Machine Learning Patents (Class 706/12)
  • Patent number: 11925469
    Abstract: The present invention relates to a non-invasive cardiac monitoring device that records cardiac data to infer physiological characteristics of a human, such as cardiac arrhythmia. Some embodiments of the invention allow for long-term monitoring of physiological signals. Further embodiments allow for processing of the detected cardiac rhythm signals partially on the wearable cardiac monitor device, and partially on a remote computing system. Some embodiments include a wearable cardiac monitor device for long-term adhesion to a mammal for prolonged detection of cardiac rhythm signals.
    Type: Grant
    Filed: July 1, 2022
    Date of Patent: March 12, 2024
    Assignee: iRhythm Technologies, Inc.
    Inventors: Steven Szabados, Yuriko Tamura, Xixi Wang, George Mathew
  • Patent number: 11929845
    Abstract: A system and method are disclosed that utilizes an artificial intelligence based virtual proxy node. The virtual proxy node includes an intent resolution model and communicates between a smart audio device and at least one secondary device, wherein the at least one secondary device is configured to be controlled by a smart audio device or smart hub. The virtual proxy node tracks interactions between the smart audio device and the at least one secondary device to derive historical and context data from the tracking interactions. The virtual proxy node uses the historical and context data to predict which secondary device will be successful in responding to the user input command and broadcasts the input command to the virtual proxy node associated with one of the at least one secondary device. The virtual proxy node includes an intent resolution model trained by historical and context data.
    Type: Grant
    Filed: January 7, 2022
    Date of Patent: March 12, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Anvita Vyas, Namit Kabra, Vijay Ekambaram, Sarbajit K. Rakshit
  • Patent number: 11928464
    Abstract: A model lifecycle management method includes: executing a model initial development phase based on at least a first criteria, a second criteria, and a third criteria to obtain a set of production ready models; executing, using the set of production ready models, a model production phase based on at least a fourth criteria, a fifth criteria, and a sixth criteria to obtain; and executing, after executing the model production phase, using the set of models to be updated, a model update phase based on at least a seventh criteria on at least one model in the model production phase.
    Type: Grant
    Filed: March 25, 2022
    Date of Patent: March 12, 2024
    Assignee: Dell Products L.P.
    Inventors: Balasubramanian Chandrasekaran, Lucas Avery Wilson, Dharmesh M. Patel
  • Patent number: 11928133
    Abstract: Described are systems and methods for establishing a unit group dictionary based on user provided annotations. The unit group dictionary may be used to identify relationships between multiple items in a corpus. Those relationships may facilitate the display of object identifiers and/or other aspects used and/or provided by the object management service.
    Type: Grant
    Filed: August 23, 2021
    Date of Patent: March 12, 2024
    Assignee: Pinterest, Inc.
    Inventors: Ningning Hu, Tze Way Eugene Ie
  • Patent number: 11930030
    Abstract: A system detects and responds to malicious acts directed towards machine learning models. Data fed into and output by a machine learning model is collected by a sensor. The data fed into the model includes vectorization data, which is generated from raw data provided from a requester, such as for example a stream of timeseries data. The output data may include a prediction or other output generated by the machine learning model in response to receiving the vectorization data. The vectorization data and machine learning model output data are processed to determine whether the machine learning model is being subject to a malicious act (e.g., attack). The output of the processing may indicate an attack score. A response for handling the request by a requester may be selected based on the output that includes the attack score, and the response may be applied to the requestor.
    Type: Grant
    Filed: November 8, 2023
    Date of Patent: March 12, 2024
    Assignee: HiddenLayer Inc.
    Inventors: Tanner Burns, Chris Sestito, James Ballard
  • Patent number: 11928567
    Abstract: Methods, systems and computer program products are described to improve machine learning (ML) model-based classification of data items by identifying and removing inaccurate training data. Inaccurate training samples may be identified, for example, based on excessive variance in vector space between a training sample and a mean of category training samples, and based on a variance between an assigned category and a predicted category for a training sample. Suspect or erroneous samples may be selectively removed based on, for example, vector space variance and/or prediction confidence level. As a result, ML model accuracy may be improved by training on a more accurate revised training set. ML model accuracy may (e.g., also) be improved, for example, by identifying and removing suspect categories with excessive (e.g., weighted) vector space variance. Suspect categories may be retained or revised. Users may (e.g., also) specify a prediction confidence level and/or coverage (e.g., to control accuracy).
    Type: Grant
    Filed: March 17, 2023
    Date of Patent: March 12, 2024
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Oren Elisha, Ami Luttwak, Hila Yehuda, Adar Kahana, Maya Bechler-Speicher
  • Patent number: 11928124
    Abstract: An Artificial Intelligence (AI)-based data processing system processes current data to determine if the quality of the current data is adequate to be provided to data consumers and if the quality is adequate, the current data is further analyzed to determine if an impacted load including changes to dimension data of the current data or an incremental load including changes to fact data of the current data is to be provided to the data consumers. Depending on the amount of data to be provided to the data consumers, processing units (PUs) may be determined and assigned to carry out the data upload. Various machine learning (ML) models that are used to provide predictions from the current data are analyzed to determine the quality of predictions and if needed, can be automatically retrained by the data processing system.
    Type: Grant
    Filed: August 3, 2021
    Date of Patent: March 12, 2024
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Mamta Aggarwal Rajnayak, Govindarajan Jothikumar, Rajat Agarwal, Prateek Jain
  • Patent number: 11928563
    Abstract: The present application provides a model training, image processing method, device, storage medium, and program product relating to deep learning technology, which are able to screen auxiliary image data with image data for learning a target task, and further fuse the target image data and the auxiliary image data, so as to train a built and to-be-trained model with the fusion-processed fused image data. This implementation can increase the amount of data for training the model, and the data for training the model is determined is based on the target image data, which is suitable for learning the target task. Therefore, the solution provided by the present application can train an accurate target model even if the amount of target image data is not sufficient.
    Type: Grant
    Filed: June 23, 2021
    Date of Patent: March 12, 2024
    Assignee: Beijing Baidu Netcom Science Technology Co., Ltd.
    Inventors: Xingjian Li, Haoyi Xiong, Dejing Dou
  • Patent number: 11927926
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting control settings for the environment based on (i) a causal model that identifies causal relationships between possible settings for controllable elements in the environment and environment responses that reflect a performance of the control system in controlling the environment and (ii) current values of a set of internal parameters; and during the repeatedly selecting: monitoring environment responses to the selected control settings; determining, based on the environment responses, an indication that one or more properties of the environment have changed; and in response, modifying the current values of one or more of the internal parameters.
    Type: Grant
    Filed: September 11, 2019
    Date of Patent: March 12, 2024
    Assignee: 3M Innovative Properties Company
    Inventors: Brian E. Brooks, Gilles J. Benoit, Peter O. Olson, Tyler W. Olson, Himanshu Nayar, Frederick J. Arsenault, Nicholas A. Johnson
  • Patent number: 11928436
    Abstract: Methods and systems are presented for analyzing feedback data associated with a content and generating an interactive graphical representation of the feedback data. Upon receiving a request from a user, a feedback analysis system may access feedback data associated with a content from a content hosting server. The feedback data may include comments submitted by viewers of the content. The feedback analysis system may analyze the comments and generate an interactive graphical representation of the feedback data. The interactive graphical representation may include icons that represents keywords that are relevant to the comments and sentiments of the viewers derived based on the comments. Upon receiving a selection of an icon, the feedback analysis system may present a comment that corresponds to the keyword and/or sentiment represented by the icon.
    Type: Grant
    Filed: November 21, 2022
    Date of Patent: March 12, 2024
    Assignee: TYNTRE, LLC
    Inventor: Thomas Chen
  • Patent number: 11928698
    Abstract: An information processing apparatus having a first fitness calculation to calculate a fitness using a predetermined function for models in a population; a virtual model generating to select, as parent models, models having higher value of the fitness using the first fitness calculation among the models, and generate a virtual model that outputs by performing calculation of output results of the selected parent models; a second fitness calculation to calculate the fitness of the virtual model using the predetermined function; a replacing operation constituting the population by adding the virtual model and by deleting a model having lower value of the fitness among the models in the population; and a model extracting to extract a model having higher value of the fitness from the population by repeating processing by the virtual model generating, the second fitness calculation, and the model replacing until a predetermined termination condition is reached.
    Type: Grant
    Filed: January 20, 2020
    Date of Patent: March 12, 2024
    Assignee: RAKUTEN GROUP, INC.
    Inventors: Dinesh Daultani, Bruno Andre Charron
  • Patent number: 11928583
    Abstract: Techniques for generating a set of Deep Learning (DL) models are described. An example method includes training an initial set of DL models using the training data, wherein a topology of each of the DL models is determined based on the parameters vector. The method also includes generating a set of estimate performance functions for each of the DL models in the initial set based on the set of edge-related metrics, and generating a plurality of objective functions based on the set of estimated performance functions. The method also includes generating a final DL model set based on the objective functions, receiving a user selection of a selected DL model from the final DL model set, and deploying the selected DL model to an edge device.
    Type: Grant
    Filed: July 8, 2019
    Date of Patent: March 12, 2024
    Assignee: International Business Machines Corporation
    Inventors: Lior Turgeman, Nir Naaman, Michael Masin, Nili Guy, Shmuel Kalner, Ira Rosen, Adar Amir
  • Patent number: 11928011
    Abstract: Embodiments of systems and methods for enhanced drift remediation with causal methods and online model modification are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: detect drift in an Artificial Intelligence (AI) or Machine Learning (ML) model configured to make a prediction or a causal reasoning graphical or structural inference based upon input data, identify a root cause of the drift, and tag the input data with an indication of the root cause.
    Type: Grant
    Filed: October 22, 2021
    Date of Patent: March 12, 2024
    Assignee: Dell Products, L.P.
    Inventors: Said Tabet, Jeffery White, George Currie, Xin Ma
  • Patent number: 11928208
    Abstract: A calculation device receives input of a plurality of pieces of training data including a communication destination known to be malignant as data. The calculation device generates a model that calculates a malignant degree of an input communication destination from each piece of the training data. The calculation device gives weight to each of the models, and generates a mixed model using the model and the weight. The calculation device calculates a malignant degree of a communication destination unknown whether the communication destination is malignant using the mixed model.
    Type: Grant
    Filed: April 16, 2019
    Date of Patent: March 12, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Daiki Chiba, Yuta Takata, Mitsuaki Akiyama
  • Patent number: 11928017
    Abstract: A method includes receiving a point data anomaly detection query from a user. The query requests the data processing hardware to determine a quantity of anomalous point data values in a set of point data values. The method includes training a model using the set of point data values. For at least one respective point data value in the set of point data values, the method includes determining, using the trained model, a variance value for the respective point data value and determining that the variance value satisfies a threshold value. Based on the variance value satisfying the threshold value, the method includes determining that the respective point data value is an anomalous point data value. The method includes reporting the determined anomalous point data value to the user.
    Type: Grant
    Filed: May 21, 2022
    Date of Patent: March 12, 2024
    Assignee: Google LLC
    Inventors: Zichuan Ye, Jiashang Liu, Forest Elliott, Amir Hormati, Xi Cheng, Mingge Deng
  • Patent number: 11928857
    Abstract: Techniques for implementing unsupervised anomaly detection by self-prediction are provided. In one set of embodiments, a computer system can receive an unlabeled training data set comprising a plurality of unlabeled data instances, where each unlabeled data instance includes values for a plurality of features. The computer system can further train, for each feature in the plurality of features, a supervised machine learning (ML) model using a labeled training data set derived from the unlabeled training data set, receive a query data instance, and generate a self-prediction vector using at least a portion of the trained supervised ML models and the query data instance, where the self-prediction vector indicates what the query data instance should look like if it were normal. The computer system can then generate an anomaly score for the query data instance based on the self-prediction vector and the query data instance.
    Type: Grant
    Filed: July 8, 2020
    Date of Patent: March 12, 2024
    Assignee: VMware LLC
    Inventors: Yaniv Ben-Itzhak, Shay Vargaftik
  • Patent number: 11928573
    Abstract: A computer system has a first machine learning module configured to predict a probability of a respective option being selected by a particular user if presented to that user via a computer app. A second machine learning module is configured to determine a respective confidence value associated with the probability. A third module uses the predicted probabilities and confidence values to determine at least one option to be presented to the particular user.
    Type: Grant
    Filed: November 14, 2022
    Date of Patent: March 12, 2024
    Assignee: KING.COM LTD.
    Inventors: Lele Cao, Sahar Asadi
  • Patent number: 11919165
    Abstract: Process evolution for robotic process automation (RPA) and RPA workflow micro-optimization are disclosed. Initially, an RPA implementation may be scientifically planned, potentially using artificial intelligence (AI). Embedded analytics may be used to measure, report, and align RPA operations with strategic business outcomes. RPA may then be implemented by deploying AI skills (e.g., in the form of machine learning (ML) models) through an AI fabric that seamlessly applies, scales, manages AI for RPA workflows of robots. This cycle of planning, measuring, and reporting may be repeated, potentially guided by more and more AI, to iteratively improve the effectiveness of RPA for a business. RPA implementations may also be identified and implemented based on their estimated return on investment (ROI).
    Type: Grant
    Filed: February 6, 2023
    Date of Patent: March 5, 2024
    Assignee: UiPath, Inc.
    Inventors: Prabhdeep Singh, Christian Berg
  • Patent number: 11922322
    Abstract: Aspects of the present disclosure enable humanly-specified relationships to contribute to a mapping that enables compression of the output structure of a machine-learned model. An exponential model such as a maximum entropy model can leverage a machine-learned embedding and the mapping to produce a classification output. In such fashion, the feature discovery capabilities of machine-learned models (e.g., deep networks) can be synergistically combined with relationships developed based on human understanding of the structural nature of the problem to be solved, thereby enabling compression of model output structures without significant loss of accuracy. These compressed models provide improved applicability to “on device” or other resource-constrained scenarios.
    Type: Grant
    Filed: January 30, 2023
    Date of Patent: March 5, 2024
    Assignee: GOOGLE LLC
    Inventors: Mitchel Weintraub, Ananda Theertha Suresh, Ehsan Variani
  • Patent number: 11924052
    Abstract: A network device divided into a training plane and a control plane, model management server that controls a network device, and processing methods of a network device and model management server are disclosed. A processing method may include receiving a machine learning model from a model management server, obtaining network data to generate analytics information, generating analytics information by inputting the network data to a machine learning model, feeding back the analytics information to the model management server, and generating a control command of the network device using the analytics information, wherein the analytics information is generated by a training plane function and the control command is generated by a control plane function.
    Type: Grant
    Filed: September 24, 2021
    Date of Patent: March 5, 2024
    Assignee: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE
    Inventors: Myung Ki Shin, Soohwan Lee
  • Patent number: 11922287
    Abstract: Described herein are embodiments of a reinforcement learning based large-scale multi-objective ranking system. Embodiments of the system may be used for optimizing short-video recommendation on a video sharing platform. Multiple competing ranking objective and implicit selection bias in user feedback are the main challenges in real-world platform. In order to address those challenges, multi-gate mixture of experts (MMoE) and soft actor critic (SAC) are integrated together into a MMoE_SAC system. Experiment results demonstrate that embodiments of the MMoE_SAC system may greatly reduce a loss function compared to systems only based on single strategies.
    Type: Grant
    Filed: July 15, 2020
    Date of Patent: March 5, 2024
    Assignees: Baidu USA, LLC, Baidu.com Times Technology (Beijing) Co., Ltd.
    Inventors: Dingcheng Li, Xu Li, Jun Wang, Ping Li
  • Patent number: 11921505
    Abstract: The present invention discloses a collaborative design method using an event-triggered scheme (ETS) and a Takagi-Sugeno (T-S) fuzzy H? controller in a network environment. For the problem about the unmanned surface vehicle control based on a switching T-S fuzzy system under an aperiodic DoS attack, the present invention provides an H? controller design method based on the event-triggered scheme. The characteristics of the unmanned surface vehicle system under the DoS attack are analyzed, and external disturbance in the navigation process is added into an unmanned surface vehicle motion model to establish an unmanned surface vehicle switching system model. The stability of the system is analyzed by piecewise Lyapunov functionals, such that controller gain and event-triggered scheme weight matrix parameters are obtained, thus ensuring that a networked unmanned surface vehicle navigation system has the ability to resist the DoS attack and the external disturbance.
    Type: Grant
    Filed: November 18, 2020
    Date of Patent: March 5, 2024
    Assignee: WUHAN UNIVERSITY OF TECHNOLOGY
    Inventors: Yong Ma, Hao Li, Zongqiang Nie
  • Patent number: 11922232
    Abstract: Techniques are described for providing an IT and security operations mobile application for managing IT and security operations instances of an IT and security operations application via a mobile device. The IT and security operations mobile application can be linked to the IT and security operations application to enable the IT and security operations application to send messages (e.g., notifications, alerts, action requests, etc.) related the occurrences of incidents/events in an IT environment, such as security-related incident, that can impact the operation of the IT environment. The IT and security operations mobile application enables a user to respond to the messages by initiating actions that are sent to the IT and security operations application for executing within the IT environment.
    Type: Grant
    Filed: October 20, 2021
    Date of Patent: March 5, 2024
    Assignee: Splunk Inc.
    Inventors: Maryann Cristofi, Jeff Roecks, Kavita Varadarajan
  • Patent number: 11922333
    Abstract: A search method using an artificial intelligence based information retrieval model and a method for training the artificial intelligence based information retrieval model used for the method are provided. In the method, even if there is no labeled data and only a corpus exists, the artificial intelligence based information retrieval model can be trained using the weak-supervision methodology. Search can be performed by dividing documents into passages having short lengths. Compared to an information retrieval model based on unsupervised learning, improved search results are provided.
    Type: Grant
    Filed: May 16, 2022
    Date of Patent: March 5, 2024
    Assignees: HOSEO UNIVERSITY ACADEMIC COOPERATION FOUNDATION, LIVIN AI INC.
    Inventors: Sungbum Park, Suehyun Chang, Geun Jin Ahn
  • Patent number: 11921948
    Abstract: A control device includes an exterior panel comprising multiple regions, including a groove region and a surrounding region that surrounds the groove region. The control device further includes a sensor layer comprising one or more sensors to detect touch inputs performed on the groove region and the surrounding region of the exterior panel. The control device further includes a control module configured to operate a plurality of devices. The control module is configured to detect a first touch input performed by a user on the groove region and a second touch input performed on the surrounding region. Based at least in part on the location of the touch inputs the control module operates respective devices of the plurality of devices.
    Type: Grant
    Filed: October 26, 2022
    Date of Patent: March 5, 2024
    Assignee: Brilliant Home Technology, Inc.
    Inventors: Aaron T. Emigh, Steven Stanek, Brian Cardanha, Bozhi See, Iris Yan, Gaurav Hardikar
  • Patent number: 11922280
    Abstract: A method for monitoring performance of a ML system includes receiving a data stream via a processor and generating a first plurality of metrics based on the data stream. The processor also generates input data based on the data stream, and sends the input data to a machine learning (ML) model for generation of intermediate output and model output based on the input data. The processor also generates a second plurality of metrics based on the intermediate output, and a third plurality of metrics based on the model output. An alert is generated based on at least one of the first plurality of metrics, the second plurality of metrics, or the third plurality of metrics, and a signal representing the alert is sent for display to a user via an interface.
    Type: Grant
    Filed: December 9, 2020
    Date of Patent: March 5, 2024
    Assignee: Arthur AI, Inc.
    Inventors: Adam Wenchel, John Dickerson, Priscilla Alexander, Elizabeth O'Sullivan, Keegan Hines
  • Patent number: 11922520
    Abstract: A computer-based method, system, and computer program product for automatically identifying significant events for food traceability. The method may comprise receiving a series of events from an agriculture supply chain entity, automatically determining, at a machine learning model of an event analysis module, one or more events in the series having a significance for food traceability greater than a threshold, and automatically reporting the one or more events to a ledger.
    Type: Grant
    Filed: November 25, 2020
    Date of Patent: March 5, 2024
    Assignee: International Business Machines Corporation
    Inventors: Sushain Pandit, Krishna Teja Rekapalli
  • Patent number: 11923057
    Abstract: A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan and a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session. The computer-implemented system may also include a first computing device configured to: receive treatment data pertaining to the user while the user uses the treatment device to perform the treatment plan; write to an associated memory, for access by an artificial intelligence engine, the treatment data; receive, from the artificial intelligence engine, at least one prediction; identify a threshold corresponding to the at least one prediction; and, in response to a determination that the at least one prediction is outside of the range of the threshold, update the treatment data pertaining to the user to indicate the at least one prediction.
    Type: Grant
    Filed: August 23, 2021
    Date of Patent: March 5, 2024
    Assignee: ROM Technologies, Inc.
    Inventors: Steven Mason, Daniel Posnack, Peter Arn, Wendy Para, S. Adam Hacking, Micheal Mueller, Joseph Guaneri, Jonathan Greene
  • Patent number: 11922424
    Abstract: A computer-implemented method includes: receiving an inquiry request message identifying a first payment transaction having a plurality of transaction parameters and a risk score, where the risk score is generated by a machine-learning model based on the plurality of transaction parameters; for each transaction parameter of the plurality of transaction parameters, perturbing a value of the transaction parameter and re-analyzing the first payment transaction with the machine-learning model to generate a perturbed risk score based on the perturbed transaction parameter; determining at least one impact parameter from the plurality of transaction parameters by comparing the perturbed risk scores generated for each of the plurality of transaction parameters; and generating an inquiry response message based on the at least one impact parameter.
    Type: Grant
    Filed: July 19, 2022
    Date of Patent: March 5, 2024
    Assignee: Visa International Service Association
    Inventors: Shi Cao, Chiranjeet Chetia, Xi Kan, Dan Wang
  • Patent number: 11924759
    Abstract: Disclosed herein is a method of a communication device operating in a wireless communication network for managing power consumption of the device. The device is configured to operate according to first, second and third operational states for communication with a network node associated with the communication network.
    Type: Grant
    Filed: March 18, 2020
    Date of Patent: March 5, 2024
    Assignee: TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)
    Inventors: Ali Nader, Tahmineh Torabian Esfahani
  • Patent number: 11914306
    Abstract: A calibrated lithographic model may be used to generate a lithographic model output based on an integrated circuit (IC) design layout. Next, at least a chemical parameter may be extracted from the lithographic model output. A calibrated defect rate model may then be used to predict a defect rate for the IC design layout based on the chemical parameter.
    Type: Grant
    Filed: October 16, 2020
    Date of Patent: February 27, 2024
    Assignee: Synopsys, Inc.
    Inventors: Erik A. Verduijn, Ulrich Karl Klostermann, Ulrich Welling, Jiuzhou Tang, Hans-Jürgen Stock
  • Patent number: 11914709
    Abstract: Aspects of the disclosure relate to predicting the spread of malicious software. The computing platform may identify malicious software at a computing device and may input characteristics of the malicious software into a machine learning model to produce time horizons for the malicious software. The computing platform may identify, using a knowledge graph and based on the time horizons, subsets of computing devices, each corresponding to a particular time horizon. The computing platform may perform, at a time within a first time horizon, a first security action for a first subset of computing devices within the first time horizon and a second security action for a second subset of computing devices located within a second time horizon, where the first time horizon and the second time horizon indicate that the first subset will be affected by the malicious software prior to the second subset.
    Type: Grant
    Filed: July 20, 2021
    Date of Patent: February 27, 2024
    Assignee: Bank of America Corporation
    Inventors: George Anthony Albero, Maharaj Mukherjee
  • Patent number: 11916855
    Abstract: A file commenting method includes displaying file content in an instant messaging client, displaying comment content entered via a commenting operation performed on a portion of the file content, and displaying a session page when the commenting operation is completed, the session page including the portion of the file content, the comment content, and a file identifier corresponding to the file content.
    Type: Grant
    Filed: March 23, 2022
    Date of Patent: February 27, 2024
    Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: Fen He, Xuejun Sun, Liqiang Liu, Dan He, Jinhui Chen
  • Patent number: 11914918
    Abstract: A medical information processing apparatus comprises an obtaining unit that obtains medical information, a learning unit that performs learning on a function of the medical information processing apparatus using the medical information, an evaluation data holding unit that holds evaluation data in which a correct answer to be obtained by executing the function is known, the evaluation data being for evaluating a learning result of the learning unit, an evaluating unit that evaluates a learning result obtained through learning, based on the evaluation data, and an accepting unit that accepts an instruction to apply a learning result of the learning unit to the function.
    Type: Grant
    Filed: February 1, 2021
    Date of Patent: February 27, 2024
    Assignee: CANON KABUSHIKI KAISHA
    Inventors: Yoshihito Machida, Yoshinori Hirano, Hideaki Miyamoto, Daisuke Yamada
  • Patent number: 11915109
    Abstract: In some embodiments, a method includes generating a trained decision tree with a set of nodes based on input data and a partitioning objective, and generating a modified decision tree by recursively passing the input data through the trained decision tree, recursively calculating, for each of the nodes, an associated set of metrics, and recursively defining an association between each of the nodes and the associated set of metrics. A node from a set of nodes of the modified decision tree is identified that violates a user-specified threshold value, associated with a user, for at least one of the metrics. The method also includes causing transmission of a signal to a compute device of the user, the signal including a representation of the identified node.
    Type: Grant
    Filed: September 15, 2022
    Date of Patent: February 27, 2024
    Assignee: Arthur AI, Inc.
    Inventors: Kenneth S. Chen, Reese Hyde, Keegan E. Hines
  • Patent number: 11916515
    Abstract: A method includes obtaining pairs of in-phase (I) and quadrature (Q) samples associated with a signal to be demodulated. The method also includes providing a set of the I/Q pairs to a trained AI/ML model. The set of the I/Q pairs includes an I/Q pair associated with a symbol being demodulated and at least one I/Q pair associated with at least one prior symbol that has been demodulated. In addition, the method includes using the trained AI/ML model to generate a symbol estimate for the symbol based on the set of the I/Q pairs, where the symbol estimate represents a portion of data that is encoded in the signal.
    Type: Grant
    Filed: February 14, 2022
    Date of Patent: February 27, 2024
    Assignee: Raytheon Company
    Inventors: Jacob M. Miller, H. Brown Cribbs, III
  • Patent number: 11915041
    Abstract: An artificial intelligence (AI) sequencer is provided. The Al sequencer includes a queue manager configured to manage a plurality of queues for maintaining data of AI jobs, wherein an AI job includes processing of one or more AI functions; a scheduler for scheduling execution of data maintained by the plurality of queues; a plurality of job processing units (JPUs), wherein each of the plurality JPUs is configured to at least generate an execution sequence for an AI job; and a plurality of dispatchers connected to a plurality of AI accelerators, wherein each of the plurality of dispatchers is configured to dispatch at least a function of the AI job to an AI accelerator, wherein a function is dispatched to an AI accelerator at an order determined by an execution sequence created for a respective AI job.
    Type: Grant
    Filed: September 11, 2020
    Date of Patent: February 27, 2024
    Assignee: NEUREALITY LTD.
    Inventors: Moshe Tanach, Yossi Kasus
  • Patent number: 11915816
    Abstract: Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, treatment plans for optimizing a user outcome. The method comprises receiving attribute data associated with a user. The attribute data comprises one or more symptoms associated with the user. The method also comprises, while the user uses a treatment apparatus to perform a first treatment plan for the user, receiving measurement data associated with the user. The method further comprises generating, by the artificial intelligence engine configured to use one or more machine learning models, a second treatment plan for the user. The generating is based on at least the attribute data associated with the user and the measurement data associated with the user. The second treatment plan comprises a description of one or more predicted disease states of the user. The method also comprises transmitting, to a computing device, the second treatment plan for the user.
    Type: Grant
    Filed: February 28, 2023
    Date of Patent: February 27, 2024
    Assignee: ROM Technologies, Inc.
    Inventor: Steven Mason
  • Patent number: 11915114
    Abstract: The present teaching relates to method, system, medium, and implementations for machine learning. A training sample is first received from a source. A prediction is generated according to the training sample and based on one or more parameters associated with a model. A metric characterizing the prediction is also determined. The prediction and the metric are transmitted to the source to facilitate a determination on whether a ground truth label for the training sample is to be provided. When the ground truth label is received from the source, the one or more parameters of the model are updated based on the prediction and the ground truth label.
    Type: Grant
    Filed: July 31, 2020
    Date of Patent: February 27, 2024
    Assignee: YAHOO ASSETS LLC
    Inventors: Gal Lalouche, Ran Wolff
  • Patent number: 11907847
    Abstract: An electronic device may determine whether a machine-learning model is operating within predefined limits. In particular, the electronic device may receive, from another electronic device, instructions for the machine-learning model, a reference input and a predetermined output of the machine-learning model for the reference input. Note that the instructions may include an architecture of the machine-learning model, weights associated with the machine-learning model and/or a set of pre-processing transformations for use when executing the machine-learning model on images. In response, the electronic device may configure the machine-learning model based on the instructions. Then, the electronic device may calculate an output of the machine-learning model for the reference input. Next, the electronic device may determine whether the machine-learning model is operating within predefined limits based on the output and the predetermined output.
    Type: Grant
    Filed: February 23, 2021
    Date of Patent: February 20, 2024
    Assignee: Cogniac, Corp
    Inventors: William S Kish, Huayan Wang, Sandip C. Patel
  • Patent number: 11907231
    Abstract: A method is performed at a server system having one or more processors and memory storing instructions for execution by the one or more processors. The server system provides a content service. The method includes providing a first media item for playback based on a request from an application executing on an electronic device. The method includes receiving data associated with a behavior of a first user of the content service. The data associated with the behavior of the first user includes an indication of at least a first user input for controlling the playback of the first media item. The method includes using the received data to provide a media recommendation to the electronic device.
    Type: Grant
    Filed: March 30, 2020
    Date of Patent: February 20, 2024
    Assignee: Spotify AB
    Inventor: Andreas Mattsson
  • Patent number: 11907949
    Abstract: An apparatus for controlling a vehicle includes a memory, a network interface, and a processor, where the processor may check whether a fingerprint recognition module in the vehicle supports fast identity online (FIDO), may request for an encryption key to register the FIDO, may encrypt an input pin code to transmit the encrypted pin code to a financial information processing server, may transmit vehicle and account information for the FIDO registration to a FIDO authentication server when receiving an authentication token from the financial information processing server, may generate information on the FIDO registration when receiving policy information from the FIDO authentication server, and may transmit the information on the FIDO registration to the FIDO authentication server.
    Type: Grant
    Filed: July 11, 2022
    Date of Patent: February 20, 2024
    Assignees: Hyundai Motor Company, Kia Corporation
    Inventors: Yong Woo Shin, Min Woo Lee
  • Patent number: 11907226
    Abstract: A computer-implemented method, a computer system and a computer program product create rules for a rule-based natural language interface for databases (NLIDB). The method may include receiving a natural language query from a user. The method may also include generating a first explanation for the natural language query using a deep learning model and a second explanation for the natural language query using the rule-based NLIDB and validating whether the first and second explanations correctly represent the natural language query. The method may further include identifying the database value in the first explanation in response to the first explanation correctly representing the natural language query and the second explanation not correctly representing the natural language query. Lastly, the method may include creating a rule in a table for the rule-based natural language interface for databases that associates the database value with the original word of the natural language query.
    Type: Grant
    Filed: March 21, 2022
    Date of Patent: February 20, 2024
    Assignee: International Business Machines Corporation
    Inventors: Ngoc Phuoc An Vo, Vadim Sheinin, Elahe Khorasani, Hangu Yeo
  • Patent number: 11907862
    Abstract: Systems, methods, and apparatuses are described herein for performing sentiment analysis on electronic communications relating to one or more image-based communications methods, such as emoji. Message data may be received. The message data may correspond to a message that is intended to be sent but has not yet been sent to an application. Using a first machine learning model, one or more subsets of the plurality of emoji may be determined. The one or more subsets of the plurality of emoji may comprise one or more different types and quantities of emoji, and may each correspond to the same or a different sentiment. Using a second machine learning model, one or more emojis may be selected from the one or more subsets. The one or more emojis selected may correspond to responses to the message.
    Type: Grant
    Filed: May 10, 2023
    Date of Patent: February 20, 2024
    Assignee: Capital One Services, LLC
    Inventors: Kevin Osborn, Eric Loucks, Joshua Edwards, George Bergeron, Kyle Johnson, Brian Lee
  • Patent number: 11907810
    Abstract: Certain aspects of the present disclosure provide techniques for concurrently performing inferences using a machine learning model and optimizing parameters used in executing the machine learning model. An example method generally includes receiving a request to perform inferences on a data set using the machine learning model and performance metric targets for performance of the inferences. At least a first inference is performed on the data set using the machine learning model to meet a latency specified for generation of the first inference from receipt of the request. While performing the at least the first inference, operational parameters resulting in inference performance approaching the performance metric targets are identified based on the machine learning model and operational properties of the computing device. The identified operational parameters are applied to performance of subsequent inferences using the machine learning model.
    Type: Grant
    Filed: July 18, 2019
    Date of Patent: February 20, 2024
    Assignee: QUALCOMM Incorporated
    Inventors: Serag Gadelrab, James Esliger, Meghal Varia, Kyle Ernewein, Alwyn Dos Remedios, George Lee
  • Patent number: 11907860
    Abstract: Targeted acquisition of data for model training includes automatically generating metadata describing samples, of an initial dataset, in neighborhoods of an embedding space in which the samples are embedded. The samples described by the automatically generated metadata are classified by a classification model, and include both correctly classified samples in the neighborhoods and incorrectly classified samples in the neighborhoods. Additionally, attributes of one or more correctly classified samples of the collection of samples and one or more incorrectly classified samples of the collection of samples are identified, and queries are generated based on the identified attributes, the queries tailored, based on the attributes, to retrieve additional training data for training the classification model to more accurately classify samples and avoid incorrect sample classification.
    Type: Grant
    Filed: September 26, 2022
    Date of Patent: February 20, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Namit Kabra, Ritesh Kumar Gupta, Vijay Ekambaram, Smitkumar Narotambhai Marvaniya
  • Patent number: 11907334
    Abstract: A first classification is received from a neural network regarding a training dataset sent to the neural network. A modified training dataset with a perturbation of the training dataset is identified, where this modified training dataset causes the neural network to return a second classification. The perturbation is analyzed to identify a negative rule of the neural network.
    Type: Grant
    Filed: December 8, 2020
    Date of Patent: February 20, 2024
    Assignee: International Business Machines Corporation
    Inventors: Franck Vinh Le, Mudhakar Srivatsa
  • Patent number: 11907663
    Abstract: A system includes: a natural language processing (NLP) model trained in a training domain and configured to perform natural language processing on an input dataset; an accuracy module configured to: calculate a domain shift metric based on the input dataset; and calculate a predicted decrease in accuracy of the NLP model attributable to domain shift relative to the training domain based on the domain shift metric; and a retraining module configured to selectively trigger a retraining of the NLP model based on the predicted decrease in accuracy of the NLP model.
    Type: Grant
    Filed: April 26, 2021
    Date of Patent: February 20, 2024
    Assignee: NAVER FRANCE
    Inventors: Matthias Galle, Hady Elsahar
  • Patent number: 11900272
    Abstract: A method and system for mapping labels of documents is described. A training set including a plurality of documents and at least one map can be retrieved. Each document can include a plurality of labels, and the at least one map can represent associations between the labels of one document and another document in the set. Each document (or group of documents) in the set can include certain features. These features can relate to the labels in the documents. Each label can correspond to one or more data points (or datasets) in each documents. In one example embodiment, the map can be generated based on the features extracted from each document.
    Type: Grant
    Filed: May 13, 2020
    Date of Patent: February 13, 2024
    Assignee: FACTSET RESEARCH SYSTEM INC.
    Inventors: Yan Chen, Agrima Srivastava, Dakshina Murthy Malladi
  • Patent number: 11902181
    Abstract: A computer-implemented method, a computer program product, and a computer system for managing permissions in cloud computing. A computer detects n times of attempts of an action in cloud computing, where the n times of attempts are initiated by a user who has no permission to perform the action, where n is a predetermined number triggering generation of a request for a permission to perform the action. A computer generates the request for the permission for the user. A computer determines whether the request has been pre-approved. In response to determining that the request has been pre-approved, a computer automatically approves the request. In response to determining that the request has not been pre-approved, a computer adds metadata about the user to the request and sends the request with the metadata to a cloud administrator, where the cloud administrator approves or denies the request based on the metadata.
    Type: Grant
    Filed: April 3, 2023
    Date of Patent: February 13, 2024
    Assignee: International Business Machines Corporation
    Inventors: Paritosh Ranjan, Lamogha Chiazor