Staged training of neural networks for improved time series prediction performance

    公开(公告)号:US10650045B2

    公开(公告)日:2020-05-12

    申请号:US16556573

    申请日:2019-08-30

    Abstract: An apparatus includes a processor to: train a first neural network of a chain to generate first configuration data including first trained parameters, wherein the chain performs an analytical function generating a set of output values from a set of input values, each neural network has inputs to receive the set of input values and outputs to output a portion of the set of output values, and the neural networks are ordered from the first at the head to a last neural network at the tail, and are interconnected so that each neural network additionally receives the outputs of a preceding neural network; train, using the first configuration data, a next neural network in the chain ordering to generate next configuration data including next trained parameters; and use at least the first and next configuration data and data indicating the interconnections to instantiate the chain to perform the analytical function.

    Generation of job flow objects in federated areas from data structure

    公开(公告)号:US10380185B2

    公开(公告)日:2019-08-13

    申请号:US16223518

    申请日:2018-12-18

    Abstract: An apparatus includes a processor to: receive a request to provide, within a specified federated area, a set of objects that enable a performance of a job flow to perform multiple tasks of an analysis based on data table(s) and formulae of a spreadsheet data structure, wherein the set of objects includes at least one task routine to perform a task of the multiple tasks; correlate each indication of data required as input or output to at least a subpart of a data table; identify data dependencies and determine an order of performance among the multiple tasks based on the formulae; generate, within the specified federated area, a job flow definition that specifies the order of performance of the multiple tasks; and for each task routine of the at least one task routine, generate, within the specified federated area, a corresponding macro data structure.

    GENERATION OF JOB FLOW OBJECTS IN FEDERATED AREAS FROM DATA STRUCTURE

    公开(公告)号:US20190146997A1

    公开(公告)日:2019-05-16

    申请号:US16223518

    申请日:2018-12-18

    Abstract: An apparatus includes a processor to: receive a request to provide, within a specified federated area, a set of objects that enable a performance of a job flow to perform multiple tasks of an analysis based on data table(s) and formulae of a spreadsheet data structure, wherein the set of objects includes at least one task routine to perform a task of the multiple tasks; correlate each indication of data required as input or output to at least a subpart of a data table; identify data dependencies and determine an order of performance among the multiple tasks based on the formulae; generate, within the specified federated area, a job flow definition that specifies the order of performance of the multiple tasks; and for each task routine of the at least one task routine, generate, within the specified federated area, a corresponding macro data structure.

    GENERATION OF JOB FLOW OBJECTS IN FEDERATED AREAS FROM DATA STRUCTURE

    公开(公告)号:US20190146998A1

    公开(公告)日:2019-05-16

    申请号:US16226828

    申请日:2018-12-20

    Abstract: An apparatus includes a processor to: receive a request to generate a DAG of a job flow of multiple tasks of an analysis based on data table(s) and formulae of a spreadsheet data structure; correlate each indication of data required as input or output to at least a subpart of a data table; identify data dependencies and determine an order of performance among the multiple tasks based on the formulae; generate, within the specified federated area, a job flow definition that specifies the order of performance of the multiple tasks; for each task of the multiple tasks, generate, within the specified federated area, a corresponding macro data structure of multiple macro data structures; and generate the requested visualization based on the job flow definition and the multiple macro data structures.

    NODE DEVICE FUNCTION AND CACHE AWARE TASK ASSIGNMENT

    公开(公告)号:US20170223097A1

    公开(公告)日:2017-08-03

    申请号:US15422154

    申请日:2017-02-01

    Abstract: An apparatus includes a processor and storage to store instructions that cause the processor to perform operations including: receive an indication of completion of a first task with a first partition such that the first node device is available to assign to perform another task; delay assignment of performance of a second task on a second partition to the first node device for up to a predetermined period of time, in spite of readiness of the second task to be performed on the second partition and availability of the first node device; determine whether an indication of completion of the first task with the second partition such that the second node device is available to assign to perform another task is received within the predetermined period of time; and assign performance of the second task on the second partition to the second node device based on the determination.

    STAGED TRAINING OF NEURAL NETWORKS FOR IMPROVED TIME SERIES PREDICTION PERFORMANCE

    公开(公告)号:US20190384790A1

    公开(公告)日:2019-12-19

    申请号:US16556573

    申请日:2019-08-30

    Abstract: An apparatus includes a processor to: train a first neural network of a chain to generate first configuration data including first trained parameters, wherein the chain performs an analytical function generating a set of output values from a set of input values, each neural network has inputs to receive the set of input values and outputs to output a portion of the set of output values, and the neural networks are ordered from the first at the head to a last neural network at the tail, and are interconnected so that each neural network additionally receives the outputs of a preceding neural network; train, using the first configuration data, a next neural network in the chain ordering to generate next configuration data including next trained parameters; and use at least the first and next configuration data and data indicating the interconnections to instantiate the chain to perform the analytical function.

    Generation of job flow objects in federated areas from data structure

    公开(公告)号:US10394890B2

    公开(公告)日:2019-08-27

    申请号:US16226828

    申请日:2018-12-20

    Abstract: An apparatus includes a processor to: receive a request to generate a DAG of a job flow of multiple tasks of an analysis based on data table(s) and formulae of a spreadsheet data structure; correlate each indication of data required as input or output to at least a subpart of a data table; identify data dependencies and determine an order of performance among the multiple tasks based on the formulae; generate, within the specified federated area, a job flow definition that specifies the order of performance of the multiple tasks; for each task of the multiple tasks, generate, within the specified federated area, a corresponding macro data structure of multiple macro data structures; and generate the requested visualization based on the job flow definition and the multiple macro data structures.

    Automated transfer of neural network definitions among federated areas

    公开(公告)号:US10360069B2

    公开(公告)日:2019-07-23

    申请号:US16039745

    申请日:2018-07-19

    Abstract: An apparatus includes a processor to: perform a testing job flow at least partly within a testing federated area to test a neural network defined by configuration data specifying hyperparameters and trained parameters thereof; and perform a transfer flow to transfer an object indicative of results of the testing from the testing federated area to another federated area, wherein: in response to the degree of accuracy falling below a predetermined minimum threshold, the processor is caused to transfer a specification of the degree of accuracy or a portion of inaccurate output to a training federated area in which the neural network was at least partly trained; and in response to the degree of accuracy exceeding a predetermined maximum threshold, the processor is caused to transfer a copy of the neural network configuration data to a usage federated area in which the neural network is to be made available for use.

Patent Agency Ranking