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APPLICATIONS OF MACHINE LEARNING MODELS TO A BINARY SEARCH ENGINE BASED ON AN INVERTED INDEX OF BYTE SEQUENCES

Номер патента: US20190266141A1
Опубликовано: 29-08-2019
Автор(ы): Coroiu Horea, Radu Daniel, Radu Marian
Принадлежит: CrowdStrike, Inc.
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Judgment Method For Edge Node Computing Result Trustworthiness Based On Trust Evaluation

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MANAGING INDICATION OF ACCESSED TRACKS IN CACHE TO A MOST RECENTLY USED END OF A CACHE LIST BASED ON ACCESSES TO DIFFERENT REGIONS OF THE CACHE LIST

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Method for evaluating fracture connectivity and optimizing fracture parameters based on complex network theory

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Software model testing for machine learning models

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Method and system for creating an ensemble of machine learning models to defend against adversarial examples

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Machine learning model robustness against adversarial attacks in production

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

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Model-tiering machine learning model

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Distributed learning machine learning models for personalization

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Identification of idle network connections based on machine learning

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Dynamic analysis and monitoring of machine learning processes

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System to track and measure machine learning model efficacy

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

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Using a client-side machine learning model dynamically in a mobile enterprise application on a mobile device

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Biased based delegation in machine learning models

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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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Utilizing machine learning models to determine customer care actions for telecommunications network providers

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Dynamic Machine Learning Model Selection

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Facilitating implementation of machine learning models in embedded software

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Machine Learning Model Deployment in Inference System

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Enhanced network security based on inter-application data flow diagrams

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Effective leveraging of synthetic data for depth estimation machine learning models

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Machine learning model remote management in advanced communication networks

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Interactive adaptation of machine learning models for time series data

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Systems and methods for machine learning model management

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

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Separating documents based on machine learning models

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Utilizing elastic weight consolidation (ewc) loss term(s) to mitigate catastrophic forgetting in federated learning of machine learning model(s)

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Utilizing elastic weight consolidation (ewc) loss term(s) to mitigate catastrophic forgetting in federated learning of machine learning model(s)

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

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Simulating an application of a treatment on a demand side and a supply side associated with an online system

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Machine learning model remote management in advanced communication networks

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Predicting data tampering using augmented machine learning models

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Machine-learned movement determination based on intent identification

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Simulating an application of a treatment on a demand side and a supply side associated with an online system

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System and method for machine learning modeling and estimation of loss

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Machine-learned movement determination based on intent identification

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Machine learning techniques that identify attribution of small signal stimulus in noisy response channels

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Environment-specific training of machine learning models

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Environment-specific training of machine learning models

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Digital watermarking of machine learning models

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Offline evaluation of machine learning models with noise reduction

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Digital watermarking of machine learning models

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Moving decision boundaries in machine learning models

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Explainable machine learning based on wavelet analysis

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Techniques for securing network environments by identifying device attributes based on string field conventions

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Techniques for securing network environments by identifying device attributes based on string field conventions

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Training of machine learning models for predicting document metadata

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Systems and methods for evaluating machine-learning models and predictions

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System and method for training a machine learning model based on user-selected factors

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System and method for training a machine learning model based on user-selected factors

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Systems and methods for evaluating machine-learning models and predictions

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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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Dynamic allocation and re-allocation of learning model computing resources

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

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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 that recommends virtual experiences based on graphs and clustering

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Training or using sets of explainable machine-learning modeling algorithms for predicting timing of events

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Threat identification and mitigation system using machine learning

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Threat identification and mitigation system using machine learning

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Use of machine-learning models in creating messages for advocacy campaigns

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Methods for determining application of models in multi-vendor networks

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Use of Machine-Learning Models in Creating Messages for Advocacy Campaigns

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Use of Machine-Learning Models in Creating Messages for Advocacy Campaigns

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Device attribute determination based on protocol string conventions

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First-to-saturate single modal latent feature activation for explanation of machine learning models

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Systems and techniques for measuring model sensitivity and feature importance of machine learning models

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Efficient integration of machine learning models in building management systems

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Fit-for-basin continuous machine learning for well integrity

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Machine learning model validation with verification data

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Confidence volumes for earth modeling using machine learning

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Optimization for cascade machine learning models

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Artificial intelligence and machine learning models management and/or training

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Automated machine learning using large language models

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Machine learning modeling of probe intensity

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Training machine learning models to perform neural style transfer in three-dimensional shapes

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Machine learning system for detecting anomalies in hunt data

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Training and performing inference operations of machine learning models using secure multi-party computation

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Machine learning modeling of probe intensity

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