Patents Examined by Paulinho E Smith
  • Patent number: 11017324
    Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for optimizing machine-learned tree ensemble prediction systems are presented. A plurality of instances may be processed by a tree ensemble. Determinations regarding the expected output values of one or more nodes of the tree ensemble may be made based, at least in part, on the processed instances. Further determinations regarding the node contribution values of one or more nodes of the tree ensemble to downstream nodes may be made based on the node output values. In some examples, feature value ranges may be computed for one or more features of the tree ensemble. One or more tree ensemble optimization operations may be performed based on the information determined from one or more of the above-described operations.
    Type: Grant
    Filed: May 17, 2017
    Date of Patent: May 25, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Alexander V. Moore, Yaxiong Cai, Kristine E. Jones
  • Patent number: 11017303
    Abstract: Techniques are provided for accurately and quickly processing distributed stored objects to provide a timely and accurate prediction of the number of live objects a parameterized file request will produce. Stored objects representing previous user webpage visit interactions are stored in different storage locations in a data store. The stored objects at each storage location are processed in parallel by hashing stored objects with a hash function such that they are spread somewhat uniformly into buckets. Sub-buckets in each bucket are formed that correspond to selected category identifiers. Also in parallel, K-minimum values are computed for each sub-bucket to estimate the count of stored objects in the data store. The K-minimum values for sub-buckets corresponding to the same category ID across all buckets are combined, in some cases harmonically, and used to generate a predicted number of live objects responsive to a parameterized file request.
    Type: Grant
    Filed: October 24, 2017
    Date of Patent: May 25, 2021
    Assignee: Oracle International Corporation
    Inventors: Adison H. Wongkar, Padmanabhan Natarajan, Jeevan Gheevarghese Joseph, Kendra Mariko Chen, Vernon W. Hui
  • Patent number: 11017294
    Abstract: A method of recognizing input data includes determining a feature vector corresponding to an ensemble model from input data, based on the ensemble model, and recognizing the input data based on the feature vector. The ensemble model includes a first model and a second model having a structure that is the same as a structure of the first model.
    Type: Grant
    Filed: May 3, 2017
    Date of Patent: May 25, 2021
    Assignee: Samsung Electronics Co., Ltd.
    Inventor: Hwidong Na
  • Patent number: 10997500
    Abstract: The present disclosure is directed to generating neural network (NN) output using input data representing various types of events, such as input representing a certain type of event and also an engagement metric that may be representative of a property of the event or representative of a related but different type of event. For example, the output values generated using the NN may be associated with the likelihood that certain future events will occur, given the occurrence of certain past or current events. The output can then be modified (e.g., re-ranked, adjusted, etc.) based on the occurrence of certain other past or current events.
    Type: Grant
    Filed: May 23, 2017
    Date of Patent: May 4, 2021
    Assignee: Amazon Technologies, Inc.
    Inventors: FNU Vishnu Narayanan, Oleg Rybakov, Siddharth Singh
  • Patent number: 10991451
    Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.
    Type: Grant
    Filed: August 21, 2018
    Date of Patent: April 27, 2021
    Assignee: The Regents of the University of California
    Inventors: John Zachary Sanborn, David Haussler
  • Patent number: 10990874
    Abstract: Systems, software, and computer implemented methods can be used to predict wildfires based on biophysical and spatiotemporal data. A method includes receiving a request for a wildfire prediction for at least one geographical area. At least one biophysical indicator is identified. Each biophysical indicator provides biophysical data for the at least one geographical area. The at least one biophysical indicator is provided to a convolutional neural network (CNN). The CNN is trained using ground truth data that includes historical information about wildfires for at least one ground truth geographical area. The CNN is used to generate at least one prediction for wildfire risk for the at least one geographical area. The at least one prediction is provided responsive to the request.
    Type: Grant
    Filed: May 22, 2017
    Date of Patent: April 27, 2021
    Assignee: SAP SE
    Inventors: Vadim Tschernezki, Oliver Blum, Hinnerk Gildhoff, Michèle Wyss, Bjoern Deiseroth, Wenzel Svojanovsky
  • Patent number: 10984310
    Abstract: The present disclosure provides systems and methods that leverage machine-learned models (e.g., neural networks) to provide enhanced communication assistance. In particular, the systems and methods of the present disclosure can include or otherwise leverage a machine-learned communication assistance model to detect problematic statements included in a communication and/or provide suggested replacement statements to respectively replace the problematic statements. In one particular example, the communication assistance model can include a long short-term memory recurrent neural network that detects an inappropriate tone or unintended meaning within a user-composed communication and provides one or more suggested replacement statements to replace the problematic statements.
    Type: Grant
    Filed: December 2, 2019
    Date of Patent: April 20, 2021
    Assignee: Google LLC
    Inventors: Thomas Deselaers, Victor Carbune, Pedro Gonnet Anders, Daniel Martin Keysers
  • Patent number: 10970637
    Abstract: A computer-implemented method for optimizing research of an abstracted issue with a plurality of analytics engines is described. The method includes receiving a problem report at an analytics engine controller. The problem report includes symptoms of a problem in a computing system. The analytics engine forwards the problem report to a research optimization engine that abstracts one or more issues associated with the problem based on the symptoms of the problem. The research optimization engine then obtains anomaly research data for one or more of diagnosing the problem and fixing the problem. The anomaly research data is based on the one or more abstracted issues. The research optimization engine associates the abstracted issues with corresponding portions of the anomaly research data, then assigns the abstracted issues and corresponding portions of the anomaly research data to at least one of the plurality of analytics engines.
    Type: Grant
    Filed: May 16, 2017
    Date of Patent: April 6, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Al Chakra, Michael P. Clarke, Matt R. Hogstrom
  • Patent number: 10971248
    Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.
    Type: Grant
    Filed: August 21, 2018
    Date of Patent: April 6, 2021
    Assignee: The Regents of the University of California
    Inventors: John Zachary Sanborn, David Haussler
  • Patent number: 10963815
    Abstract: The systems and methods described herein include training a well performance predictor based on field data corresponding to a hydrocarbon field in which a well is to be drilled; generating a number of candidate well parameter combinations for the well and predicting a performance of the well for each candidate well parameter combination using the trained well performance predictor; and determining an optimized well parameter combination for the well such that the predicted performance of the well is maximized.
    Type: Grant
    Filed: March 13, 2018
    Date of Patent: March 30, 2021
    Assignee: ExxonMobil Upstream Research Company
    Inventors: Damian N. Burch, Antonio R. C. Paiva, Rainer van den Bosch
  • Patent number: 10958422
    Abstract: Embodiments disclosed herein relate to methods and systems for disseminating reasoning supporting insights made with uniquely identifiable data without disclosing the uniquely identifiable data.
    Type: Grant
    Filed: June 1, 2017
    Date of Patent: March 23, 2021
    Assignee: COTIVITI, INC.
    Inventors: Christopher Taylor Creel, William Paige Vestal, Christopher Shawn Watson
  • Patent number: 10949755
    Abstract: An apparatus that extracts an explanatory variable used as a condition from a classification model classified by the condition for selecting a component used for prediction, displays the explanatory variable in association with any of dimensional axes of a multi-dimensional space in which a prediction value is displayed, specifies the component that corresponds to a position in the multi-dimensional space specified by each of the explanatory variables associated with the dimensional axis, displays the prediction value calculated based on the specified component, on the same position and displays the multi-dimensional space that corresponds to the position in which the prediction value is displayed, in a mode that corresponds to the component used for calculating the prediction value.
    Type: Grant
    Filed: January 18, 2016
    Date of Patent: March 16, 2021
    Assignee: NEC CORPORATION
    Inventors: Yuki Chiba, Yousuke Motohashi, Ryohei Fujimaki, Satoshi Morinaga
  • Patent number: 10943182
    Abstract: A machine learning process is performed using one or more sources of information for enhanced oil recovery (EOR) materials to be used for an EOR process on a defined oil reservoir. Performance of the machine learning process produces an output comprising an indication of one or more EOR materials and their corresponding concentrations to be used in the EOR process. The indication of the one or more EOR materials and their corresponding concentrations is output to be used in the EOR process. Methods, apparatus, and computer program products are disclosed.
    Type: Grant
    Filed: March 27, 2017
    Date of Patent: March 9, 2021
    Assignee: International Business Machines Corporation
    Inventors: Peter W. Bryant, Rodrigo Neumann Barros Ferreira, Ronaldo Giro, Mathias B. Steiner
  • Patent number: 10936968
    Abstract: A method includes receiving, at a processor, ticket data representing a ticket. The method further includes receiving, at the processor, description data representing a description of the ticket. The method further includes calculating, based on the description data, a first probability that the ticket corresponds to a first category and a second probability that the ticket corresponds to a second category. The method further includes determining an entropy value associated with routing the ticket data. The method further includes, in response to the entropy value satisfying a threshold and the first probability exceeding the second probability, routing the ticket data to a device associated with the first category.
    Type: Grant
    Filed: May 5, 2017
    Date of Patent: March 2, 2021
    Assignee: ServiceNow, Inc.
    Inventors: Frank Wall Elliott, Jr., Fernando Ros, Carmine Mangione-Tran
  • Patent number: 10922623
    Abstract: Systems and methods provide capacity planning, management, and engineering automation in networks including virtualization.
    Type: Grant
    Filed: April 18, 2017
    Date of Patent: February 16, 2021
    Assignee: AT&T Intellectual Property I, L.P.
    Inventors: Chuxin Chen, David Kinsey, George Dome, John Getting
  • Patent number: 10902026
    Abstract: A class may be determined of a term from a database. The term may be blocked from being presented to a user, if the determined class does not include a permission for the user to view the term. The term may suggest a remainder of an incomplete query input by the user.
    Type: Grant
    Filed: November 27, 2014
    Date of Patent: January 26, 2021
    Assignee: LONGSAND LIMITED
    Inventors: Daniel Lau, Lewis Mackay, Daniel Timms
  • Patent number: 10892055
    Abstract: An apparatus generates motor function estimation information by performing a process including calculating, using a sensor value of a subject, a feature vector corresponding to a feature value of a feature in a time segment, acquiring a first weight vector using the feature vector and a motor ability value of the subject, calculating a gradient vector with respect to the feature vector, determining a new time segment in the predetermined time period and a new feature value based on the new time segment, calculating, using the sensor value, a feature candidate vector corresponding to a feature value of the new feature in the new time segment, determining a feature candidate vector satisfying a predetermined condition associated with a gradient vector based on a difference between the feature candidate vector and the feature vector, and correcting the first weight vector to a second weight vector using the feature candidate vector.
    Type: Grant
    Filed: August 2, 2017
    Date of Patent: January 12, 2021
    Assignee: PANASONIC INTELLECTUAL PROPERTY MANAGEMENT CO., LTD.
    Inventors: Yoshikuni Sato, Toru Nakada, Yoshihide Sawada
  • Patent number: 10885424
    Abstract: A neural system comprises multiple neurons interconnected via synapse devices. Each neuron integrates input signals arriving on its dendrite, generates a spike in response to the integrated input signals exceeding a threshold, and sends the spike to the interconnected neurons via its axon. The system further includes multiple noruens, each noruen is interconnected via the interconnect network with those neurons that the noruen's corresponding neuron sends its axon to. Each noruen integrates input spikes from connected spiking neurons and generates a spike in response to the integrated input spikes exceeding a threshold. There can be one noruen for every corresponding neuron. For a first neuron connected via its axon via a synapse to dendrite of a second neuron, a noruen corresponding to the second neuron is connected via its axon through the same synapse to dendrite of the noruen corresponding to the first neuron.
    Type: Grant
    Filed: November 13, 2017
    Date of Patent: January 5, 2021
    Assignee: International Business Machines Corporation
    Inventor: Dharmendra S. Modha
  • Patent number: 10878940
    Abstract: A method and associated systems for using machine-learning methods to perform linear regression on a DNA-computing platform. One or more processors generate and initialize beta coefficients of a system of linear equations. These initial values are encoded into nucleobase chains that are then padded to a standard length. The chains are allowed to bind with complementary template chains in a DNA-computing reaction, and the resulting DNA molecules are decoded to reveal the relative the relative likelihood of each chain to bind. The initial values of the beta coefficients are weighted proportionally to these likelihoods, and the process is repeated iteratively until the beta coefficients converge to optimal values.
    Type: Grant
    Filed: June 12, 2019
    Date of Patent: December 29, 2020
    Assignee: International Business Machines Corporation
    Inventors: Aaron K. Baughman, Jennifer McDonough, Sathya Santhar, Craig M. Trim
  • Patent number: 10861028
    Abstract: In some implementations, a computing device determines an event timeline that comprises one or more finance-related events associated with a person. A production classifier may be used to determine (i) an individual contribution of each event in the event timeline to a financial capacity of the person and (ii) a first decision regarding whether to extend credit to the person. A bias monitoring classifier may, based on the event timeline, determine a second decision whether to extend credit to the person. The bias monitoring classifier may be trained using pseudo-unbiased data. If a difference between the first decision and the second decision satisfies a threshold, the production classifier may be modified to reduce bias in decisions made by the production classifier.
    Type: Grant
    Filed: May 15, 2017
    Date of Patent: December 8, 2020
    Assignee: Cerebri AI Inc.
    Inventors: Gabriel M. Silberman, Michael Louis Roberts, Jean Belanger, Karen Bennet