MACHINE LEARNING

VolverVolver

Resultados 72 resultados LastUpdate Última actualización 07/08/2022 [12:58:00] pdf PDF xls XLS

Solicitudes publicadas en los últimos 30 días / Applications published in the last 30 days



Página1 de 3 nextPage   por página


SYSTEMS AND METHODS FOR TRAINING OF MULTI-OBJECTIVE MACHINE LEARNING ALGORITHMS

NºPublicación: US2022245669A1 04/08/2022

Solicitante:

WALMART APOLLO LLC [US]

Resumen de: US2022245669A1

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving one or more objectives and one or more constraints from a user electronic device of a user; generating a combined objective using the one or more objectives; calculating, using the combined objective, a return per click for an advertisement campaign; determining one or more bids based on (a) the return per click for the advertisement campaign and (b) a return on advertising spend for the advertisement campaign; estimating, using a first predictive algorithm and the one or more bids, an average cost per click; estimating an expected number of clicks for the advertisement campaign based on the average cost per click; determining a total amount used of the one or more constraints for the one or more bids based on the expected number of clicks for the advertisement campaign; and when the total amount used of the one or more constraints for the one or more bids exceeds at least one of the one or more constraints, lowering the one or more bids. Other embodiments are disclosed herein.

traducir

AI-POWERED AUTONOMOUS PLANT-GROWTH OPTIMIZATION SYSTEM THAT AUTOMATICALLY ADJUSTS INPUT VARIABLES TO YIELD DESIRED HARVEST TRAITS

NºPublicación: US2022245940A1 04/08/2022

Solicitante:

AGEYE TECH INC [US]

US_2021027057_A1

Resumen de: US2022245940A1

Inputs from sensors (e.g., image and environmental sensors) are used for real-time optimization of plant growth in indoor farms by adjusting the light provided to the plants and other environmental factors. The sensors use wireless connectivity to create an Internet of Things network. The optimization is determined using machine-learning analysis and image recognition of the plants being grown. Once a machine-learning model has been generated and/or trained in the cloud, the model is deployed to an edge device located at the indoor farm to overcome connectivity issues between the sensors and the cloud. Plants in an indoor farm are continuously monitored and the light energy intensity and spectral output are automatically adjusted to optimal levels at optimal times to create better crops. The methods and systems are self-regulating in that light controls the plant's growth, and the plant's growth in-turn controls the spectral output and intensity of the light.

traducir

SYSTEMS AND METHODS FOR AUTOMATED INSERTION OF SUPPLEMENTAL CONTENT INTO A VIRTUAL ENVIRONMENT USING A MACHINE LEARNING MODEL

NºPublicación: US2022245901A1 04/08/2022

Solicitante:

ROVI GUIDES INC [US]

CA_3104306_PA

Resumen de: US2022245901A1

Insertion of supplemental content into a virtual environment is automated using a machine learning model. The machine learning model is trained to calculate a confidence value that a candidate virtual object fits into a virtual environment based on an input that includes a candidate virtual object, a list of persistent virtual objects, and a list of temporary virtual objects. The machine learning model is trained using the persistent and temporary objects displayed in the current virtual environment until it predicts that a selected virtual object fits into the current virtual environment. The trained machine learning model is then used to select a virtual object comprising supplemental content to be inserted as a new virtual object in the virtual environment.

traducir

GRAPH DATA REPRESENTATION SYSTEMS AND METHODS FOR ELIGIBILITY DETERMINATION AND/OR MONITORING

NºPublicación: US2022245481A1 04/08/2022

Solicitante:

OPTUM INC [US]

Resumen de: US2022245481A1

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for processing an inclusion of an entity for an event. In accordance with one embodiment, a method is provided that includes: determining whether a graph representation data object comprises an inbound edge connecting an entity node representing the entity with an event node representing the event; and responsive to determining the graph representation data object comprises the inbound edge, performing an action involving inclusion of the entity for the event. The inbound edge is generated via an inbound edge generator machine learning model configured to: traverse entity and/or inclusion edges of the graph representation data object to identify inclusion and entity edges connected, generate an entity score data object for the entity based at least in part on the inclusion edges, and responsive to the data object satisfying a threshold, generate the inbound edge.

traducir

DATA PROCESSING METHOD AND APPARATUS, AND NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM

NºPublicación: US2022245472A1 04/08/2022

Solicitante:

JINGDONG CITY BEWING DIGITS TECH LTD [CN]

EP_3971798_PA

Resumen de: US2022245472A1

The present disclosure relates to a data processing method and apparatus and non-transitory computer-readable storage medium, and relates to the field of computer technology. The method includes: combining original data from a plurality of data platforms to create a training data set, according to an overlap condition between the original data from different data platforms; classifying data in the training data set to obtain a plurality of data subsets, according to attributes of the data in the training data set determining a machine learning model corresponding to each data subset, according to a type of the each data subset and sending the each data subset and its corresponding machine learning model to each of a plurality of data platforms.

traducir

Decision Making Using Integrated Machine Learning Models and Knowledge Graphs

NºPublicación: US2022245469A1 04/08/2022

Solicitante:

BANK OF AMERICA [US]

Resumen de: US2022245469A1

Aspects of the disclosure relate to machine learning models and knowledge graphs. A computing platform may receive event processing data. Using a machine learning mode, the computing platform may identify k nearest data points corresponding to the event processing data. Using a knowledge graph, the computing platform may identify k nearest data nodes corresponding to the event processing data. The computing platform may generate first weighted relative distances between the event processing data and the k nearest data points, and second weighted relative distances between the event processing data and the k nearest data nodes. Based on the weighted relative distances, the computing platform may identify a data cluster for the event processing data. The computing platform may send, based on the identified data cluster, event processing information and one or more commands directing an enterprise computing device to display the event processing information.

traducir

Machine learning-based malware detection system and method

NºPublicación: US2022245248A1 04/08/2022

Solicitante:

ZSCALER INC [US]

US_2021026962_A1

Resumen de: US2022245248A1

Disclosed is a computer implemented method for malware detection that analyses a file on a per packet basis. The method receives a packet of one or more packets associated a file, and converting a binary content associated with the packet into a digital representation and tokenizing plain text content associated with the packet. The method extracts one or more n-gram features, an entropy feature, and a domain feature from the converted content of the packet and applies a trained machine learning model to the one or more features extracted from the packet. The output of the machine learning method is a probability of maliciousness associated with the received packet. If the probability of maliciousness is above a threshold value, the method determines that the file associated with the received packet is malicious.

traducir

SECURING MACHINE LEARNING MODELS AGAINST ADVERSARIAL SAMPLES THROUGH MODEL POISONING

NºPublicación: US2022245243A1 04/08/2022

Solicitante:

NEC LABORATORIES EUROPE GMBH [DE]

Resumen de: US2022245243A1

A method for securing a genuine machine learning model against adversarial samples includes receiving a sample, as well as receiving a classification of the sample using the genuine machine learning model or classifying the sample using the genuine machine learning model. The sample is classified using a plurality of backdoored models, which are each a backdoored version of the genuine machine learning model. The classification of the sample using the genuine machine learning model is compared to each of the classifications of the sample using the backdoored models to determine a number of the backdoored models outputting a different class than the genuine machine learning model. The number of the backdoored models outputting a different class than the genuine machine learning model is compared against a predetermined threshold so as to determine whether the sample is an adversarial sample.

traducir

MODULAR SYSTEMS AND METHODS FOR SELECTIVELY ENABLING CLOUD-BASED ASSISTIVE TECHNOLOGIES

NºPublicación: US2022245327A1 04/08/2022

Solicitante:

AUDIOEYE INC [US]

US_2021165950_A1

Resumen de: US2022245327A1

Systems and methods are disclosed for manually and programmatically remediating websites to thereby facilitate website navigation by people with diverse abilities. For example, an administrator portal is provided for simplified, form-based creation and deployment of remediation code, and a machine learning system is utilized to create and suggest remediations based on past remediation history. Voice command systems and portable document format (PDF) remediation techniques are also provided for improving the accessibility of such websites.

traducir

USAGE RESTRICTIONS FOR DIGITAL CERTIFICATES

NºPublicación: US2022247575A1 04/08/2022

Solicitante:

IBM [US]

Resumen de: US2022247575A1

A method, a computer program product, and a system for usage restrictions on digital certificates. The method includes selecting a digital certificate relating to a user and determining a usage restriction policy for the digital certificate based on the user. The method also includes populating an extension field of the digital certificate with the usage restriction policy. The method further includes providing the digital certificate including the usage restriction policy to the user. The method also includes gathering parameters relating to the digital certificate, determining usage patterns based on the parameters, inputting the usage patterns into a machine learning model, outputting a risk assessment, and updating the usage restriction policy based on the risk assessment.

traducir

DEVICES AND METHODS FOR MACHINE LEARNING ASSISTED SPHERE DECODING

NºPublicación: US2022247605A1 04/08/2022

Solicitante:

INST MINES TELECOM [FR]

KR_20220027966_PA

Resumen de: US2022247605A1

A decoder for decoding a signal received through a transmission channel represented by a channel matrix using a search sphere radius. The decoder comprises a radius determination device for determining a search sphere radius from a preliminary radius. The radius determination device is configured to: i. apply a machine learning algorithm to input data derived from the received signal, the channel matrix and a current radius, the current radius being initially set to the preliminary radius, which provides a current predicted number of lattice points associated with the current radius; ii. compare the current predicted number of lattice points to a given threshold; iii. update the current radius if the current predicted number of lattice points is strictly higher than the given threshold, the current radius being updated by applying a linear function to the current radius; Steps i to iii are iterated until a termination condition is satisfied, the termination condition being related to the current predicted number, the radius determination device being configured to set the search sphere radius to the current radius in response to the termination condition being satisfied.

traducir

SYSTEMS AND METHODS FOR GENERATING BASKET AND ITEM QUANTITY PREDICTIONS USING MACHINE LEARNING ARCHITECTURES

NºPublicación: US2022245707A1 04/08/2022

Solicitante:

WALMART APOLLO LLC [US]

Resumen de: US2022245707A1

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of: generating a feature vector for a user based, at least in part, on historical data pertaining to the user's previous transactions; generating, using a quantity prediction model of a machine learning architecture, a respective item quantity prediction for each of one or more items included in a predicted basket based, at least in part, on the feature vector for the user; and populating a respective quantity selection option for each of the one or more items included in the predicted basket based on the respective item quantity prediction generated for each of the one or more items. Other embodiments are disclosed herein.

traducir

TECHNIQUES FOR ADAPTIVE QUANTIZATION LEVEL SELECTION IN FEDERATED LEARNING

NºPublicación: US2022245527A1 04/08/2022

Solicitante:

QUALCOMM INC [US]

Resumen de: US2022245527A1

Methods, systems, and devices for wireless communications are described. To support adaptive quantization level selection in federated learning, a server may cause a base station to transmit an indication of a quantization level for a user equipment (UE) to use to compress gradient data output by a machine learning model. For example, the server may determine, for each UE of a set of UEs, a respective quantization level for respective gradient data that is output by a respective machine learning model at each UE. The server may transmit, to each UE via one or more base stations, first information for use as an input in the respective machine learning model and an indication of the respective quantization level. A UE may receive the first information and the indication and may transmit, to the server, compressed gradient data that is generated based on (e.g., using) the indicated quantization level.

traducir

SYSTEMS AND METHODS FOR GENERATING TIME SLOT PREDICTIONS AND REPURCHASE PREDICTIONS USING MACHINE LEARNING ARCHITECTURES

NºPublicación: US2022245530A1 04/08/2022

Solicitante:

WALMART APOLLO LLC [US]

Resumen de: US2022245530A1

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform functions comprising: generating one or more feature vectors for a user, the one or more feature vectors at least comprising transaction-based features and slot-based features; generating, using a machine learning architecture, a repurchase prediction for the user based, at least in part, on the one or more feature vectors; generating, using the machine learning architecture, a time slot prediction for the user based, at least in part, on the one or more feature vectors, the time slot prediction predicting a time slot desired by the user for an upcoming transaction; and executing a reservation function that facilitates reserving of the time slot for the user. Other embodiments are disclosed herein.

traducir

DISTRIBUTED MACHINE LEARNING FOR IMPROVED PRIVACY

NºPublicación: US2022245524A1 04/08/2022

Solicitante:

SNAP INC [US]

US_11341429_B1

Resumen de: US2022245524A1

Methods, computer readable media, devices, and systems provide for distributed machine learning. In one aspect, a method of training a model is disclosed. The method includes receiving, by a client device, from one or more servers, an intermediate model, training, by the client device, the intermediate model based on private data, and transmitting, by the client device, to the one or more servers, the trained intermediate model.

traducir

MACHINE LEARNING APPROACH TO MULTI-DOMAIN PROCESS AUTOMATION AND USER FEEDBACK INTEGRATION

NºPublicación: US2022245511A1 04/08/2022

Solicitante:

SISCALE AI INC [US]

Resumen de: US2022245511A1

Embodiments relate to multi-domain process automation with user feedback integration. Some embodiments include a method performed by one or more computing devices. The one or more computing devices generate, using a machine learning (ML) model, predictions for records. The one or more computing devices receive at least one of single user feedback or multiple user feedback for the predictions. The one or more computing devices generate a user validated record pool based on the single user feedback or multiple user feedback. The one or more computing devices update the ML model using the user validated record pool.

traducir

ARTIFICIAL INTELLIGENCE BASED CONFIGURE PRICE QUOTE RECOMMENDATION SYSTEM

NºPublicación: US2022245484A1 04/08/2022

Solicitante:

ORACLE INT CORP [US]

Resumen de: US2022245484A1

Techniques for suggesting a candidate layout based on historical characteristics are disclosed. A system trains a machine learning model to suggest layouts for three-dimensional spaces. The system obtains sets of historical characteristic data, including spatial characteristics of a particular three-dimensional space and layout characteristics including information indicating items present in the particular three-dimensional space and positioning information indicating a position of each item within the particular three-dimensional space. The system trains the machine learning model based on the sets of historical characteristic data. The system receives a first request for a layout suggestion from a first user, including at least a first set of spatial characteristics for a first three-dimensional space. The system applies the machine learning model to the first set of spatial characteristics to identify a first candidate layout as a suggestion and, based on the applying operation: recommends the first candidate layout as a layout suggestion.

traducir

SELF-SUPERVISED SEMANTIC SHIFT DETECTION AND ALIGNMENT

NºPublicación: US2022245348A1 04/08/2022

Solicitante:

IBM [US]
RENSSELAER POLYTECH INST [US]

Resumen de: US2022245348A1

Generate, for each of the words of a common vocabulary of first and second text corpora, a first word embedding vector in the first text corpus and a second word embedding vector in the second text corpus. Generate, for each word in a random sample of non-landmark words, an artificially shifted word embedding vector by modifying the first word embedding vector for that word. Train a machine learning classifier to predict whether an artificial shift has been injected for a given word, based on the artificially shifted word embedding vector and the second word embedding vector for the given word. Predict semantic shifts for at least a plurality of the words of the common vocabulary by providing the first word embedding vectors and the second word embedding vectors for at least the plurality of the words of the common vocabulary as input to the trained machine learning classifier.

traducir

CONFIGURING AN INSTANCE OF A SOFTWARE PROGRAM USING MACHINE LEARNING

NºPublicación: WO2022165168A1 04/08/2022

Solicitante:

SPLUNK INC [US]

US_2022244934_A1

Resumen de: WO2022165168A1

Disclosed are embodiments of a system for receiving, from a product management system, a model trained to select one state from a set of predefined states based on a state of an installation of a software program on a computing device. Each of the predefined states are associated with a configuration of the software program and each configuration of the software program are associated with operational parameter values of the software program. The system further determines a state of the installation of the software program, inputs the determined state into the model, obtains, from the model, and based on the determined state, the selection of the one state from the set of predefined states. Finally, the system adjusts a parameter of the software program according to the selected one predefined state.

traducir

ENTITY SELECTION METRICS

NºPublicación: WO2022162343A1 04/08/2022

Solicitante:

BENEVOLENTAI TECH LIMITED [GB]

Resumen de: WO2022162343A1

Embodiments of present disclosure provide a system, apparatus and method(s) for generating a set of metrics for evaluating entities used with a predictive machine learning model, the method comprising: selecting one or more sets of entities from a data sources for generating a plurality of predictions aggregated from said one or more sets of entities using one or more pre-trained predictive models; selecting a subset of predictions from the plurality of predictions based on said one or more sets of entities in relation to the data source; extracting metadata from the data source associated with the subset of predictions, where the metadata comprises entity metadata and predicted metadata; generating the set of metrics based on the metadata extracted and the subset of predictions; and outputting the set of metrics for evaluation.

traducir

METHOD AND APPARATUS FOR SELECTING MACHINE LEARNING MODEL FOR EXECUTION IN A RESOURCE CONSTRAINT ENVIRONMENT

NºPublicación: WO2022161644A1 04/08/2022

Solicitante:

ERICSSON TELEFON AB L M [SE]

Resumen de: WO2022161644A1

Embodiments herein disclose a method for selecting a machine learning model to be deployed in an execution environment having resource constraints. The method comprises receiving, by an apparatus, a request for a machine learning model solving a task T using a feature set F. Further, the method includes retrieving, from a model store, a first set of machine learning models that solves the task T using at least a subset of features F. The complexity of each machine learning model in the first set of machine learning models is calculated. The method includes determining, from the first set of machine learning models, at least one suitable machine learning model to be deployed, wherein the determining is based on the calculated complexity and the resource constraints of the execution environment.

traducir

SYSTEM AND COMPUTER-IMPLEMENTED METHOD FOR VALIDATION OF LABEL DATA

NºPublicación: WO2022164491A1 04/08/2022

Solicitante:

UIPATH INC [US]

US_2022237800_A1

Resumen de: WO2022164491A1

A system and a computer-implemented method for validating label data includes receiving the label data and segmenting it into one or more parts using a first machine learning model. Further, from the segmented label data a first plurality of attributes, including text and images, are extracted. The method further includes receiving ground truth data associated with the label data and extracting a second plurality of attributes from the ground truth data. The first and second plurality of attributes are then compared using a second machine learning model and the result of comparison are displayed on a three pane user interface. Further, the label data is validated based on the displayed results.

traducir

DISTRIBUTED MACHINE LEARNING WITH NEW LABELS USING HETEROGENEOUS LABEL DISTRIBUTION

NºPublicación: WO2022162677A1 04/08/2022

Solicitante:

ERICSSON TELEFON AB L M [SE]
GAUTHAM KRISHNA GUDUR [IN]

Resumen de: WO2022162677A1

A method for distributed machine learning (ML) which includes providing a first dataset including a first set of labels to a plurality of local computing devices including a first local computing device and a second local computing device. The method further includes receiving, from the first local computing device, a first set of ML model probabilities values from training a first local ML model using the first set of labels. The method further includes receiving, from the second local computing device, a second set of ML model probabilities values from training a second local ML model using the first set of labels and one or more labels different from any label in the first set of labels. The method further includes generating a weights matrix using the received first set of ML model probabilities values and the received second set of ML model probabilities values. The method further includes generating a third set of ML model probabilities values by sampling using the generated weights matrix.

traducir

METHOD & APPARATUS FOR DETERMINING AND/OR PREDICTING SLEEP AND RESPIRATORY BEHAVIOURS FOR MANAGEMENT OF AIRWAY PRESSURE

NºPublicación: US2022241530A1 04/08/2022

Solicitante:

NOVARESP TECH INC [CA]

WO_2021168588_A1

Resumen de: US2022241530A1

Devices, systems and methods are provided for controlling the operation of a breathing assistance device for a user. The controller may include an input for receiving sensor data to measure at least one airflow parameter of the user's airflow; a memory unit that stores at least one machine learning model and at least one classifier or predictor; and a processor that is configured to perform measurements and to generate a control signal for adjusting the operation of the breathing assistance device for a current monitoring time period by: obtaining measured air pressure and/or airflow data and measured FOT data during a current monitoring time period; performing feature extraction on the measured data to obtain feature values that are used by the machine learning model employed by the at least one classifier or predictor to determine a property of the user; and adjusting the control signal based on the determined property.

traducir

DEVICES AND METHODS FOR MACHINE LEARNING ASSISTED PRECODING

Nº publicación: US2022247460A1 04/08/2022

Solicitante:

INST MINES TELECOM [FR]

KR_20220031624_PA

Resumen de: US2022247460A1

A precoder for precoding a vector of information symbols is provided. The precoder includes a radius determination unit configured to determine a search sphere radius, the determination of the search sphere radius comprising applying a machine learning algorithm to input data dependent on the vector of information symbols and on a predefined precoding matrix; a sphere encoding unit configured to determine a perturbation vector from lattice points found inside a spherical region by applying a sphere search-based sequential algorithm, the spherical region having as a radius the search sphere radius, and a precoding unit configured to precode the vector of information symbols using the perturbation vector and a precoding matrix.

traducir

Página1 de 3 nextPage por página

punteroimgVolver