Patents Examined by Viker A Lamardo
  • Patent number: 10311368
    Abstract: A computing device provides a cluster connectivity graph presented on a display to summarize machine learning model performance. A classification value is predicted is predicted for a response variable value of each observation vector using a trained model. Observation vectors are divided into overlapping data slices that are separately clustered using the predicted classification value to define a set of clusters. A number of observations in each cluster is computed. An accuracy measure is computed for each cluster based on the predicted classification value. A number of overlapping observations between each pair of clusters is computed. The cluster connectivity graph includes a node for each cluster. A size of each node is determined from the computed number of observations. A fill-pattern of each node is determined from the computed accuracy measure. A connector line between each pair of nodes is determined from the computed number of overlapping observations.
    Type: Grant
    Filed: March 22, 2018
    Date of Patent: June 4, 2019
    Assignee: SAS INSTITUTE INC.
    Inventors: Namita Dilip Lokare, Jorge Manuel Gomes da Silva, Ilknur Kaynar Kabul, Gregory Naisat
  • Patent number: 10311356
    Abstract: An unsupervised behavior learning system and method for predicting anomalies in a distributed computing infrastructure. The distributed computing infrastructure includes a plurality of computer machines. The system includes a first computer machine and a second computer machine. The second computer machine is configured to generate a model of normal and anomalous behavior of the first computer machine, where the model is based on unlabeled training data. The second computer machine is also configured to acquire real-time data of system level metrics of the first machine; determine whether the real-time data is normal or anomalous based on a comparison of the real-time data to the model; and predict a future failure of the first computer machine based on multiple consecutive comparisons of the real-time data to the model.
    Type: Grant
    Filed: September 8, 2014
    Date of Patent: June 4, 2019
    Assignee: North Carolina State University
    Inventors: Xiaohui Gu, Daniel Dean
  • Patent number: 10296160
    Abstract: Systems and processes are disclosed for virtual assistant request recognition using live usage data and data relating to future events. User requests that are received but not recognized can be used to generate candidate request templates. A count can be associated with each candidate request template and can be incremented each time a matching candidate request template is received. When a count reaches a threshold level, the corresponding candidate request template can be used to train a virtual assistant to recognize and respond to similar user requests in the future. In addition, data relating to future events can be mined to extract relevant information that can be used to populate both recognized user request templates and candidate user request templates. Populated user request templates (e.g., whole expected utterances) can then be used to recognize user requests and disambiguate user intent as future events become relevant.
    Type: Grant
    Filed: December 6, 2013
    Date of Patent: May 21, 2019
    Assignee: APPLE INC.
    Inventors: Rushin N. Shah, Devang K. Naik
  • Patent number: 10289956
    Abstract: A method for updating a factor graph (10;10?;10?) of an a posteriori probability estimator, the factor graph including at least one repetition node (13;13?;13?) and at least one sum node (11;11?;11?), wherein at least two connections are associated with each node, and wherein each connection is associated with an incoming message at the node and with an outgoing message from the node, wherein the method includes the steps of: storing the nodes' incoming and outgoing messages into memory (12;12?;12?) of the estimator as messages belonging to one same class of wrapped and/or sampled Gaussian messages; updating the node of the factor graph (10;10?;10?) by using a resulting message belonging to the class of incoming messages, the resulting message being obtained by processing the incoming wrapped and/or sampled Gaussian messages.
    Type: Grant
    Filed: May 31, 2012
    Date of Patent: May 14, 2019
    Assignee: POLITECNICO DI TORINO
    Inventor: Guido Montorsi
  • Patent number: 10275711
    Abstract: The present invention relates to methods, systems and apparatus for capturing, integrating, organizing, navigating and querying large-scale data from high-throughput biological and chemical assay platforms. It provides a highly efficient meta-analysis infrastructure for performing research queries across a large number of studies and experiments from different biological and chemical assays, data types and organisms, as well as systems to build and add to such an infrastructure.
    Type: Grant
    Filed: August 17, 2012
    Date of Patent: April 30, 2019
    Assignee: Nextbio
    Inventors: Ilya Kupershmidt, Qiaojuan Jane Su, Francois Andry
  • Patent number: 10169720
    Abstract: Systems and methods are provided for performing data mining and statistical learning techniques on a big data set. More specifically, systems and methods are provided for linear regression using safe screening techniques. Techniques may include receiving a plurality of time series included in a prediction hierarchy for performing statistical learning to develop an improved prediction hierarchy. It may include pre-processing data associated with each of the plurality of time series, wherein the pre-processing includes tasks performed in parallel using a grid-enabled computing environment. For each time series, the system may determine a classification for the individual time series, a pattern group for the individual time series, and a level of the prediction hierarchy at which the each individual time series comprises an need output amount greater than a threshold amount.
    Type: Grant
    Filed: December 16, 2016
    Date of Patent: January 1, 2019
    Assignee: SAS INSTITUTE INC.
    Inventors: Yung-Hsin Chien, Pu Wang, Yue Li
  • Patent number: 10152677
    Abstract: A mechanism is provided in a stream computing platform for data stream change detection and model swapping. The mechanism builds a model for each input data stream in a stream computing platform. Each tuple of each given input data stream is tagged with a key corresponding to the given input data stream. The mechanism performs an operation on each input data stream using its corresponding model. The mechanism detects a misdirected input data stream, which is tagged with a key that does not correspond to the misdirected input data stream. The mechanism pauses the misdirected input data stream swaps a model corresponding to the misdirected input data stream with another model corresponding to another paused input data stream.
    Type: Grant
    Filed: June 18, 2015
    Date of Patent: December 11, 2018
    Assignee: International Business Machines Corporation
    Inventors: Alain E. Biem, Dattaram Bijavara Aswathanarayana Rao, Bharath K. Devaraju
  • Patent number: 10147046
    Abstract: A mechanism is provided in a stream computing platform for data stream change detection and model swapping. The mechanism builds a model for each input data stream in a stream computing platform. Each tuple of each given input data stream is tagged with a key corresponding to the given input data stream. The mechanism performs an operation on each input data stream using its corresponding model. The mechanism detects a misdirected input data stream, which is tagged with a key that does not correspond to the misdirected input data stream. The mechanism pauses the misdirected input data stream swaps a model corresponding to the misdirected input data stream with another model corresponding to another paused input data stream.
    Type: Grant
    Filed: October 30, 2014
    Date of Patent: December 4, 2018
    Assignee: International Business Machines Corporation
    Inventors: Alain E. Biem, Dattaram Bijavara Aswathanarayana Rao, Bharath K. Devaraju
  • Patent number: 10095660
    Abstract: Various embodiments are generally directed to techniques for producing statistically correct and efficient combinations of multiple simulated posterior samples from MCMC and related Bayesian sampling schemes are described. One or more chains from a Bayesian posterior distribution of values may be generated. It may be determine whether the one or more chains have reached stationarity through parallel processing on a plurality of processing nodes. Based upon the determination, each of the one or more chains that have reached stationarity through parallel processing on the plurality of processing nodes may be sorted. The one or more sorted chains may be resampled through parallel processing on the plurality of processing nodes. The one or more resampled chains may be combined. Other embodiments are described and claimed.
    Type: Grant
    Filed: March 13, 2014
    Date of Patent: October 9, 2018
    Assignee: SAS Institute Inc.
    Inventors: Christian Macaro, Jan Chvosta, Mark Roland Little
  • Patent number: 10075510
    Abstract: Content on a client device is updated. Analytics data describing how a user uses the client device to consume digital content are received. The analytics data are generated by the client device responsive to observations of how the user uses the client device to consume digital content. A prediction model is generated based on the analytics data and used to predict when the user will consume digital content on the client device. Prediction data describing the prediction are provided to the client device. The client device uses the prediction data to request updated digital content prior to when the user is predicted to consume digital content on the client device.
    Type: Grant
    Filed: March 13, 2014
    Date of Patent: September 11, 2018
    Assignee: Google LLC
    Inventors: James Reilly, Sami Mohammed Shalabi, Mehul Agarwal, Michael Scott Depinet
  • Patent number: 10049162
    Abstract: A system and method for processing information in unstructured or structured form, comprising a computer running in a distributed network with one or more data agents. Associations of natural language artifacts may be learned from natural language artifacts in unstructured data sources, and semantic and syntactic relationships may be learned in structured data sources, using grouping based on a criteria of shared features that are dynamically determined without the use of a priori classifications, by employing conditional probability constraints.
    Type: Grant
    Filed: November 6, 2015
    Date of Patent: August 14, 2018
    Assignee: Digital Reasoning Systems, Inc.
    Inventor: Timothy W. Estes
  • Patent number: 9773044
    Abstract: Method, system, and computer program product to analyze a plurality of candidate answers identified as responsive to a question presented to a deep question answering system, by computing a first feature score for a first feature of an item of evidence, of a plurality of items of evidence, the first feature score being based on at least one attribute of the first feature, the item of evidence relating to a first candidate answer, of the plurality of candidate answers, and computing a merged feature score for the first candidate answer by applying the first feature score to a second feature score for a second feature of the item of evidence.
    Type: Grant
    Filed: March 11, 2013
    Date of Patent: September 26, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Joel C. Dubbels, Thomas J. Eggebraaten, Mark G. Megerian, William C. Rapp, Richard J. Stevens, Patrick M. Wildt, Eric W. Will
  • Patent number: 9754215
    Abstract: System, method, and computer program product to identify relevant features in a deep question answering system, by classifying a first case received by the deep question answering system, and, while training the deep question answering system to answer the first case, identifying a first feature in the first case, computing a first feature score for the first feature, the first feature score indicating a relevance of the first feature in generating a correct response to the first case, and, identifying the first feature as relevant in answering the classified first case upon determining that the first feature score exceeds a relevance threshold.
    Type: Grant
    Filed: December 17, 2012
    Date of Patent: September 5, 2017
    Assignee: SINOEAST CONCEPT LIMITED
    Inventors: Adam T. Clark, Mark G. Megerian, John E. Petri, Richard J. Stevens
  • Patent number: 9753986
    Abstract: Method, system, and computer program product to analyze a plurality of candidate answers identified as responsive to a question presented to a deep question answering system, by computing a first feature score for a first feature of an item of evidence, of a plurality of items of evidence, the first feature score being based on at least one attribute of the first feature, the item of evidence relating to a first candidate answer, of the plurality of candidate answers, and computing a merged feature score for the first candidate answer by applying the first feature score to a second feature score for a second feature of the item of evidence.
    Type: Grant
    Filed: December 17, 2012
    Date of Patent: September 5, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Joel C. Dubbels, Thomas J. Eggebraaten, Mark G. Megerian, William C. Rapp, Richard J. Stevens, Patrick M. Wildt, Eric W. Will
  • Patent number: 9704102
    Abstract: A mechanism for discerning user preferences for categories of provided content. A computer receives response data including a set of preference values that have been assigned to content items by content users. Output data is computed based on the response data using a latent factor model. The output data includes at least: an association matrix that defines K concepts associated with the content items, wherein K is smaller than the number of the content items, wherein, for each of the K concepts, the association matrix defines the concept by specifying strengths of association between the concept and the content items; and a concept-preference matrix including, for each content user and each of the K concepts, an extent to which the content user prefers the concept. The computer may display a visual representation of the association strengths in the association matrix and/or the extents in the concept-preference matrix.
    Type: Grant
    Filed: March 15, 2014
    Date of Patent: July 11, 2017
    Assignee: William Marsh Rice University
    Inventors: Richard G. Baraniuk, Andrew S. Lan, Christoph E. Studer, Andrew E. Waters
  • Patent number: 9648016
    Abstract: Embodiments of a system and methods for predictive transmission of information are generally described herein. In some embodiments, a system includes a ground moving target indicator (GMTI) tracker module receives a current position estimate from a user equipment and to generate position and/or velocity estimates. A database system, including a mission/role database and user information database, receives the position and/or velocity estimates and transmits user information to the user equipment based on a predicted position of the user and the mission/role of a user.
    Type: Grant
    Filed: January 22, 2014
    Date of Patent: May 9, 2017
    Assignee: Raytheon Company
    Inventors: Susan N. Gottschlich, Raimund Merkert
  • Patent number: 9563854
    Abstract: In one embodiment, a device determines that a machine learning model is to be trained by a plurality of devices in a network. A set of training devices are identified from among the plurality of devices to train the model, with each of the training devices having a local set of training data. An instruction is then sent to each of the training devices that is configured to cause a training device to receive model parameters from a first training device in the set, use the parameters with at least a portion of the local set of training data to generate new model parameters, and forward the new model parameters to a second training device in the set. Model parameters from the training devices are also received that have been trained using a global set of training data that includes the local sets of training data on the training devices.
    Type: Grant
    Filed: January 27, 2014
    Date of Patent: February 7, 2017
    Assignee: Cisco Technology, Inc.
    Inventors: Javier Cruz Mota, Jean-Philippe Vasseur, Andrea Di Pietro
  • Patent number: 9454732
    Abstract: Some examples include receiving data from a source external to an adaptive machine learning platform that includes at least one machine learning component. Some implementations may execute a machine learning component to generate a machine learning component output. The machine learning component output may be generated at least in part based on the received data. A command may be generated based at least in part on the machine learning component output, and the command may be communicated to an action plugin. The action plugin manager may be used to configure one or more parameters of an action representing an automated workflow to be executed by the action plugin in response to receiving the command.
    Type: Grant
    Filed: November 21, 2012
    Date of Patent: September 27, 2016
    Assignee: Amazon Technologies, Inc.
    Inventors: Lian R. Garton, Luhui Hu
  • Patent number: 9449273
    Abstract: A method includes maintaining descriptions of a plurality of information technology resources in a computer-readable storage medium. The method includes maintaining a plurality of evaluation strategies, wherein the evaluation strategies associate a plurality of rules with forms of changes to the plurality of information technology resources. Responsive to detecting a command to change a first property of the set of properties of a first information technology resource of the plurality of information technology resources, the method determines that a first of the evaluation strategies associates at least one of the plurality of rules with a form of the change to the first property of the first information technology resource. Also, responsive to detecting the command, the method evaluates the at least one of the plurality of rules and performs the operation of the at least one rule.
    Type: Grant
    Filed: April 30, 2012
    Date of Patent: September 20, 2016
    Assignee: International Business Machines Corporation
    Inventors: Gerd Breiter, Dominik Jall, Markus Mueller, Alexander Neef, Martin Reitz
  • Patent number: 9390404
    Abstract: One feature pertains to a computer-readable storage medium having instructions for generating group solutions stored thereon, the instructions when executed by at least one processor causes the processor to receive a plurality of solution statements from a plurality of users, determine that two or more solution statements of the plurality of solution statements are positively and significantly correlated with each other, and generate a group solution that includes the two or more solution statements determined to be positively and significantly correlated with each other. The two or more solution statements having the positive and significant correlation tending to be included concurrently in the plurality of solution statements received from the plurality of users.
    Type: Grant
    Filed: November 10, 2014
    Date of Patent: July 12, 2016
    Assignee: GROUPSOLVER, INC.
    Inventors: Rastislav Ivanic, Maros Ivanic