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    CONFIGURATION TOOL FOR DEPLOYING AN APPLICATION ON A SERVER
    131.
    发明申请
    CONFIGURATION TOOL FOR DEPLOYING AN APPLICATION ON A SERVER 审中-公开

    公开(公告)号：WO2023002294A1

    公开(公告)日：2023-01-26

    申请号：PCT/IB2022/056324

    申请日：2022-07-08

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM UNITED KINGDOM LIMITED ,  IBM (CHINA) INVESTMENT COMPANY LIMITED

    Inventor： REEVE, John, Anthony ,  KLINGER, Doina, Liliana ,  XING, Chengxuan ,  SOAL, Tom

    IPC: G06F9/50

    Abstract: An application configuration tool and associated method for supporting deployment of an application on a server that has a set of configurations available for applications deployed on the server. The method attempts to match every configuration required by the application to a configuration available on the server. In case of multiple candidates that match, one is selected. When there is no match an error message is generated. The method is iterated to inspect each selected configuration to identify any references contained in the selected configuration that themselves need further configurations. The iteration of inspecting and the matching to follow the references is continued until all such references are exhausted either by matching or failure to match and consequent error message generation. Finally, a configuration report is output specifying the selected configurations and, to the extent that not all required configurations have been matched to available configurations, the error messages.

    ANOMALY DETECTION OVER HIGH-DIMENSIONAL SPACE
    133.
    发明申请
    ANOMALY DETECTION OVER HIGH-DIMENSIONAL SPACE 审中-公开

    公开(公告)号：WO2022269387A1

    公开(公告)日：2022-12-29

    申请号：PCT/IB2022/054851

    申请日：2022-05-24

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM UNITED KINGDOM LIMITED ,  IBM (CHINA) INVESTMENT COMPANY LIMITED

    Inventor： HARRIS, Bradley, Evan ,  KHAN, Moazzam ,  HEINLEIN, James

    IPC: G06K9/62 ,  G06N20/00 ,  G06N5/027 ,  G06N5/04 ,  H04L63/1425

    Abstract: One or more computer processors create a binary cluster of events by bootstrapping a set of ground truths contained with a rule engine applied to a set of high-dimensional datapoints, wherein the binary cluster contains two clusters each containing a plurality of high-dimensional datapoints; determine one or more peer groups for a set of unknown high-dimensional datapoints utilizing a trained multiclass classifier, wherein the high-dimensional datapoints are assigned to one or more peer groups by the trained multiclass classifier using an incremental learning algorithm in order to reduce system resources; create an activity distribution for each unknown high-dimensional datapoint associated with a user in the set of unknown high-dimensional datapoints and each peer group; calculate a deviation percentage between the activity distribution of the user and each peer group associated with the user; and responsive to exceeding a deviation threshold, classify the user or associated high-dimensional datapoints as risky.

    PROGRAM EVENT RECORDING STORAGE ALTERATION PROCESSING FOR A NEURAL NETWORK ACCELERATOR INSTRUCTION
    136.
    发明申请
    PROGRAM EVENT RECORDING STORAGE ALTERATION PROCESSING FOR A NEURAL NETWORK ACCELERATOR INSTRUCTION 审中-公开

    公开(公告)号：WO2022263997A1

    公开(公告)日：2022-12-22

    申请号：PCT/IB2022/055449

    申请日：2022-06-13

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM (CHINA) INVESTMENT COMPANY LTD. ,  IBM DEUTSCHLAND GMBH

    Inventor： WEISHAUPT, Simon ,  SAPORITO, Anthony ,  SLEGEL, Timothy

    IPC: G06N3/063

    Abstract: Instruction processing is performed for an instruction (700). The instruction is configured to perform a plurality of functions (702), in which a function of the plurality of functions is to be performed in a plurality of processing phases (704). A processing phase is defined to store up to a select amount of data (706). The select amount of data is based on the function to be performed (708). At least one function of the plurality of functions has a different value for the select amount of data than at least one other function (710). A determination is made as to whether a store into a designated area occurred based on processing a select processing phase of a select function (712). Based on determining that the store into the designated area occurred, an interrupt is presented (714), and based on determining that the store into the designated area did not occur, instruction processing is continued (716).

    POINTER ALIGNMENT COMPUTATION IN PROGRAM CODE ACCORDING TO CODE PATTERN ANALYSES
    137.
    发明申请
    POINTER ALIGNMENT COMPUTATION IN PROGRAM CODE ACCORDING TO CODE PATTERN ANALYSES 审中-公开

    公开(公告)号：WO2022263980A1

    公开(公告)日：2022-12-22

    申请号：PCT/IB2022/055409

    申请日：2022-06-10

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM UNITED KINGDOM LIMITED ,  IBM (CHINA) INVESTMENT COMPANY LIMITED

    Inventor： CUI, Shimin

    IPC: G06F12/02

    Abstract: Pointer alignment in a computer programming to obtain information enabling a compiler to optimize program code. Equivalence classes of pointers are collected in a program using a flow-insensitive yet field-sensitive pointer analysis operation iterating through an entire program code of the program. The equivalence classes of pointers, once collected, are mapped to and recorded in an equivalence class mapping table (ECTable). A portion of the collected equivalence classes of pointers are identified, from the ECTable, as pointer candidates for a pointer alignment computation according to a code pattern analysis of each pointer candidate. The code pattern analysis is based on available alignment information, and whether the alignment information would enable a compiler to optimize pointer references of the candidate pointer. The pointer alignment computation is then performed for each identified pointer candidate to obtain the alignment information used to optimize execution of the program.

    BIAS REDUCTION DURING ARTIFICAL INTELLIGENCE MODULE TRAINING
    138.
    发明申请
    BIAS REDUCTION DURING ARTIFICAL INTELLIGENCE MODULE TRAINING 审中-公开

    公开(公告)号：WO2022259089A1

    公开(公告)日：2022-12-15

    申请号：PCT/IB2022/055104

    申请日：2022-06-01

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM (CHINA) INVESTMENT COMPANY LTD. ,  IBM DEUTSCHLAND GMBH

    Inventor： CMIELOWSKI, Lukasz ,  KUCHARCZYK, Szymon ,  HIRZEL, Martin ,  LĄCZAK, Dorota

    IPC: G06N3/08 ,  G06N20/00 ,  G06N7/00

    Abstract: Disclosed herein is a method of training an artificial intelligence model with adjustable parameters that is trained to provide an analysis result in response to receiving an input data set comprising one or more chosen variables. The method comprises: receiving a training data set comprising multiple groups of training input data paired with a training analysis result(400), receiving a trial analysis result from the artificial intelligence model in response to inputting the multiple groups of training input data into artificial intelligence model(402), calculating an accuracy metric descriptive of a comparison between the trail analysis result and the training analysis result(404), calculating a fairness score metric by comparing the one or more chosen variables to the trial analysis result (406), calculating a combined metric from the fairness score metric and the accuracy metric(408), and modifying the adjustable parameters using a training algorithm that receives at least the combined metric(410).

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