid7 Inc. Дата публикации: 2022-12-13.

Entity identification using machine learning

Номер патента: US20230282020A1. Автор: Barnaby John James,Christopher Thornton,Grace Taixi Brentano. Владелец: X Development LLC. Дата публикации: 2023-09-07.

Methods and apparatus for machine learning-based movement recognition

Номер патента: US20220350398A1. Автор: Sean Michael PETTERSON,Michael Dohyun KIM,Michael Patrick SPINELLI,Sivasankara Reddy BOMMIREDDY. Владелец: Strongarm Technologies Inc. Дата публикации: 2022-11-03.

Computer-based systems including machine learning models trained on distinct dataset types and methods of use thereof

Номер патента: US20210241036A1. Автор: Joshua Edwards,Michael Mossoba,Abdelkader M'Hamed Benkreira. Владелец: Capital One Services LLC. Дата публикации: 2021-08-05.

Determining substrate profile properties using machine learning

Номер патента: EP4186012A1. Автор: Steven Trey TINDEL,Upendra Ummethala,Michael Kutney,Prashanth Kumar,Zhaozhao ZHU,Blake Erickson. Владелец: Applied Materials Inc. Дата публикации: 2023-05-31.

Edge devices and gateways with machine learning for detecting anomalies in building equipment vibration data

Номер патента: US12050442B2. Автор: John M. Sullivan,Kelsey C. Schuster,Christopher J. Verink,Matthias Walczyk,Andrew S. Pike. Владелец: Tyco Fire and Security GmbH. Дата публикации: 2024-07-30.

Model optimization and data analysis using machine learning techniques

Номер патента: US20240257974A1. Автор: Brent Vaughan,Dennis WALL,Abdelhalim Abbas,Sharief Khalil TARAMAN. Владелец: Cognoa Inc. Дата публикации: 2024-08-01.

Machine learning based duplicate invoice detection

Номер патента: US12045215B2. Автор: Krishnan Ramanathan,Akash BAVISKAR. Владелец: Oracle Internatio Nal Corp. Дата публикации: 2024-07-23.

Hybrid input machine learning frameworks

Номер патента: US20210327455A1. Автор: Damian Kelly,Megan O'Brien,Randy Olinger. Владелец: Optum Inc. Дата публикации: 2021-10-21.

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 training based on dual loss functions

Номер патента: CA3206485A1. Автор: Francis Grady. Владелец: Schlumberger Canada Ltd. Дата публикации: 2022-07-07.

Machine learning model for predicting health plans based on missing input data

Номер патента: US12045894B2. Автор: James L. Poteet, III,Raymond G. Delano, III,Julie Ann Jensen. Владелец: Cerner Innovation Inc. Дата публикации: 2024-07-23.

Generating object-based layers for digital image editing using object classification machine learning models

Номер патента: US12056791B2. Автор: Harshit Agrawal,Venkatrayalu Krishnamurthy Logashwar. Владелец: Adobe Inc. Дата публикации: 2024-08-06.

Machine learning based prediction of document metadata

Номер патента: WO2024151630A9. Автор: Yan He,David Lange,Qing Zheng,Kaushik Narayanan,David DeBarr,David Matthew Wong,Vinay Jethava,Mohammad Mehdi Ghanimifard,Pontus Lindstrom,Gowtham Rangarajan Raman. Владелец: DOCUSIGN, INC.. Дата публикации: 2024-08-29.

Machine learning based prediction of document metadata

Номер патента: WO2024151630A1. Автор: Yan He,David Lange,Qing Zheng,Kaushik Narayanan,David DeBarr,David Matthew Wong,Vinay Jethava,Mohammad Mehdi Ghanimifard,Pontus Lindstrom,Gowtham Rangarajan Raman. Владелец: DOCUSIGN, INC.. Дата публикации: 2024-07-18.

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.

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

Номер патента: WO2020160099A1. Автор: Le SONG,Yuyu Zhang,Lucia MIRABELLA,Heng CHI,Tsz Ling Elaine Tang,Janani VENUGOPALAN,Glaucio PAULINO. Владелец: GEORGIA TECH RESEARCH CORPORATION. Дата публикации: 2020-08-06.

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

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System for Machine Learning-Based Acceleration of a Topology Optimization Process

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Multiple machine learning model anomaly detection framework

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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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Detecting code anomalies in source code using machine learning techniques

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Self contrastive decorrelation based training of machine learning models

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Deployment of machine learned models to plurality of devices

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

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Automatic anomaly thresholding for machine learning

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Training machine learning models to perform aligner damage prediction

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Image-based document search using machine learning

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Machine-learning based gesture recognition using multiple sensors

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Machine learning models with multi-budget differential privacy

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Identification of patent-relevant messages in a group-based communication system using machine learning techniques

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Analysis device and method for detecting variable vulnerability in software using machine learning model

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

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Machine-learning based gesture recognition using multiple sensors

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Storage device predicting failure using machine learning and method of operating the same

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

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Machine learning-based summarization and evaluation of clinical data

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Triggering execution of machine learning based prediction of document metadata

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Machine learning based prediction of document metadata

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Adaptive batching for optimizing execution of machine learning tasks

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User equipment, base station, and wireless communication methods based on machine learning/artificial intelligence

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Computer-readable recording medium storing machine learning program, machine learning method, and information processing apparatus

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Ascertaining and/or mitigating extent of effective reconstruction, of predictions, from model updates transmitted in federated learning

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Sparsity-inducing federated machine learning

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Model update method and apparatus in communication system, and storage medium

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Model update necessity determination system and update necessity determination method of model update necessity determination system

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Machine learning model updating

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Machine learning model update based on dataset or feature unlearning

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Machine learning model update based on dataset or feature unlearning

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Systems and methods for machine learning model training and deployment

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Decentralized learning of machine learning model(s) through utilization of stale updates(s) received from straggler computing device(s)

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Methods and apparatuses for training and using a machine learning model to determine a parameter for use in a personalised collaborative learning process

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System, method, and computer program product for time-based ensemble learning using supervised and unsupervised machine learning models

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Systems and methods for machine learning model management

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Evolved machine learning models

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Machine learning model for automatically detecting faults using optical inspection

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Framework for a machine learning model and/or machine learning application adaptation for a target in a communications network

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Method and system for training a machine learning model

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Method and apparatus for training machine learning models, computer device, and storage medium

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Sparsity-inducing federated machine learning

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Facilitating implementation of machine learning models in embedded software

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Offline evaluation of machine learning models with noise reduction

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Machine learning model aggregation

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Hybrid machine learning architecture for visual content processing and uses thereof

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

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

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

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Personalized machine learning on mobile computing devices

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System, Method, and Computer Program Product for Segmentation Using Knowledge Transfer Based Machine Learning Techniques

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Apparatus, method, and computer program product for configuration, association, registration, training, and monitoring of machine learning models for operational systems

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Machine Learning Model Deployment in Inference System

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Optimization for cascade machine learning models

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

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Confidential tuning of pre-trained machine learning models

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Automated progressive tuning of machine-learning model for fault localization in overhead transmission line

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Systems and methods for evaluating machine-learning models and predictions

Номер патента: US20240220778A1. Автор: Kenneth Wenger,Damian Brunt Fozard. Владелец: Squint Ai Inc. Дата публикации: 2024-07-04.

Automated progressive tuning of machine-learning model for fault localization in overhead transmission line

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Hybrid machine learning architecture for visual content processing and uses thereof

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Dynamic machine learning on premise model selection based on entity clustering and feedback

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Systems and methods for evaluating machine-learning models and predictions

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Methods, systems and computer programs for adjusting a first and a second machine-learning model and for processing a set of images, imaging system

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Context enabled machine learning

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Career progression planning tool using a trained machine learning model

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Mask correction method, mask correction device for double patterning and training method for layout machine learning model

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Machine learning system for automated recommendations of evidence during dispute resolution

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Training and executing machine-learning models for building data conversion

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Machine learning model lineage tracking

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Computer-readable recording medium storing machine learning program, machine learning method, and machine learning device

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Machine learning for vehicle allocation

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Hyper parameter tuning for machine learning models

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Predictive assignments that relate to genetic information and leverage machine learning models

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Machine learning apparatus, method, and non-transitory computer readable medium storing program

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Undercarriage wear prediction using machine learning model

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Undercarriage wear prediction using machine learning model

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Undercarriage wear prediction using machine learning model

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Using machine learning and 3d projection to guide medical procedures

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Dynamic variable quantization of machine learning inputs

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Generalizable machine learning algorithms for flash calculations

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Seismic well tie based on machine learning

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Seismic well tie based on machine learning

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Controlling devices in operations areas based on environmental states detected using machine learning

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Learning model generation method, learning model generation device, method for controlling molten iron temperature in blast furnace, method for guiding molten iron temperature control in blast furnace, and molten iron manufacturing method

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Machine learning models based methods and systems for determining prospective acquisitions between business entities

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Management of drifted records in machine learning

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Machine-learning model for predictive plant breeding using phenomic selection to predict grain composition

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System and method for a machine learning service

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Systems and methods for estimating robustness of a machine learning model

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Determining machine learning model anomalies and impact on business output data

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Systems and methods for estimating robustness of a machine learning model

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Method and system for intelligent bid price selection for profit accumulation using multiple software agents and machine learning model

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Blockchain hosted machine learning

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System and method of operation for remotely operated vehicles leveraging synthetic data to train machine learning models

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Security, luggage tracking, and machine learning models

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Supplying HMI snapshots from industrial automation environments as input to machine learning models

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Machine-learning techniques for predicting actions and behavior

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Methods, systems, apparatuses, and devices for facilitating a diagnosis of pathologies using a machine learning model

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System and method for automatically reconstructing 3D model of an object using machine learning model

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Computer-readable recording medium storing machine learning program, machine learning apparatus, and machine learning method

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Machine-learning techniques for detecting artifact pixels in images

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Multi arm machine learning models with attention for lesion segmentation

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Sales orchestration using iterative machine learning

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Machine learning for predictive in-flight alerts

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Machine learning for antibody discovery and uses thereof

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Werkergegenstandsaufbewahrungsvorrichtung, verfahren zur beurteilung des beladungszustands einer aufnahmevorrichtung und verfahren zum erstellen eines machine learning modells

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Machine-learning modeling to generate virtual bolus attributes

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Machine learning models for asset optimization within industrial automation environments

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Machine learning for protein identification

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Methods and systems for privacy preserving evaluation of machine learning models

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Machine learning model monitoring with autoencoder

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On-device machine learning-based network bandwidth prediction to improve adaptive media streaming performance

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Machine learning models for spatial reuse

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Generating model update data at satellite

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Generating model update data at satellite

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Model update techniques in wireless communications

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Generating model update data at satellite

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Techniques for machine learning scheme changing based at least in part on dynamic network changes

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Multi-head machine learning model for processing multi-sensor data

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Training Action Prediction Machine-Learning Models for Video Games with Healed Data

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