Prediction Patents (Class 706/21)
  • Patent number: 11961013
    Abstract: Disclosed is an electronic apparatus. The electronic apparatus may include a memory configured to store one or more training data generation models and an artificial intelligence model, and a processor configured to generate personal training data that reflects a characteristic of a user using the one or more training data generation models, train the artificial intelligence model using the personal learning data as training data, and store the trained artificial intelligence model in the memory.
    Type: Grant
    Filed: July 8, 2020
    Date of Patent: April 16, 2024
    Assignee: SAMSUNG ELECTRONICS CO., LTD.
    Inventors: Chiyoun Park, Jaedeok Kim, Youngchul Sohn, Inkwon Choi
  • Patent number: 11960575
    Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
    Type: Grant
    Filed: October 27, 2022
    Date of Patent: April 16, 2024
    Assignee: Splunk Inc.
    Inventors: Manish Sainani, Sergey Slepian, Di Lu, Adam Oliner, Jacob Leverich, Iryna Vogler-Ivashchanka, Iman Makaremi
  • Patent number: 11941439
    Abstract: According to an embodiment, an information processing device is configured to assign a first computing device one or more first tasks of processing respective one or more first partial data of a plurality of partial data included in an n-dimensional target data, n being an integer greater than or equal to 2, the target data being to be processed using a neural network, the one or more first partial data including first data and second data adjacent to the first data in a direction of m-dimension, m being an integer satisfying 1?m?n; and instruct the first computing device to execute a second task included in the one or more first tasks, according to an execution status of second partial data of the plurality of partial data included in the target data, the second partial data being executed by the second computing device.
    Type: Grant
    Filed: August 27, 2021
    Date of Patent: March 26, 2024
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Ryota Tamura, Mizuki Ono, Masanori Furuta
  • Patent number: 11941513
    Abstract: Provided is a device for ensembling data received from prediction devices and a method of operating the same. The device includes a data manager, a learner, and a predictor. The data manager receives first and second device prediction results from first and second prediction devices, respectively. The learner may adjust a weight group of a prediction model for generating first and second item weights, first and second device weights, based on the first and second device prediction results. The first and second item weights depend on first and second item values, respectively, of the first and second device prediction results. The first device weight corresponds to the first prediction device, and the second device weight corresponds to the second prediction device. The predictor generates an ensemble result of the first and second device prediction results, based on the first and second item weights and the first and second device weights.
    Type: Grant
    Filed: November 28, 2019
    Date of Patent: March 26, 2024
    Assignee: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE
    Inventors: Myung-Eun Lim, Jae Hun Choi, Youngwoong Han
  • Patent number: 11930089
    Abstract: A highway detection system may include a telematics device associated with a vehicle having one or more sensors arranged therein, a mobile device associated with a user traveling in the vehicle, and a server computer. The server computer may receive traveling data for a trip of the user from the one or more sensors and via the telematics device. The server computer may then determine whether the user is traveling within a city or on a highway based on analysis of the traveling data for the trip of the user, which may include a statistical analysis to calculate standard deviations of metrics in the traveling data. In response to the determination, the server computer may generate a notification to transmit to the user based on whether the user is traveling within a city or on a highway and transmit the notification to the mobile device associated with the user.
    Type: Grant
    Filed: December 7, 2022
    Date of Patent: March 12, 2024
    Assignee: Allstate Solutions Private Limited
    Inventors: Rahul Kothari, Payal Patel, Anirudha S I
  • Patent number: 11926332
    Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a first probability distribution may be generated for the vehicle at a first future point in time using a generative model for predicting expected behaviors of objects and a set of characteristics for the vehicle at an initial time expected to be perceived by an observer. Planning system software of the vehicle may be used to generate a trajectory for the vehicle to follow. A second probability distribution may be generated for a second future point in time using the generative model based on the trajectory and a set of characteristics for the vehicle at the first future point expected to be perceived by the observer. A surprise assessment may be generated by comparing the first probability distribution to the second probability distribution. The vehicle may be controlled based on the surprise assessment.
    Type: Grant
    Filed: September 16, 2022
    Date of Patent: March 12, 2024
    Assignee: Waymo LLC
    Inventors: Johan Engstrom, Jared Russell
  • Patent number: 11928593
    Abstract: Among a great deal of other disclosure and scope, systems and methods are enclosed that enable for highly efficient labeling of data. For example, in some of many cases, a novel methodology for ranking vectors most useful to label next is disclosed. In such an example, a neural network is trained to predict this ranking methodology upon being given a set of heuristics from which to assess the given problem space. A user can continue the cycle of identifying a set of candidate vectors to label, compiling relevant heuristics from said vectors, ranking vectors via the trained neural network, selecting a subset of the ranked vectors, inquiring an oracle regarding the true labels of the vectors, and then appending the subset of newly labelled vectors to the labelled set of vectors until satisfaction.
    Type: Grant
    Filed: June 15, 2021
    Date of Patent: March 12, 2024
    Assignee: Fortinet, Inc.
    Inventor: Sameer T. Khanna
  • Patent number: 11916773
    Abstract: A system, method, and computer-readable medium for performing a data center management and monitoring operation. The data center management and monitoring operation includes: receiving data center data from a plurality of data center assets within a data center, the data center data comprising outlier data detection data; assigning the data center data to a vectorized input space; reducing a dimension of the vectorized input space to a latent space; decoding the latent space to provide a vectorized decoded output space; and, performing an outlier data detection operation using the vectorized decoded output space, wherein the outlier data detection operation is performed to detect data center asset outlier data.
    Type: Grant
    Filed: January 24, 2023
    Date of Patent: February 27, 2024
    Assignee: Dell Products L.P.
    Inventors: Raja Neogi, Khayam Anjam
  • Patent number: 11915387
    Abstract: Implementations relate to crop yield prediction at the field- and pixel-level. In various implementations, a first temporal sequence of high-elevation digital images may be obtained that capture a first geographic area and are acquired over a first predetermined time interval while the first geographic area includes a particular crop. A first plurality of other data points may also be obtained that influence a ground truth crop yield of the first geographic area after the first predetermined time interval. The first plurality of other data points may be grouped into temporal chunks corresponding temporally with respective images of the first temporal sequence. The first temporal sequence and the temporal chunks of the first plurality of other data points may be applied, e.g., iteratively, as input across a machine learning model to estimate a crop yield of the first geographic area at the end of the first predetermined time interval.
    Type: Grant
    Filed: April 21, 2023
    Date of Patent: February 27, 2024
    Assignee: MINERAL EARTH SCIENCES LLC
    Inventors: Cheng-en Guo, Wilson Zhao, Jie Yang, Zhiqiang Yuan
  • Patent number: 11900325
    Abstract: A device may receive project management data associated with development of a software product and may process a first portion of the project management data, with first models, to generate timeliness scores and an overall timeliness score for the software product. The device may process a second portion of the project management data, with second models, to generate quality scores and an overall quality score for the software product and may process a third portion of the project management data, with third models, to generate product readiness scores and an overall product readiness score for the software product. The device may utilize a fourth machine learning model, with the overall timeliness score, the overall quality score, and the overall product readiness score, to generate a success probability for the software product and may perform one or more actions based on the success probability for the software product.
    Type: Grant
    Filed: July 19, 2021
    Date of Patent: February 13, 2024
    Assignee: Accenture Global Solutions Limited
    Inventors: Aditi Kulkarni, Roopalaxmi Manjunath, Sudha Srinivasan, Rajesh Nagarajan, Koushik M. Vijayaraghavan, Nishanth Kumar, Sudhir Hanumanthappa, Parul Jagtap, Sangeetha Jayaram
  • Patent number: 11886318
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for monitoring technology usage and performance. In some implementations, use of a technology item by one or more individuals assigned to use the technology item is monitored. Based on the monitoring, usage data that indicates usage of the technology item is generated. One or more criteria for evaluating the usage of the technology item by the one or more individuals is identified. It is determined whether usage data satisfies the one or more criteria. A system provides, for display on a user interface, output data indicating whether the usage data satisfies the one or more criteria.
    Type: Grant
    Filed: January 30, 2023
    Date of Patent: January 30, 2024
    Assignee: VigNet Incorporated
    Inventors: Praduman Jain, Josh Schilling, Dave Klein, Mark James Begale
  • Patent number: 11886999
    Abstract: Apparatuses and methods can be related to implementing age-based network training. An artificial neural network (ANN) can be trained by introducing errors into the ANN. The errors and the quantity of errors introduced into the ANN can be based on age-based characteristics of the memory device.
    Type: Grant
    Filed: January 17, 2023
    Date of Patent: January 30, 2024
    Assignee: Micron Technology, Inc.
    Inventors: Saideep Tiku, Poorna Kale
  • Patent number: 11886783
    Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.
    Type: Grant
    Filed: January 12, 2023
    Date of Patent: January 30, 2024
    Assignee: SAMSUNG ELECTRONICS CO., LTD.
    Inventors: Sanghoon Myung, Hyunjae Jang, In Huh, Hyeon Kyun Noh, Min-Chul Park, Changwook Jeong
  • Patent number: 11869149
    Abstract: In various embodiments, an unsupervised training application executes a neural network on a first point cloud to generate keys and values. The unsupervised training application generates output vectors based on a first query set, the keys, and the values and then computes spatial features based on the output vectors. The unsupervised training application computes quantized context features based on the output vectors and a first set of codes representing a first set of 3D geometry blocks. The unsupervised training application modifies the first neural network based on a likelihood of reconstructing the first point cloud, the quantized context features, and the spatial features to generate an updated neural network. A trained machine learning model includes the updated neural network, a second query set, and a second set of codes representing a second set of 3D geometry blocks and maps a point cloud to a representation of 3D geometry instances.
    Type: Grant
    Filed: May 13, 2022
    Date of Patent: January 9, 2024
    Assignee: NVIDIA Corporation
    Inventors: Ben Eckart, Christopher Choy, Chao Liu, Yurong You
  • Patent number: 11854088
    Abstract: The embodiments recite systems and methods that improve the traditional underwriting process within a financial institution. These embodiments produce an underwriting model that emulates the resolution patterns of top performing underwriters. The underwriting model once is built and tested is incorporated into decision tools that provide underwriters with insightful advices when underwriting a client. The embodiments use statistical learning techniques such as support vector machine and logistic regression. These techniques can assume a linear or nonlinear relationship between factors and risk classes. Furthermore, the underwriting model also uses artificial intelligence tools such as expert systems and fuzzy logic. A company's underwriting standards and best underwriting practices may be updated periodically so that underwriting model based on decision heuristic keep improving the quality of its output over time.
    Type: Grant
    Filed: October 25, 2021
    Date of Patent: December 26, 2023
    Assignee: Massachusetts Mutual Life Insurance Company
    Inventors: Gareth Ross, Tricia Walker
  • Patent number: 11836610
    Abstract: An artificial neural network that includes first subnetworks to implement known functions and second subnetworks to implement unknown functions is trained. The first subnetworks are trained separately and in parallel on corresponding known training datasets to determine first parameter values that define the first subnetworks. The first subnetworks are executing on a plurality of processing elements in a processing system. Input values from a network training data set are provided to the artificial neural network including the trained first subnetworks. Error values are generated by comparing output values produced by the artificial neural network to labeled output values of the network training data set. The second subnetworks are trained by back propagating the error values to modify second parameter values that define the second subnetworks without modifying the first parameter values. The first and second parameter values are stored in a storage component.
    Type: Grant
    Filed: December 13, 2017
    Date of Patent: December 5, 2023
    Assignee: Advanced Micro Devices, Inc.
    Inventors: Dmitri Yudanov, Nicholas Penha Malaya
  • Patent number: 11822529
    Abstract: A system may forecast a plurality of workload measurements for a database management system (DBMS) at respective times based on a workload model. The system may determine, based on the forecasted workload measurements, configuration parameter sets optimized for the DBMS at the respective times. The system may generate a reconfiguration plan. The system may determine performance that would result from reconfiguring nodes of the DBMS with the configurations parameter sets. The system may select a reconfiguration plan in response to the performance satisfying a fitness criterion. The system may cause, at the reconfiguration times, the nodes to begin reconfiguration with the configuration parameter sets included in the selected reconfiguration plan.
    Type: Grant
    Filed: September 6, 2022
    Date of Patent: November 21, 2023
    Assignee: Purdue Research Foundation
    Inventors: Saurabh Bagchi, Somali Chaterji, Ashraf Mahgoub, Paul Curtis Wood
  • Patent number: 11803815
    Abstract: The presently disclosed subject matter includes an apparatus with a processor and a memory storing code which, when executed by the processor, causes the processor to receive a data profile associated with a candidate resource, the data profile includes a set of attributes of the candidate resource which are relevant for assessing the candidate resource's suitability to satisfy a particular resource demand. The apparatus extracts an n-dimensional feature vector from the received data profile, the n-dimensional feature vector capturing aspects of the candidate resource's attributes and process said n-dimensional feature vector with a first ensemble machine learning model to generate a first suitability factor. Likewise, the apparatus process said n-dimensional feature vector with a second ensemble machine learning model to generate a second suitability factor. The apparatus determines whether to allocate the candidate resource to the particular resource demand using said first and second suitability factors.
    Type: Grant
    Filed: July 27, 2018
    Date of Patent: October 31, 2023
    Assignee: Vettery, Inc.
    Inventors: Bhavish Agarwal, Abhishek Gupta, Ye Xu
  • Patent number: 11789710
    Abstract: A compile method for a neural network, the compile method includes receiving data related to the neural network, generating a grouped layer by grouping layers comprised in the neural network based on the data, generating a set of passes executable in parallel based on a dependency between a plurality of passes to process the neural network, generating a set of threads performing a plurality of optimization functions based on whether optimization operations performed by the optimization functions is performed independently for the layers, respectively, or sequentially based on a dependency between the layers, and performing compilation in parallel based on the grouped layer, the set of passes, and the set of threads.
    Type: Grant
    Filed: March 10, 2022
    Date of Patent: October 17, 2023
    Assignee: Samsung Electronics Co., Ltd.
    Inventor: Hanwoong Jung
  • Patent number: 11790289
    Abstract: The disclosed computer-implemented method may include (i) receiving a first transport request and a second transport request, (ii) evaluating a fitness of matching the first and second transport requests to be fulfilled by a transport provider, based at least partly on a transportation overlap between the first and second transport requests, (iii) generating a simulated future transport request, (iv) evaluating a fitness of matching the first transport request with the simulated future transport request, based at least in part on a transportation overlap between the first transport request and the simulated future transport request, and (v) matching the first and second transport requests based at least in part on the fitness of matching the first and second transport requests and based at least in part on the fitness of matching the first transport request with the simulated future transport request. Various other methods, systems, and computer-readable media are disclosed.
    Type: Grant
    Filed: January 21, 2022
    Date of Patent: October 17, 2023
    Assignee: Lyft, Inc.
    Inventor: Chinmoy Dutta
  • Patent number: 11783247
    Abstract: Aspects of the disclosure relate to using machine learning for resource planning. A computing platform may detect an occupancy modification event for a physical space. Based on detecting the occupancy modification event, the computing platform may send commands directing display of a data collection prompt to end user devices, which may prompt for work to be performed by users of the end user devices in the physical space during a first day. Using natural language processing, the computing platform may analyze user input information and other occupancy data to determine whether or not the users of the end user devices have permission to occupy the physical space during the first day. The computing platform may cause the end user devices to display a resource management interface indicating whether or not the users of the end user devices have valid permission to physically occupy the physical space during the first day.
    Type: Grant
    Filed: July 28, 2022
    Date of Patent: October 10, 2023
    Assignee: Bank of America Corporation
    Inventors: Veerandra S. Srivastava, Maharaj Mukherjee, Mehul Jayant Pandya, Utkarsh Raj
  • Patent number: 11783376
    Abstract: Tiered advertisement bidding is disclosed. One or more quality metrics associated with a user profile are determined. An advertisement bid is selected from a plurality of tiered bids based at least in part on the determined quality metrics. Determining the quality metrics can include determining a conversion assessment. Determining the quality metric can also include determining whether a need associated with a user profile has been met for a category. In some cases, persona detection is performed with respect to the user profile.
    Type: Grant
    Filed: December 22, 2022
    Date of Patent: October 10, 2023
    Assignee: Security Technology, LLC
    Inventor: Bjorn Markus Jakobsson
  • Patent number: 11741369
    Abstract: Some embodiments provide a method for training a machine-trained (MT) network that processes inputs using network parameters. The method propagates a set of input training items through the MT network to generate a set of output values. The set of input training items comprises multiple training items for each of multiple categories. The method identifies multiple training item groupings in the set of input training items. Each grouping includes at least two training items in a first category and at least one training item in a second category. The method calculates a value of a loss function as a summation of individual loss functions for each of the identified training item groupings. The individual loss function for each particular training item grouping is based on the output values for the training items of the grouping. The method trains the network parameters using the calculated loss function value.
    Type: Grant
    Filed: October 29, 2021
    Date of Patent: August 29, 2023
    Assignee: PERCEIVE CORPORATION
    Inventors: Eric A. Sather, Steven L. Teig, Andrew C. Mihal
  • Patent number: 11736767
    Abstract: Disclosed herein are system, method, and computer program product embodiments for the detection of human presence in an energy efficient manner using a plurality of sensors such as those of a battery-powered device such as a television remote, and a device with a processor, such as a television. Data gathered from an initial television WiFi radio scan, or an initial low-powered detection scan from the television remote, may be analyzed by the processor to determine a potential presence of one or more humans are present proximate to the device. If there is such a potential presence, the device remote can enter a full-powered detection mode to accurately determine the presence or absence of one or more humans, and take further actions.
    Type: Grant
    Filed: May 13, 2020
    Date of Patent: August 22, 2023
    Assignee: ROKU, INC.
    Inventors: Jan Neerbek, Rafal Krzysztof Malewski, Brian Thoft Moth Møller, Paul Nangeroni, Amalavoyal Narasimha Chari
  • Patent number: 11727249
    Abstract: In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
    Type: Grant
    Filed: November 15, 2021
    Date of Patent: August 15, 2023
    Assignee: NARA LOGICS, INC.
    Inventors: Nathan R. Wilson, Sahil Zubair, Denise Ichinco, Raymond J. Plante, Jana B. Eggers
  • Patent number: 11727671
    Abstract: Provided are methods for efficient and optimal feature extraction, which can include identifying observations that satisfy a predetermined configuration of metrics. Some methods described also include extracting feature values of a respective metric from the identified observations and determining parameters for feature extraction based on the feature values extracted from the identified observations and a respective label of the identified observations. Systems and computer program products are also provided.
    Type: Grant
    Filed: August 26, 2022
    Date of Patent: August 15, 2023
    Assignee: Motional AD LLC
    Inventors: Zhiliang Chen, Ke Yi Kaitlyn Ng, Pietro Zullo
  • Patent number: 11720826
    Abstract: Techniques that facilitate feedback loop learning between artificial intelligence systems are provided. In one example, a system includes a monitoring component and a machine learning component. The monitoring component identifies a data pattern associated with data for an artificial intelligence system. The machine learning component compares the data pattern to historical data patterns for the artificial intelligence system to facilitate modification of at least a component of the artificial intelligence system and/or one or more dependent systems of the artificial intelligence system.
    Type: Grant
    Filed: July 24, 2019
    Date of Patent: August 8, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Jinho Hwang, Larisa Shwartz, Hagen Völzer, Michael Elton Nidd, Rodrigo Otavio Castrillon
  • Patent number: 11714913
    Abstract: A method includes receiving historical interaction data, which includes a plurality of historical interactions. Each historical interaction is associated with a plurality of data fields. The method includes assigning a plurality of weights to the plurality of data fields, generating a neural network using the plurality of weights and the plurality of data fields, identifying a first plurality of feature indicators indicative of a first class, the first class being different from a second class; receiving a second plurality of feature indicators derived from data relating to compromised accounts, updating, a probability distribution component using the first plurality of feature indicators and the second plurality of feature indicators, and receiving current data for an interaction. The method also includes applying the probability distribution component to the current data, and scoring the interaction using the probability distribution component.
    Type: Grant
    Filed: October 9, 2018
    Date of Patent: August 1, 2023
    Assignee: Visa International Service Association
    Inventors: Juharasha Shaik, Durga Kala, Gajanan Chinchwadkar
  • Patent number: 11710251
    Abstract: In one embodiment, a method includes receiving an image associated with an object in an environment, the image being captured by sensors associated with a vehicle, generating a feature representation of the image, determining a potential ground control point associated with the object based on the feature representation of the image, determining a predetermined location reading based on the potential ground control point, calculating a differential relative to the predetermined location reading based on the potential ground control point, and determining a location of the vehicle based on the differential and the predetermined location reading based on the potential ground control point.
    Type: Grant
    Filed: November 2, 2020
    Date of Patent: July 25, 2023
    Assignee: Lyft, Inc.
    Inventors: Ramesh Rangarajan Sarukkai, Shaohui Sun
  • Patent number: 11686736
    Abstract: The present disclosure relates to the field of laboratory diagnostics. Specifically, methods are disclosed for determining a patient's risk of suffering from heart failure (HF) based on the detection of NT-proBNP, troponin T, and/or a natriuretic peptide. Also disclosed are methods for improving both the accuracy and speed of HF risk models by incorporating biomarker data from patient samples.
    Type: Grant
    Filed: March 15, 2018
    Date of Patent: June 27, 2023
    Inventors: Christie Mitchell Ballantyne, Ron Hoogeveen, Vijay Nambi, Lloyd E. Chambless
  • Patent number: 11645625
    Abstract: Machine learning systems for predictive targeting and optimizing engagement are described herein. In various embodiments, the system includes 1) training a first machine learning computer model to generate machine predicted outcomes; (2) determining weights based on the machine predicted outcomes; (3) generating a second machine learning computer model based on the weights; and (4) generating machine learned predictions for candidates.
    Type: Grant
    Filed: August 21, 2019
    Date of Patent: May 9, 2023
    Assignee: JOB MARKET MAKER, LLC
    Inventors: Christina R. Whitehead, Joseph W. Hanna
  • Patent number: 11636090
    Abstract: A computer-implemented method, system, and non-transitory machine readable medium for a graph-based analysis for an Information Technology (IT) operations includes generating a temporal graph by extracting one or more of operation objects, relations and attributes from operation data of workloads distributed across a plurality of levels of the IT operation within a predetermined time window. Anomalies are detected from the extracted operation data and annotating corresponding objects in the graph. A directional impact between corresponding objects on the temporal graph is determined, and the temporal graph is refined based on the determined directional impact. Accessible paths in the temporal graph indicating error propagation are searched, and potential causes for the detected anomalies in the temporal graph are identified. A list of the potential causes of the anomalies is generated, and a root cause ranked for each of the corresponding objects in the temporal graph.
    Type: Grant
    Filed: March 15, 2020
    Date of Patent: April 25, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Jia Qi Li, Fan Jing Meng, Pei Ni Liu, Zi Xiao Zhu, Matt Hogstrom, Dong Sheng Li
  • Patent number: 11636435
    Abstract: The present disclosure relates to systems and methods for optimizing benefits plan options offered by an organization through balancing derived population preferences with organizational preferences by analyzing historical selections made by individuals. Census data dividing members of an organization into census divisions may be applied to machine learning algorithm(s) to derive estimated selection preferences of the members. Using selection preferences, costs of various product offering scenarios and overall member satisfaction estimates of the scenarios may be calculated. Product offering scenarios meeting member preference criteria and organizational budget criteria may be presented for review.
    Type: Grant
    Filed: May 21, 2020
    Date of Patent: April 25, 2023
    Assignee: Aon Global Operations SE, Singapore Branch
    Inventors: Michael Morrow, Salina Shah, Todor Penev, Andy Rallis, Kartick Subramanian
  • Patent number: 11636338
    Abstract: A computer-implemented method is provided for data augmentation. The method includes calculating, by a hardware processor for each of words in a text data, a word replacement probability based on a word occurrence frequency in the text data, wherein the word replacement probability decreases with increasing word occurrence frequency. The method additionally includes selectively replacing at least one of the words in the text data with words predicted therefor by a Bidirectional Neural Network Language Model (BiNNLM) to generate augmented text data, based on the word replacement probability.
    Type: Grant
    Filed: March 20, 2020
    Date of Patent: April 25, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Masayasu Muraoka, Tetsuya Nasukawa
  • Patent number: 11627316
    Abstract: Disclosed according to one exemplary embodiment includes not limited to: a filtering unit configured to generate filtering information by filtering a residual image corresponding to a difference between an original image and a prediction image; an inverse filtering unit configured to generate inverse filtering information by inversely filtering the filtering information; an estimator configured to generate the prediction image based on the original image and reconstruction information; a CNN-based in-loop filter configured to receive the inverse filtering information and the prediction image and to output the reconstruction information; and an encoder configured to perform encoding based on the filtering information and information of the prediction image, and wherein the CNN-based in-loop filter is trained for each of the plurality of artefact sections according to an artefact value or for each of the plurality of quantization parameter sections according to a quantization parameter.
    Type: Grant
    Filed: July 15, 2021
    Date of Patent: April 11, 2023
    Assignee: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY
    Inventor: Mun Churl Kim
  • Patent number: 11620523
    Abstract: Artificial-intelligence-based river information system. In an embodiment, a first training dataset is used to train a travel time prediction model to predict a travel time along the waterway for a given trip. In addition, a second training dataset is used to train a river level prediction model to predict a river level along the waterway for a given time. For each of a plurality of trips, a request is received that specifies the trip and a time of the trip, and, in response to the request, the travel time prediction model is used to predict a travel time for the trip, and the river level prediction model is used to predict a river level of the waterway at one or more points along the trip. Then, a voyage plan is generated based on one or both of the predicted travel time and the predicted river level.
    Type: Grant
    Filed: April 14, 2022
    Date of Patent: April 4, 2023
    Assignee: Trabus
    Inventors: Joseph Celano, David Sathiaraj, Eric Ho, Andrew Nolan Smith, Eric Vincent Rohli
  • Patent number: 11620499
    Abstract: Aspects described herein provide a method including: receiving input data at a machine learning model, comprising: a plurality of processing layers; a plurality of gate logics; a plurality of gates; and a fully connected layer; determining based on a plurality of gate parameters associated with the plurality of gate logics, a subset of the plurality of processing layers with which to process the input data; processing the input data with the subset of the plurality of processing layers and the fully connected layer to generate an inference; determining a prediction loss based on the inference and a training label associated with the input data; determining an energy loss based on the subset of the plurality of processing layers used to process the input data; and optimizing the machine learning model based on: the prediction loss; the energy loss; and a prior probability associated with the training label.
    Type: Grant
    Filed: November 25, 2019
    Date of Patent: April 4, 2023
    Assignee: Qualcomm Incorporated
    Inventors: Jamie Menjay Lin, Daniel Hendricus Franciscus Fontijne, Edwin Chongwoo Park
  • Patent number: 11612134
    Abstract: An electronic monitor can monitor experimental animals in a cage. The cage has one or more walls that enclose a living space for the experimental animals. The electronic monitor is coupled to the cage. The electronic monitor may include a housing adapted to be mechanically coupled to the cage in a predefined position relative to the cage. A substantially sterile barrier is provided between the living space and the external environment in this coupled state. The walls of the cage may include a signal-interface section. An electromagnetic detector may be coupled to the housing to have a line-of-sight through the signal-interface section and into the living space of the cage. The electromagnetic detector is adapted to detect electromagnetic radiation that is transmitted through the signal-interface section. A controller processes a signal received from the electromagnetic detector to determine a status of the experimental animals or the living space.
    Type: Grant
    Filed: February 15, 2021
    Date of Patent: March 28, 2023
    Assignee: Recursion Pharmaceuticals, Inc.
    Inventors: Jonathan Noble Betts-Lacroix, Timothy Levi Robertson
  • Patent number: 11615315
    Abstract: A machine learning system includes a coach machine learning system that uses machine learning to help a student machine learning system learn its system. By monitoring the student learning system, the coach machine learning system can learn (through machine learning techniques) “hyperparameters” for the student learning system that control the machine learning process for the student learning system. The machine learning coach could also determine structural modifications for the student learning system architecture. The learning coach can also control data flow to the student learning system.
    Type: Grant
    Filed: March 9, 2022
    Date of Patent: March 28, 2023
    Assignee: D5AI LLC
    Inventor: James K. Baker
  • Patent number: 11604305
    Abstract: Classifying land use by receiving geographic data and land use data for a geographic area, receiving surface temperature data for the geographic area, mapping the geographic data and temperature data to a set of map grid cells, determining temperature statistics for each map grid cell, training a machine learning model according to the land use data and temperature statistics, and classifying land use for map grid cells of a different geographic area according to the machine learning model.
    Type: Grant
    Filed: October 9, 2020
    Date of Patent: March 14, 2023
    Assignee: International Business Machines Corporation
    Inventors: Campbell D Watson, Mukul Tewari, Lloyd A Treinish, Eli Michael Dow
  • Patent number: 11604988
    Abstract: Methods, systems, apparatuses, and computer programs, are described for generalizing a learned behavior across different tasks.
    Type: Grant
    Filed: April 16, 2020
    Date of Patent: March 14, 2023
    Assignee: The Johns Hopkins University
    Inventors: Bruce A. Swett, Corban G. Rivera
  • Patent number: 11599790
    Abstract: Embodiments of the subject technology for deep learning based reservoir modelling provides for receiving input data comprising information associated with one or more well logs in a region of interest. The subject technology determines, based at least in part on the input data, an input feature associated with a first deep neural network (DNN) for predicting a value of a property at a location within the region of interest. Further, the subject technology trains, using the input data and based at least in part on the input feature, the first DNN. The subject technology predicts, using the first DNN, the value of the property at the location in the region of interest. The subject technology utilizes a second DNN that classifies facies based on the predicted property in the region of interest.
    Type: Grant
    Filed: July 21, 2017
    Date of Patent: March 7, 2023
    Assignee: Landmark Graphics Corporation
    Inventors: Yogendra Narayan Pandey, Keshava Prasad Rangarajan, Jeffrey Marc Yarus, Naresh Chaudhary, Nagaraj Srinivasan, James Etienne
  • Patent number: 11600396
    Abstract: Systems and methods for collecting clinical trial data across multiple locations is described. One described method; decentralized clinical trial design; comprises collecting clinical and non-clinical data on a client device over a network; the data is collected at a hospital, home or an alternate care facility, by either the patient or the healthcare professional; and transmitting the data, for access to sponsors over the network.
    Type: Grant
    Filed: April 29, 2020
    Date of Patent: March 7, 2023
    Assignee: CliniOps, Inc.
    Inventors: Avik. Kumar Pal, Yerramalli Subramaniam
  • Patent number: 11593645
    Abstract: Embodiments implement non-intrusive load monitoring using machine learning. A trained convolutional neural network (CNN) can be stored, where the CNN includes a plurality of layers, and the CNN is trained to predict disaggregated target device energy usage data from within source location energy usage data based on training data including labeled energy usage data from a plurality of source locations. Input data can be received including energy usage data at a source location over a period of time. Disaggregated target device energy usage can be predicted, using the trained CNN, based on the input data.
    Type: Grant
    Filed: November 27, 2019
    Date of Patent: February 28, 2023
    Assignee: Oracle International Corporation
    Inventors: Selim Mimaroglu, Oren Benjamin, Arhan Gunel, Anqi Shen
  • Patent number: 11577616
    Abstract: In various embodiments, methods, systems, and vehicle apparatuses are provided. A method for implementing torque control using a Neural Network (NN) for a torque prediction model to receive a set of measured vehicle operating inputs associated with torque prediction; substituting a set of multiple independent variables into the torque prediction model so that the NN is then taking the form of a simplified pseudo-NN that contains a reduced variable set of one independent variable; processing, the set of measured vehicle operating inputs by the pseudo-NN based on the NN prediction model by using only one independent variable in a pseudo-NN's simplified mathematical expression; and solving for at least one root of the pseudo-NN's simplified mathematical expression by obtaining a root value without having to rely on an inversion operation of a mathematical expression that consists of an entire set of independent variables.
    Type: Grant
    Filed: October 27, 2020
    Date of Patent: February 14, 2023
    Assignee: GM GLOBAL TECHNOLOGY OPERATIONS LLC
    Inventor: Dana J. Suttman
  • Patent number: 11574377
    Abstract: Embodiments for providing intelligent transportation service management in a transportation system by a processor. Transportation service requests may be assigned amongst multiple transportation service providers according to one or more transportation service request distribution models and various parameters and preferences for each user. The transportation service request distribution models may protect information relation to each of the transportation service providers and suggests a selected order for distributing the plurality of transportation service requests.
    Type: Grant
    Filed: June 3, 2019
    Date of Patent: February 7, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Julien Monteil, Claudio Gambella, Andrea Simonetto, Yassine Lassoued, Anton Dekusar, Martin Mevissen
  • Patent number: 11567914
    Abstract: Disclosed are a framework and method for selecting an anomaly detection method for each of a plurality of class of time series based on characteristics a time series example that represents an expected form of data. The method provides classification of a given time series into one of known classes based on expected properties of the time series, filtering the set of possible detection methods based on the time series class, evaluating the remaining detection methods on the given time series using the specific evaluation metric and selecting and returning a recommended anomaly detection method based on the specific evaluation metric.
    Type: Grant
    Filed: September 13, 2019
    Date of Patent: January 31, 2023
    Assignee: Verint Americas Inc.
    Inventors: Ian Roy Beaver, Cynthia Freeman, Jonathan Merriman
  • Patent number: 11562402
    Abstract: Tiered advertisement bidding is disclosed. One or more quality metrics associated with a user profile are determined. An advertisement bid is selected from a plurality of tiered bids based at least in part on the determined quality metrics. Determining the quality metrics can include determining a conversion assessment. Determining the quality metric can also include determining whether a need associated with a user profile has been met for a category. In some cases, persona detection is performed with respect to the user profile.
    Type: Grant
    Filed: March 15, 2021
    Date of Patent: January 24, 2023
    Assignee: RightQuestion, LLC
    Inventor: Bjorn Markus Jakobsson
  • Patent number: 11559616
    Abstract: A method for determining the dry weight of a patient after dialysis therapy, wherein the patient's blood volume is monitored and blood volume values are output. The blood volume values are recorded and evaluated for a predetermined period of time after reaching an ultrafiltration volume appropriately predetermined for the patient, wherein the dry weight of the patient then is determined on the basis of the rate of change of the blood volume during the predetermined period of time.
    Type: Grant
    Filed: August 17, 2017
    Date of Patent: January 24, 2023
    Assignee: B. Braun Avitum AG
    Inventors: Richard Atallah, Florian Bauer
  • Patent number: 11556935
    Abstract: An approach is provided in which the approach constructs a 3-dimensional (3D) matrix based on a plurality of historical transactions performed by a user. The 3D matrix includes a set of features, a set of rows, and a set of channels. The approach trains a convolutional neural network using the 3D matrix, and then uses the trained convolutional neural network to predict a risk level of a new transaction initiated by the user. The approach transmits an alert message based on the predicted risk level.
    Type: Grant
    Filed: July 28, 2021
    Date of Patent: January 17, 2023
    Assignee: International Business Machines Corporation
    Inventors: Chun Lei Xu, Jing James Xu, Xiao Ming Ma, Yi Shan Jiang, Lei Gao