MACHINE LEARNING

VolverVolver

Resultados 114 resultados LastUpdate Última actualización 27/05/2020 [01:26:00] pdf PDF xls XLS

Solicitudes publicadas en los últimos 60 días / Applications published in the last 60 days



Página1 de 5 nextPage   por página


High recall additive pattern recognition for image and other applications

NºPublicación: US2020160035A1 21/05/2020

Solicitante:

SHUTTERFLY LLC [US]

US_2019244009_A1

Resumen de: US2020160035A1

A computer-implemented method includes selecting a kernel and kernel parameters for a first Support Vector Machine (SVM) model, testing the first SVM model on a feature matrix T of n feature vectors of length m to produce false positive (FP) data set and false negative (FN) data set by a computer processor, wherein n and m are integer numbers, automatically removing feature vectors corresponding to the FP data set from the feature matrix T by the computer processor to produce a feature matrix T_best, retraining the first SVM model on the feature matrix T_best to produce a second SVM model, and checking if a ratio (T_best sample number)/(SVM support vector number) is above a threshold for the second SVM model on T_best. If the ratio is above the threshold, SVM predictions are performed using the second SVM model on the feature matrix T_best.

traducir

INTENT-ORIENTED INTERNET BROWSING

NºPublicación: US2020159790A1 21/05/2020

Solicitante:

BARBOSA NATA [BR]
WANG YANG [US]
UNIV SYRACUSE [US]

Resumen de: US2020159790A1

A system that provides intent-oriented browsing powered by machine learning and crowdsourcing. The system allows users to enter their intents, which are then assigned to target pages via supervised learning models based on hyperlinks and contributions made by other users. The system has a prediction server that is programmed to receive hyperlinks from a website and return target hyperlinks based on known intent, a user interface for inputting user intent, and a browser programmed to connect to the intent repository and to the prediction server via a user script. The list of supported intents can grow over time based on correct page marks for intent-page mappings as well as via continuous training of machine learning models.

traducir

MACHINE LEARNING CLASSIFICATION AND PREDICTION SYSTEM

NºPublicación: AU2020202909A1 21/05/2020

Solicitante:

ACCENTURE GLOBAL SOLUTIONS LTD [IE]

AU_2018271385_A1

Resumen de: AU2020202909A1

A machine learning and predictive analytics system, including one or more data stores to store and manage data within a network, one or more servers to facilitate operations using information from the one or more data stores, and a processing system using machine learning and predictive analytics, the processing system including a data access interface to receive data associated with a subject, wherein the data is received from a data source including an internal data source and an external data source, wherein the internal data source includes a financial database of a financial institution associated with the subject, and the external data source includes a public database and a web feed associated with the subject, the public database associated with a census database and including population data, and the web feed including data from social media, RSS, syndication, aggregators, and web scraping, and a processor to execute machine-readable instructions stored on at least one non-transitory computer readable medium, the processor analyzing, based on a clustering technique, the data associated with the subject to predict a future life event, the clustering technique including at least one of agglomerative hierarchical clustering, Bayesian hierarchical clustering, K-means clustering, mean-shift clustering, density-based special clustering of applications with noise (DBSCAN), expectation-maximization (EM) based clustering or Gaussian Mixture Model (GMM) based clustering, calcu

traducir

METHOD AND SYSTEM FOR IMPLEMENTING A CLOUD MACHINE LEARNING ENVIRONMENT

NºPublicación: US2020151346A1 14/05/2020

Solicitante:

JPMORGAN CHASE BANK NA [US]

Resumen de: US2020151346A1

An embodiment of the present invention is directed to leveraging GPU farms for machine learning where the selection of data is self-service. The data may be cleansed based on a classification and automatically transferred to a cloud services platform. This allows an entity to leverage the commoditization of the GPU farms in the public cloud without exposing data into that cloud. Also, an entire creation of a ML instance may be fully managed by a business analyst, data scientist and/or other users and teams.

traducir

SYSTEMS AND METHODS FOR IMPLEMENTING AN INTELLIGENT APPLICATION PROGRAM INTERFACE FOR AN INTELLIGENT OPTIMIZATION PLATFORM

NºPublicación: US2020151029A1 14/05/2020

Solicitante:

SIGOPT INC [US]

US_2019391859_A1

Resumen de: US2020151029A1

Systems and methods for implementing an application programming interface (API) that controls operations of a machine learning tuning service for tuning a machine learning model for improved accuracy and computational performance includes an API that is in control communication the tuning service that: executes a first API call function that includes an optimization work request that sets tuning parameters for tuning hyperparameters of a machine learning model; and initializes an operation of distinct tuning worker instances of the service that each execute distinct tuning tasks for tuning the hyperparameters; executes a second API call function that identifies raw values for the hyperparameters; and generates suggestions comprising proposed hyperparameter values selected from the plurality of raw values for each of the hyperparameters; and executes a third API call function that returns performance metrics relating to a real-world performance of the subscriber machine learning model executed with the proposed hyperparameter values.

traducir

SYSTEM AND METHOD FOR IMPLEMENTING AN ARTIFICIALLY INTELLIGENT VIRTUAL ASSISTANT USING MACHINE LEARNING

NºPublicación: US2020151566A1 14/05/2020

Solicitante:

CLINC INC [US]

US_2019156198_PA

Resumen de: US2020151566A1

Systems and methods for implementing an artificially intelligent virtual assistant includes collecting a user query; using a competency classification machine learning model to generate a competency label for the user query; using a slot identification machine learning model to segment the text of the query and label each of the slots of the query; generating a slot value for each of the slots of the query; generating a handler for each of the slot values; and using the slot values to: identify an external data source relevant to the user query, fetch user data from the external data source, and apply one or more operations to the query to generate response data; and using the response data, to generate a response to the user query.

traducir

ANALYZING VIEWER BEHAVIOR IN REAL TIME

NºPublicación: US2020151587A1 14/05/2020

Solicitante:

DISNEY ENTPR INC [US]

EP_3654655_A1

Resumen de: US2020151587A1

Systems, methods and articles of manufacture for are provided for analyzing user behavior in real time by ingesting telemetry data related to a streaming media application; feeding the telemetry data to a machine learning model (MLM) that produces a User Experience (UX) command based on the telemetry data and prior telemetry data received from the content streaming application; selecting content items to provide to the client device based on the telemetry data; determining, based on the telemetry data, whether the client device has sufficient free resources to receive the UX command and the content items in a current time window while providing a predefined level of service; when client device has sufficient free resources to receive the UX command and the content items, encapsulating the UX command with the content items in a content stream; and transmitting the content stream to the client device.

traducir

Applied Artificial Intelligence Technology for Processing Trade Data to Detect Patterns Indicative of Potential Trade Spoofing

NºPublicación: US2020151565A1 14/05/2020

Solicitante:

TRADING TECHNOLOGIES INT INC [US]

US_10552735_B1

Resumen de: US2020151565A1

Various techniques are described for using machine-learning artificial intelligence to improve how trading data can be processed to detect improper trading behaviors such as trade spoofing. In an example embodiment, semi-supervised machine learning is applied to positively labeled and unlabeled training data to develop a classification model that distinguishes between trading behavior likely to qualify as trade spoofing and trading behavior not likely to qualify as trade spoofing. Also, clustering techniques can be employed to segment larger sets of training data and trading data into bursts of trading activities that are to be assessed for potential trade spoofing status.

traducir

INFORMATION EXTRACTION FROM DOCUMENTS

NºPublicación: US2020151591A1 14/05/2020

Solicitante:

MOCSY INC [CA]

CA_3052113_A1

Resumen de: US2020151591A1

There is provided a method including sending a first document to a GUI, and receiving at a classification and extraction engine (CEE) from the GUI an input indicating first document data for the first document. The input forms a portion of a dataset. A prediction is generated at the CEE of second document data for a second document using a machine learning model (MLM) configured to receive an input and generate a predicted output. The MLM is trained using the dataset, the input includes one or more tokens corresponding to the second document. The output includes the prediction of the second document data. The prediction is sent to the GUI, and feedback on the prediction is received at the CEE from the GUI, to form a reviewed prediction. The reviewed prediction is added to the dataset to form an enlarged dataset, and the MLM is trained using the enlarged dataset.

traducir

AUTOMATED TRAINING AND EXERCISE ADJUSTMENTS BASED ON SENSOR-DETECTED EXERCISE FORM AND PHYSIOLOGICAL ACTIVATION

NºPublicación: US2020151595A1 14/05/2020

Solicitante:

MAD APPAREL INC [US]

Resumen de: US2020151595A1

The invention(s) described are configured to process sensor data in order to optimize or otherwise improve training of users for achievement of goals in relation to performing an activity. The invention(s) can also iteratively adapt training in a personalized manner, with assessment of training results and subsequent modification of training regimens, in order to provide improved alignment between users and their goals. Such iteration can drive interventions provided to users throughout the course of training, and allow the system to iteratively develop better and more precise interventions (e.g., through manual means, through machine learning models with generated training and test data). Such iteration, with large datasets applied to populations of users can also increase the breadth of user states that the can be addressed, with respect to provided interventions, and improve rates at which interventions are provided.

traducir

CONTEXT-DEPENDENT TIMEOUT FOR REMOTE SECURITY SERVICES

NºPublicación: US2020153849A1 14/05/2020

Solicitante:

SOPHOS LTD [GB]

US_2019342312_PA

Resumen de: US2020153849A1

A threat management facility that remotely stores global reputation information for network content can be used in combination with a recognition engine such as a machine learning classifier that is locally deployed on endpoints within an enterprise network. More specifically, the recognition engine can locally evaluate reputation for a network address being accessed by an endpoint, and this reputation information can be used to dynamically establish a timeout for a request from the endpoint to the threat management facility for corresponding global reputation information.

traducir

DETECTING A TRANSACTION VOLUME ANOMALY

NºPublicación: US2020151728A1 14/05/2020

Solicitante:

CAPITAL ONE SERVICES LLC [US]

US_10445738_B1

Resumen de: US2020151728A1

A server device obtains historical transaction data regarding transactions involving a network service, obtains historical calendar data regarding static date information for a historical time period that corresponds with the historical transaction data, and processes the historical transaction data and historical calendar data to train a machine learning model using a gradient boosting machine learning technique to predict a normal transaction volume for a period of time and confidence bands associated with the normal transaction volume. The server device generates the normal transaction volume for the period of time and confidence bands using the machine learning model, obtains real-time data concerning a transaction volume during the period of time, detects a transaction volume anomaly based on comparing the real-time data and normal transaction volume and confidence bands, and sends an alert, based on the transaction volume anomaly, to cause a remote device to display the alert and perform an action.

traducir

Automated Extraction, Inference and Normalization of Structured Attributes for Product Data

NºPublicación: US2020151201A1 14/05/2020

Solicitante:

SEMANTICS3 INC [US]

Resumen de: US2020151201A1

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for automated extraction, inference and normalization of structured attributes for a Product Category Normalizer to access product records from external data sources. The Product Category Normalizer defines a product-description taxonomy of product categories represented by a classification tree. The Product Category Normalizer employs product attribute data and machine learning techniques to analyze the product data of an input product record. Based on the product data of the input product record, the Product Category Normalizer extracts and infers appropriate product data for a relevant product category in the classification tree for the item described by the input product record. The Product Category Normalizer normalizes the product data of the input product record. The Product Category Normalizer provides an output normalized product record related to a product category and product attributes of the classification tree.

traducir

METHOD AND APPARATUS FOR DETERMINING INFORMATION RELATED TO A LANE CHANGE OF A TARGET VEHICLE, METHOD AND APPARATUS FOR DETERMINING A VEHICLE COMFORT METRIC FOR A PREDICTION OF A DRIVING MANEUVER OF A TARGET VEHICLE AND COMPUTER PROGRAM

NºPublicación: WO2020094264A1 14/05/2020

Solicitante:

BAYERISCHE MOTOREN WERKE AG [DE]

EP_3650297_A1

Resumen de: WO2020094264A1

Embodiments relate to a method and an apparatus for determining information related to a lane change of a target vehicle, to a method and an apparatus for determining a vehicle comfort metric for a prediction of a driving maneuver of a target vehicle, and to a computer program, The method for determining information related to a lane change of a target vehicle comprises obtaining ( 1 10) information related to an environment of the target vehicle. The information related to the environment relates to a plurality of features of the environment of the target vehicle. The plurality of features are partitioned into two or more groups of features. The method further comprises determining ( 120) two or more weighting factors for the two or more groups of features. An attention mechanism is used for determining the two or more weighting factors. The method further comprises determining ( 130) the information related to the lane change of the target vehicle based on the information related to the environment of the target vehicle using a machine-learning network. A weighting of the plurality of features of the environment of the target vehicle within the machine-learning network is based on the two or more weighting factors for the two or more groups of features.

traducir

MACHINE LEARNING-BASED PREDICTION, PLANNING, AND OPTIMIZATION OF TRIP TIME, TRIP COST, AND/OR POLLUTANT EMISSION DURING NAVIGATION

NºPublicación: US2020151291A1 14/05/2020

Solicitante:

IOCURRENTS INC [US]

WO_2020097562_A1

Resumen de: US2020151291A1

A method of predicting, in real-time, a relationship between a vehicle's engine speed, trip time, cost, and fuel consumption, comprising: monitoring vehicle operation over time to acquiring data representing at least a vehicle location, a fuel consumption rate, and operating conditions; generating a predictive model relating the vehicle's engine speed, trip time, and fuel consumption; and receiving at least one constraint on the vehicle's engine speed, trip time, and fuel consumption, and automatically producing from at least one automated processor, based on the predictive model, a constrained output.

traducir

METHODS AND SYSTEMS FOR DATA COLLECTION, LEARNING, AND STREAMING OF MACHINE SIGNALS FOR ANALYTICS AND MAINTENANCE USING THE INDUSTRIAL INTERNET OF THINGS

NºPublicación: US2020150643A1 14/05/2020

Solicitante:

STRONG FORCE IOT PORTFOLIO 2016 LLC [US]

US_2020150644_A1

Resumen de: US2020150643A1

An industrial machine predictive maintenance system may include an industrial machine data analysis facility that generates streams of industrial machine health monitoring data by applying machine learning to data representative of conditions of portions of industrial machines received via a data collection network. The system may include an industrial machine predictive maintenance facility that produces industrial machine service recommendations responsive to the health monitoring data by applying machine fault detection and classification algorithms thereto. The system may perform a method of predicting a service event from vibration data captured data from at least one vibration sensor disposed to capture vibration of a portion of an industrial machine. A signal in a predictive maintenance circuit for executing a maintenance action on the portion of the industrial machine can be generated based on a severity unit calculated for the captured vibration.

traducir

MERGING FEATURE SUBSETS USING GRAPHICAL REPRESENTATION

NºPublicación: US2020151608A1 14/05/2020

Solicitante:

IBM [US]

US_2017286866_A1

Resumen de: US2020151608A1

A system, method and computer program product provides improved performance in machine learning, decision making and similar processes. In one example method, a plurality of individual subsets of features of a dataset comprising multiple features are received. The subsets may be provided by applying one or more feature selection methods to the dataset. Each subset is represented as a graph based on a predefined graph template. The example method merges the graphs of the plurality of individual subsets by overlaying the graphs on each other to form a merged feature graph. The merged feature graph may be used for identifying a single subset of features for use in machine learning, decision making and similar processes.

traducir

MACHINE LEARNING BASED DISCOVERY OF SOFTWARE AS A SERVICE

NºPublicación: US2020153703A1 14/05/2020

Solicitante:

SERVICENOW INC [US]

EP_3651014_A1

Resumen de: US2020153703A1

An example embodiment involves receiving an activity record including activity data, provider data, and description data; applying a first layer of a multi-layer machine learning (ML) model to predict that the activity record relates to software, applying a second layer of the multi-layer ML model to predict a provider name of a software application referenced in the activity record, applying a third layer of the multi-layer ML model to predict an application title of the software application referenced in the activity record, and storing, in a database, a configuration item indicating that the activity record relates to software, where the configuration item contains attributes including the provider name and the application title.

traducir

MACHINE LEARNING BASED DISCOVERY OF SOFTWARE AS A SERVICE

NºPublicación: EP3651014A1 13/05/2020

Solicitante:

SERVICENOW INC [US]

US_2020153703_A1

Resumen de: EP3651014A1

An example embodiment involves receiving an activity record including activity data, provider data, and description data; applying a first layer of a multi-layer machine learning (ML) model to predict that the activity record relates to software, applying a second layer of the multi-layer ML model to predict a provider name of a software application referenced in the activity record, applying a third layer of the multi-layer ML model to predict an application title of the software application referenced in the activity record, and storing, in a database, a configuration item indicating that the activity record relates to software, where the configuration item contains attributes including the provider name and the application title.

traducir

MACHINE LEARNING BASED DISCOVERY OF SOFTWARE AS A SERVICE

NºPublicación: CA3061065A1 09/05/2020

Solicitante:

SERVICENOW INC [US]

US_2020153703_A1

Resumen de: CA3061065A1

An example embodiment involves receiving an activity record including activity data, provider data, and description data; applying a first layer of a multi-layer machine learning (ML) model to predict that the activity record relates to software, applying a second layer of the multi-layer ML model to predict a provider name of a software application referenced in the activity record, applying a third layer of the multi-layer ML model to predict an application title of the software application referenced in the activity record, and storing, in a database, a configuration item indicating that the activity record relates to software, where the configuration item contains attributes including the provider name and the application title.

traducir

DEEP LEARNING BASED CACHING SYSTEM AND METHOD FOR SELF-DRIVING CAR IN MULTI-ACCESS EDGE COMPUTING

NºPublicación: US2020145699A1 07/05/2020

Solicitante:

UNIV INDUSTRY COOPERATION GROUP KYUNG HEE UNIV [KR]

EP_3648435_A1

Resumen de: US2020145699A1

A caching system based on the invention can include an object requiring a content and an MEC server configured to determine caching contents based on a first prediction value, which may include the probability of the content being requested by the object within an allotted area and a prediction rating of the content, and download and cache the determined caching contents from a content provider. The object can include a recommendation module configured to recommend a content from among the caching contents by applying a k-means algorithm and binary classification to the first prediction value and a second prediction value, which may include a prediction value associated with a characteristic of a user, and a deep learning based caching module configured to search available MEC servers on a movement path of the object, select an optimal MEC server, and download and cache the recommended content from the optimal MEC server.

traducir

ELECTRONIC APPARATUS AND CONTROL METHOD THEREOF

NºPublicación: US2020143809A1 07/05/2020

Solicitante:

SAMSUNG ELECTRONICS CO LTD [KR]

WO_2020091503_A1

Resumen de: US2020143809A1

An electronic apparatus and a control method thereof are provided. A method of controlling an electronic apparatus according to an embodiment of the disclosure includes: receiving input of a first utterance, identifying a first task for the first utterance based on the first utterance, providing a response to the first task based on a predetermined response pattern, receiving input of a second utterance, identifying a second task for the second utterance based on the second utterance, determining the degree of association between the first task and the second task, and setting a response pattern for the first task based on the second task based on the determined degree of association satisfying a predetermined condition. The control method of an electronic apparatus may use an artificial intelligence model trained according to at least one of machine learning, a neural network, or a deep learning algorithm.

traducir

COMPUTER VISION BASED METHODS AND SYSTEMS OF UNIVERSAL FASHION ONTOLOGY FASHION RATING AND RECOMMENDATION

NºPublicación: US2020143454A1 07/05/2020

Solicitante:

ANANTHANARAYANA RAJESH KUMAR SALIGRAMA [IN]
MANTHANI SRIDHAR [IN]

Resumen de: US2020143454A1

In one aspect, a computerized method of computer vision based dynamic universal fashion ontology fashion rating and recommendations includes the step of receiving one or more user-uploaded digital images. The method includes the step of implementing an image classifier on the one or more user-uploaded digital images, to classify a set of user-uploaded fashion content of the one or more user-upload digital images. The method includes the step of receiving a set of fashion rules input by a domain expert. The set of rules determine a set of apparel to match with the set of user-uploaded fashion content, generating a dynamic universal fashion ontology with the image classier and a text classier. The dynamic universal fashion ontology comprises an ontology of set of mutually exclusive attribute classes. The method includes the step of using the dynamic universal fashion ontology to train a specified machine learning based fashion classifications. The method includes the step of using an active learning pipeline to keep the universal fashion ontology up-to-date. The method includes the step of using graphical representation and game theory-based algorithm for outfit generation. The method includes the step of providing an automatic outfit generator, wherein the automatic outfit generator: based on the set of user-uploaded fashion content that is output by the image classifier, matches the set of user-uploaded fashion with a ranked set of apparel suggestions that are based on the se

traducir

METHOD AND APPARATUS FOR MONITORING A PATIENT

NºPublicación: WO2020089576A1 07/05/2020

Solicitante:

UNIV OXFORD INNOVATION LTD [GB]

Resumen de: WO2020089576A1

Methods and apparatus for monitoring a patient are provided. In one arrangement, a multi- dimensional patient data set is received at each of a plurality of different reference times. Each dimension of the patient data set stores a value representing a different type of information about the patient. A plurality of predictions of a health trajectory of the patient are generated. Each prediction is generated using a trained machine learning model receiving as input a different one of the patient data sets. The trained machine learning model may be dimensionally adaptive, such that predictions of the patient trajectories are provided using patient data sets having different respective dimensionalities for at least a sub-set of the reference times. The trained machine learning model may use machine learned predictions of accuracy to select trained machine learning units from an ensemble of trained machine learning units.

traducir

FLAME ANALYTICS SYSTEM

Nº publicación: US2020141653A1 07/05/2020

Solicitante:

HONEYWELL INT INC [US]

WO_2020092949_A1

Resumen de: US2020141653A1

A flame analytics system that may incorporate a burner, one or more sensors at the burner, a historical database connected to the one or more sensors, a model training module connected to the historical database, and a runtime algorithm module connected to the one or more sensors and the model training module. The runtime algorithm may compare realtime data from the one or more sensors and historical data from the model training module in accordance with a machine learning algorithm. The system may further incorporate a fault detection module connected to the runtime algorithm module, a fault diagnostics module connected to the fault detection module, and an enunciator connected to the fault detection module. The one or more sensors may also include having video or acoustic sensitivity of combustion in the burner.

traducir

Página1 de 5 nextPage por página

punteroimgVolver