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    Two-level paralleliztion of goodness-of-fit tests for spatial process models
    1.
    发明授权
    Two-level paralleliztion of goodness-of-fit tests for spatial process models 有权

    公开(公告)号：US12299360B2

    公开(公告)日：2025-05-13

    申请号：US17535745

    申请日：2021-11-26

    Applicant: SAS Institute Inc.

    Inventor： Pradeep Mohan

    IPC: G06F30/20 ,  G06F9/50 ,  G06Q10/04

    Abstract: An apparatus includes processor(s) to: receive a request to test goodness-of-fit of a spatial process model; generate a KD tree from observed spatial point dataset including locations within a region at which instances of an event occurred; derive, from the observed spatial point dataset, multiple quadrats into which the region is divided; receive, from multiple processors, current levels of availability of processing resources including quantities of currently available execution threads; select, based on the quantity of currently available execution threads, a subset of the multiple processors to perform multiple iterations of a portion of the test in parallel; provide, to each processor of the subset, the KD tree, the spatial process model, and the multiple quadrats; receive, from each processor of the subset, per-quadrat data portions indicative of results of an iteration; derive a goodness-of-fit statistic from the per-quadrat data portions; and transmit an indication of goodness-of-fit to another device.

    TECHNIQUES AND ARCHITECTURE FOR SECURING LARGE LANGUAGE MODEL ASSISTED INTERACTIONS WITH A DATA CATALOG
    2.
    发明申请
    TECHNIQUES AND ARCHITECTURE FOR SECURING LARGE LANGUAGE MODEL ASSISTED INTERACTIONS WITH A DATA CATALOG 有权

    公开(公告)号：US20250139088A1

    公开(公告)日：2025-05-01

    申请号：US18904206

    申请日：2024-10-02

    Applicant: SAS INSTITUTE INC.

    Inventor： David Hermann Peter Weik

    IPC: G06F16/242 ,  H04L9/40

    Abstract: A computer-implemented system, computer-implemented method, and computer-program product includes receiving a natural language query from a user for executing an analytical task; generating an analytical large language model (LLM) prompt based on the natural language query and, in response to generating the analytical LLM prompt, orchestrating an LLM-directed workflow for handling the natural language query by: automatically prompting, using the analytical LLM prompt, an analytical task-oriented LLM to generate a structured query for querying a data catalog application; querying the data catalog application using the structured query generated by the analytical task-oriented LLM; obtaining query results from the data catalog application, where the query results include metadata associated with at least one element accessible to the data catalog application; prompting the analytical task-oriented LLM to identify a given analytical task associated with a given analytical agent; and automatically executing, by the given analytical agent, the analytical task.

    Systems and methods for graphical symmetry breaking
    3.
    发明授权
    Systems and methods for graphical symmetry breaking 有权

    公开(公告)号：US12287783B1

    公开(公告)日：2025-04-29

    申请号：US18808240

    申请日：2024-08-19

    Applicant: SAS Institute Inc.

    Inventor： Brandon Michael Reese ,  Steven Harenberg

    IPC: G06F16/00 ,  G06F16/22 ,  G06F16/2452 ,  G06F16/248

    Abstract: A system and method include breaking symmetry in a query graph by converting the query graph into a transformed query graph by generating a symmetry breaking expression that includes detecting one or more orbits in the transformed query graph, selecting an orbit from the one or more orbits having more than one node, generating an automorphism breaking sub-expression for the selected orbit, assigning a node of the selected orbit a unique node attribute, recalculating the one or more orbits in the transformed query graph, repeating the process until each node is in its own orbit, and combining each of the automorphism breaking sub-expressions to obtain the symmetry breaking expression. Using the symmetry breaking expression, the system and method include finding one or more subgraphs of a main graph that match the symmetry breaking expression of the query graph.

    Systems and methods for parallel exploration of a hyperparameter search space
    6.
    发明授权
    Systems and methods for parallel exploration of a hyperparameter search space 有权

    公开(公告)号：US12271795B1

    公开(公告)日：2025-04-08

    申请号：US19000713

    申请日：2024-12-24

    Applicant: SAS Institute Inc.

    Inventor： Xindian Long ,  Liping Cai ,  Xingqi Du ,  Steven Eric Krueger ,  Joshua David Griffin ,  Yan Xu ,  Scott Russell Pope ,  Lawrence Edmund Lewis

    IPC: G06N20/00

    Abstract: A system, method, and computer-program product includes selecting, by a controller node, a plurality of hyperparameter search points from a hyperparameter search space; instructing, by the controller node, one or more worker nodes to concurrently train a plurality of machine learning models for a target number of epochs using the plurality of hyperparameter search points; receiving, from the one or more worker nodes, a plurality of performance metrics that measure a performance of the plurality of machine learning models during the target number of epochs; and removing, by the controller node, one or more underperforming hyperparameter search points from the plurality of hyperparameter search points according to a pre-defined performance metric ranking criterion associated with the plurality of performance metrics.

    SYSTEMS AND METHODS FOR IMPLEMENTING AND USING A CROSS-PROCESS QUEUE WITHIN A SINGLE COMPUTER
    8.
    发明申请
    SYSTEMS AND METHODS FOR IMPLEMENTING AND USING A CROSS-PROCESS QUEUE WITHIN A SINGLE COMPUTER 有权

    公开(公告)号：US20250068358A1

    公开(公告)日：2025-02-27

    申请号：US18737721

    申请日：2024-06-07

    Applicant: SAS Institute Inc.

    Inventor： Lawrence Edmund Lewis ,  Mohammadreza Nazari ,  Amirhassan Fallah Dizche

    IPC: G06F3/06

    Abstract: A system, method, and computer-program product includes implementing a cross-process queue within a single computer that is configured to transfer a data block between an operating system process executing a write operation and an operating system process executing a read operation, initializing in-memory cell indices within the cross-process queue that include a write operation index tracking index values of one or more cells within the cross-process queue that are available to write and a read operation index tracking index values of one or more cells within the cross-process queue that are available to read, and implementing a cell synchronization data structure tracking states of a plurality of cells of the index of cells of the cross-process queue.

    TOPOLOGICAL ORDER DETERMINATION USING MACHINE LEARNING
    9.
    发明申请
    TOPOLOGICAL ORDER DETERMINATION USING MACHINE LEARNING 有权

    公开(公告)号：US20250045263A1

    公开(公告)日：2025-02-06

    申请号：US18538066

    申请日：2023-12-13

    Applicant: SAS Institute Inc.

    Inventor： Xilong Chen ,  Tao Huang ,  Jan Chvosta

    IPC: G06F16/22 ,  G06N3/04 ,  G06N3/08

    Abstract: A computing device learns a best topological order vector for a plurality of variables. (A) A topological order vector is defined. (B) A target variable and zero or more input variables are defined based on the topological order vector. (C) A machine learning model is trained with observation vectors using values of the target variable and the zero or more input variables. (D) The machine learning model is executed with second observation vectors using the values of the target variable and the zero or more input variables to compute a loss value. (E) (A) through (D) are repeated a plurality of times. Each topological order vector defined in (A) is unique in comparison to other topological order vectors defined in (A). The best topological order vector is determined based on a comparison between the loss values computed for each topological order vector in (D).

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