Patents Assigned to SAS Institute Inc.
  • Patent number: 11080602
    Abstract: A computing system trains a reinforcement learning model comprising multiple different attention model components. The reinforcement learning model trains on training data of a first environment (e.g., a first traffic intersection). The reinforcement learning model trains by training a state attention computer model on the training data that weighs each of respective inputs of a respective state. The reinforcement learning model trains by training an action attention computer model that determines a probability of switching from a first action to a second action of the first set of the multiple candidate actions (e.g., changing traffic colors of traffic lights). Alternatively, or additionally, a computing system generates an indication of a selected outcome according to the reinforcement learning model and sends a selection output to the second environment (e.g., a second traffic intersection with more lanes than the first traffic intersection) to implement the selected action in the second environment.
    Type: Grant
    Filed: February 17, 2021
    Date of Patent: August 3, 2021
    Assignee: SAS Institute Inc.
    Inventors: Afshin Oroojlooyjadid, Mohammadreza Nazari, Davood Hajinezhad, Jorge Manuel Gomes da Silva
  • Patent number: 11074412
    Abstract: A system trains a classification model. Text windows are defined from tokens based on a window size. A network model including a transformer network is trained with the text windows to define classification information. A first accuracy value is computed. (A) The window size is reduced using a predefined reduction factor value. (B) Second text windows are defined based on the reduced window size. (C) Retrain the network model with the second text windows to define classification information. (D) A second accuracy value is computed. (E) An accuracy reduction value is computed from the second accuracy value relative to the first accuracy value. When the computed accuracy reduction value is ?an accuracy reduction tolerance value, repeat (A)-(E) until the accuracy reduction value is <the accuracy reduction tolerance value. Otherwise, increase the window size, define final text windows based on the increased window size, and retrain the network model.
    Type: Grant
    Filed: March 16, 2021
    Date of Patent: July 27, 2021
    Assignee: SAS Institute Inc.
    Inventors: Samuel Paul Leeman-Munk, James Allen Cox, David Blake Styles, Richard Welland Crowell
  • Patent number: 11074483
    Abstract: A computing system receives a request to validate, according to a validation specification, a response of a system of operation. The validation specification relates to determining deviation from a specified result in response to testing one or more candidate inputs. The initial design space defines design points for the system of operation according to the respective candidate inputs for each factor. The computing system, responsive to the request to validate the response of the system of operation, generates data representing a covering array for design points defined by the initial design space or a subset design space. The computing system generates, based on the data, a test suite for testing the system of operation. The computing system obtains the response of the system of operation and generates an output indicating the deviation from the specified result.
    Type: Grant
    Filed: October 19, 2020
    Date of Patent: July 27, 2021
    Assignee: SAS Institute Inc.
    Inventors: Joseph Albert Morgan, Ryan Adam Lekivetz, Caleb Bridges King, Bradley Allen Jones
  • Publication number: 20210224051
    Abstract: An apparatus includes a processor to: use an identifier of a requesting device or operator thereof to identify federated area(s) to which access is authorized; based on data dependencies among a set of tasks of a job flow, derive an order of performance specifying the first task to be performed; store, within a task queue, a task routine execution request message including an identifier associated with the first task, and federated area identifier(s) of the identified federated area(s); within a resolver container, in response to storage of the task routine execution request message, use the identifier associated with the first task and identifier(s) of the federated area(s) to identify one in which a first task routine is stored; within a task container, execute the first task routine to perform the first task; and upon completion of the job flow, transmit an indication of completion to the requesting device.
    Type: Application
    Filed: April 7, 2021
    Publication date: July 22, 2021
    Applicant: SAS Institute Inc.
    Inventors: Henry Gabriel Victor Bequet, Ronald Earl Stogner, Eric Jian Yang, Qing Gong, Partha Dutta, Kais Arfaoui
  • Patent number: 11063849
    Abstract: Various embodiments are generally directed to techniques for automated software testing, such as by verifying operations are complete based on user interface and/or network traffic indications, for instance. Some embodiments are particularly directed to utilizing a network sniffer to detect specific network traffic to verify completion of network requests and/or responses associated with an operation included in a workflow for performance by a software under test (SUT). In many embodiments, the detection of specific network traffic may be used to accurately time operation durations and/or efficiently perform workflows to evaluate the SUT.
    Type: Grant
    Filed: August 5, 2020
    Date of Patent: July 13, 2021
    Assignee: SAS INSTITUTE INC.
    Inventors: Andrew Bynum Clegg, Christopher Chase Struble, Ronald Andrew Hackett
  • Patent number: 11062219
    Abstract: A computer solves a nonlinear optimization problem. An optimality check is performed for a current solution to an objective function that is a nonlinear equation with constraint functions on decision variables. When the performed optimality check indicates that the current solution is not an optimal solution, a barrier parameter value is updated, and a Lagrange multiplier value is updated for each constraint function based on a result of a complementarity slackness test. The current solution to the objective function is updated using a search direction vector determined by solving a primal-dual linear system that includes a dual variable for each constraint function and a step length value determined for each decision variable and for each dual variable. The operations are repeated until the optimality check indicates that the current solution is the optimal solution or a predefined number of iterations has been performed.
    Type: Grant
    Filed: November 30, 2020
    Date of Patent: July 13, 2021
    Assignee: SAS Institute Inc.
    Inventors: Joshua David Griffin, Riadh Omheni, Yan Xu
  • Patent number: 11055861
    Abstract: A computing system receives historical data. The historical data comprises physical actions taken in an experiment in a physical environment. The experiment comprises user-defined stages. The historical data comprises a recorded outcome, according to user-defined performance indicator(s) related to the user-defined stages, for each physical action taken in the experiment. The system generates, by a discrete event simulator, a computing representation of a simulated environment of the physical environment. The simulated environment comprises processing stages. The system obtains simulation data. The simulation data comprises simulated actions taken by the discrete event simulator. The simulation data comprises a predicted outcome, according to user-defined performance indicator(s) related to the processing stages, for each simulated action taken by the discrete event simulator. The system validates accuracy of the discrete event simulator at predicting the recorded outcome in the experiment.
    Type: Grant
    Filed: October 1, 2020
    Date of Patent: July 6, 2021
    Assignee: SAS Institute Inc.
    Inventors: Mohammadreza Nazari, Afshin Oroojlooyjadid, Alexander Richard Phelps, Davood Hajinezhad, Bahar Biller, Jonathan Lee Walker, Hamza Mustafa Ghadyali, Kedar Shriram Prabhudesai, Xunlei Wu, Xingqi Du, Jorge Manuel Gomes da Silva, Varunraj Valsaraj, Jinxin Yi
  • Patent number: 11055620
    Abstract: A computing system trains a clustering model. (A) Beta distribution parameter values are computed for each cluster using a mass parameter value and a responsibility parameter vector of each observation vector. (B) Parameter values are computed for a normal-Wishart distribution for each observation vector included in a batch of a plurality of observation vectors. (C) Each responsibility parameter vector defined for each observation vector of the batch is updated using the beta distribution parameter values, the parameter values for the normal-Wishart distribution, and a respective observation vector of the selected batch of plurality of observation vectors. (D) A convergence parameter value is computed. (E) (A) to (D) are repeated until the convergence parameter value indicates the responsibility parameter vector defined for each observation vector is converged. A cluster membership is determined for each observation vector using the responsibility parameter vector.
    Type: Grant
    Filed: November 17, 2020
    Date of Patent: July 6, 2021
    Assignee: SAS Institute Inc.
    Inventors: Yingjian Wang, Raymond Eugene Wright
  • Patent number: 11055639
    Abstract: Manufacturing processes can be optimized using machine learning models. For example, a system can execute an optimization model to identify a recommended set of values for configurable settings of a manufacturing process associated with an object. The optimization model can determine the recommended set of values by implementing an iterative process using an objective function. Each iteration of the iterative process can include selecting a current set of candidate values for the configurable settings from within a current region of a search space defined by the optimization model; providing the current set of candidate values as input to a trained machine learning model that can predict a value for a target characteristic of the object or the manufacturing process based on the current set of candidate values; and identifying a next region of the search space to use in a next iteration of the iterative process based on the value.
    Type: Grant
    Filed: October 6, 2020
    Date of Patent: July 6, 2021
    Assignee: SAS INSTITUTE INC.
    Inventors: Pelin Cay, Nabaruna Karmakar, Natalia Summerville, Varunraj Valsaraj, Antony Nicholas Cooper, Steven Joseph Gardner, Joshua David Griffin
  • Publication number: 20210200937
    Abstract: Embodiments are generally directed to techniques for extracting contextually structured data from document images, such as by automatically identifying document layout, document data, and/or document metadata in a document image, for instance. Many embodiments are particularly directed to generating and utilizing a document template database for automatically extracting document image contents into a contextually structured format. For example, the document template database may include a plurality of templates for identifying/explaining key data elements in various document image formats that can be used to extract contextually structured data from incoming document images with a matching document image format. Several embodiments are particularly directed to automatically identifying and associating document metadata with corresponding document data in a document image, such as for generating a machine-facilitated annotation of the document image.
    Type: Application
    Filed: November 5, 2020
    Publication date: July 1, 2021
    Applicant: SAS Institute Inc.
    Inventors: David James Wheaton, William Robert Nadolski, Heather Michelle GoodyKoontz
  • Patent number: 11049235
    Abstract: Embodiments are generally directed to techniques for extracting contextually structured data from document images, such as by automatically identifying document layout, document data, and/or document metadata in a document image, for instance. Many embodiments are particularly directed to generating and utilizing a document template database for automatically extracting document image contents into a contextually structured format. For example, the document template database may include a plurality of templates for identifying/explaining key data elements in various document image formats that can be used to extract contextually structured data from incoming document images with a matching document image format. Several embodiments are particularly directed to automatically identifying and associating document metadata with corresponding document data in a document image, such as for generating a machine-facilitated annotation of the document image.
    Type: Grant
    Filed: October 29, 2020
    Date of Patent: June 29, 2021
    Assignee: SAS INSTITUTE INC.
    Inventors: David James Wheaton, William Robert Nadolski, Heather Michelle GoodyKoontz
  • Patent number: 11049502
    Abstract: An apparatus includes processor(s) to: divide a speech data set into multiple data chunks that each represent a chunk of speech audio; configure a neural network to implement an acoustic model that includes a CTC output; provide each data chunk to the neural network and monitor the CTC output for a string of blank symbols; designate each string of blank symbols from the CTC output that is at least as long as a predetermined blank threshold length as a likely sentence pause of a candidate set of likely sentence pauses; based on at least the candidate set, divide the speech data set into multiple data segments that each represent a speech segment of the speech audio; and perform speech-to-text conversion, to identify a sentence spoken in a selected language in each speech segment.
    Type: Grant
    Filed: December 30, 2020
    Date of Patent: June 29, 2021
    Assignee: SAS INSTITUTE INC.
    Inventors: Xiaozhuo Cheng, Xu Yang, Xiaolong Li
  • Patent number: 11048884
    Abstract: A computing system receives a collection comprising multiple sets of ordered terms, including a first set. The system generates a dataset indicating an association between each pair of terms within a same set of the collection by generating co-occurrence score(s) for the first set. The system generates computed probabilities based on the co-occurrence score(s) for the first set. The computed probabilities indicate a likelihood that one term in a given pair of terms of the collection appears in a given set of the collection given that another term in the given pair of terms of the collection occurs. The system smoothes the computed probabilities by adding one or more random observations. The system generates one or more association indications for the first set based on the smoothed computed probabilities. The system outputs an indication of the dataset. Additionally, or alternatively, based on association measure(s), the system generates a virtual term.
    Type: Grant
    Filed: October 1, 2020
    Date of Patent: June 29, 2021
    Assignee: SAS Institute Inc.
    Inventors: James Allen Cox, Russell Albright, Saratendu Sethi
  • Patent number: 11042549
    Abstract: A computing system receives a program. The program is in a first computer language and specifies computer operations on stored data. The computing system is configured to partition the stored data into sets of partitioned data for performing parallel execution on each of the sets of partitioned data. The computing system determines whether the program comprises a thread program component. The computing system, responsive to determining that the program comprises a thread program component, generates computer-generated computer instructions. The computer-generated computer instructions are in a second computer language. The computer-generated computer instructions are dependent on whether the thread program component specifies information for partitioning and grouping the stored data; whether the program comprises a data program component; or whether the data program component specifies information for partitioning and grouping the output data of the thread program component.
    Type: Grant
    Filed: September 11, 2019
    Date of Patent: June 22, 2021
    Assignee: SAS Institute Inc.
    Inventor: David Abu Ghazaleh
  • Patent number: 11036981
    Abstract: A computing system determines if an event has occurred. A first window is defined that includes a subset of a plurality of observation vectors modeled as an output of an autoregressive causal system. A magnitude adjustment vector is computed from a mean computed for a matrix of magnitude values that includes a column for each window of a plurality of windows. The first window is stored in a next column of the matrix of magnitude values. Each cell of the matrix of magnitude values includes an estimated power spectrum value for a respective window and a respective frequency. A second matrix of magnitude values is updated using the magnitude adjustment vector. Each cell of the second matrix of magnitude values includes an adjusted power spectrum value for the respective window and the respective frequency. A peak is detected from the next column of the second matrix of magnitude values.
    Type: Grant
    Filed: February 4, 2021
    Date of Patent: June 15, 2021
    Assignee: SAS INSTITUTE INC.
    Inventors: Yuwei Liao, Anya Mary McGuirk, Byron Davis Biggs, Arin Chaudhuri, Allen Joseph Langlois, Vincent L. Deters
  • Publication number: 20210157595
    Abstract: An apparatus includes a processor core to: receive a request to execute application code including a trigger instruction and an instruction block that reads a row of data values from a data structure and outputs a data value from a function using the row as input, wherein the data structure is divided into multiple portions and the trigger instruction indicates that multiple instances of the instruction block are to be executed concurrently; and in response to the request, and to identification of the instruction block and trigger instruction: generate multiple instances of a support block that causes independent repetitive execution of each instance of the instruction block until all rows of the corresponding portion of the data structure are used as input; assign instances of the instruction and support blocks to multiple processor cores; and provide each instance of the instruction block with the corresponding portion of the data structure.
    Type: Application
    Filed: November 27, 2020
    Publication date: May 27, 2021
    Applicant: SAS Institute Inc.
    Inventors: Jack Joseph Rouse, Robert William Pratt, Jack Carl Erickson, Manoj Keshavmurthi Chari
  • Publication number: 20210158171
    Abstract: An apparatus includes processor(s) to: receive a request for a data catalog; in response to the request specifying a structural feature, analyze metadata of multiple data sets for an indication of including it, and to retrieve an indicated degree of certainty of detecting it for data sets including it; in response to the request specifying a contextual aspect, analyze context data of the multiple data sets for an indication of being subject to it, and to retrieve an indicated degree of certainty concerning it for data sets subject to it; selectively include each data set in the data catalog based on the request specifying a structural feature and/or a contextual aspect, and whether each data set meets what is specified; for each data set in the data catalog, generate a score indicative of the likelihood of meeting what is specified; and transmit the data catalog to the requesting device.
    Type: Application
    Filed: February 2, 2021
    Publication date: May 27, 2021
    Applicant: SAS Institute Inc.
    Inventors: Nancy Anne Rausch, Roger Jay Barney, John P. Trawinski
  • Patent number: 11017308
    Abstract: The computing device receives a first user input request to modify a structural equation model (SEM) in a graphical user interface. The modification of the SEM includes modifying one or more SEM path diagram elements. The computing device detects whether a first SEM path diagram element is modified responsive to the received first user input request. Based on the detection, the computing device determines whether the modification violates a first set of SEM rules, a second set of SEM rules, or one or more launch conditions prior to initiating execution of the SEM. Based on determining a violation of the SEM rules or the launch conditions or that there was not a violation, the computing device displays a graphical indicator for indicating a fatal error for the SEM modification, a warning error for the SEM modification, or a valid SEM modification.
    Type: Grant
    Filed: October 13, 2020
    Date of Patent: May 25, 2021
    Assignee: SAS Institute Inc.
    Inventors: Laura Castro-Schilo, James Robert Koepfler, Christopher Michael Gotwalt
  • Patent number: 11016871
    Abstract: Resource consumption associated with executing a bootstrapping process on a computing device can be reduced. For example, a system can receive a dataset including observations. The system can then instantiate one or more thread objects configured to execute a bootstrapping process that involves multiple iterations. Each iteration can involve: determining a respective set of probabilities based on an observation distribution associated with the dataset, executing a function based on the respective set of probabilities to determine a respective metric value, and storing the respective metric value in memory. This iterative process may be faster and less computationally intensive than traditional bootstrapping approaches. After completing the iterative process, the system may access the memory to obtain the metric values, determine a distribution of metric values based on at least some of the metric values, and store the distribution of metric values in the memory for further use.
    Type: Grant
    Filed: December 21, 2020
    Date of Patent: May 25, 2021
    Assignee: SAS INSTITUTE INC.
    Inventors: Rocco Claudio Cannizzaro, Christian Macaro
  • Patent number: 11010691
    Abstract: Data is classified using semi-supervised data. A decomposition is performed to define a first decomposition matrix that includes first eigenvectors of a weight matrix, a second decomposition matrix that includes second eigenvectors of a transpose of the weight matrix, and a diagonal matrix that includes eigenvalues of the first eigenvectors. Eigenvectors are selected from the first eigenvectors to define a reduced decomposition matrix. A linear transformation matrix is computed as a function of the first decomposition matrix, the reduced decomposition matrix, the diagonal matrix, and a penalty matrix. When a rank of the linear transformation matrix is less than a number of rows of the penalty matrix, a classification matrix is computed by updating a gradient of a cost function. When the rank of the linear transformation matrix is equal to the number of rows of the penalty matrix, the classification matrix is computed using a dual formulation.
    Type: Grant
    Filed: November 10, 2020
    Date of Patent: May 18, 2021
    Assignee: SAS Institute Inc.
    Inventors: Xu Chen, Jorge Manuel Gomes da Silva, Brett Alan Wujek