Visa International Service Association

International Business Machines Corporation

Yinhe Cheng

Yu Gu

Ranglin Lu

Igor V Karpenko

Peter A Walker

Subir Roy

Sam P Hamilton

Ruzhu Chen

Tzy-Hwa Kathy Tzeng

Hsian-Fen Tsao

Provided are systems for ensemble learning with machine learning models that include a processor to receive a training dataset of a plurality of data instances, wherein each data instance comprises a time series of data points, add an amount of time delay to one or more data instances to provide an augmented training dataset, select a first plurality of supervised machine learning models, select a second plurality of unsupervised machine learning models, train the first plurality of supervised machine learning models and the second plurality of unsupervised machine learning models based on the augmented training dataset, generate an ensemble machine learning model based on outputs of the supervised machine learning models and unsupervised machine learning models, and generate a runtime output of the ensemble machine learning model based on a runtime input to the ensemble machine learning model. Methods and computer program products are also provided.

System, method, and computer program product for time-based ensemble learning using supervised and unsupervised machine learning models

Described are a method, system, and computer program product for operating dynamic shadow testing environments for machine-learning models. The method includes generating a shadow testing environment operating at least two transaction services. The method also includes receiving a plurality of transaction authorization requests. The method further includes determining a first percentage associated with a first testing policy of the first transaction service and a second percentage associated with a second testing policy of the second transaction service. The method further includes replicating in the shadow testing environment, in real-time with processing the payment transactions, a first portion of the plurality of transaction authorization requests and a second portion of the plurality of transaction authorization requests. The method further includes testing the first transaction service using the first set of replicated transaction data and the second transaction service using the second set of replicated transaction data.

Method, system, and computer program product for operating dynamic shadow testing environments

A method, system, and computer program product for dynamically scheduling machine learning inference jobs receive or determine a plurality of performance profiles associated with a plurality of system resources, wherein each performance profile is associated with a machine learning model; receive a request for system resources for an inference job associated with the machine learning model; determine a system resource of the plurality of system resources for processing the inference job associated with the machine learning model based on the plurality of performance profiles and a quality of service requirement associated with the inference job; assign the system resource to the inference job for processing the inference job; receive result data associated with processing of the inference job with the system resource; and update based on the result data, a performance profile of the plurality of the performance profiles associated with the system resource and the machine learning model.

Method, system, and computer program product for dynamically scheduling machine learning inference jobs with different quality of services on a shared infrastructure

Described are a system, method, and computer program product for operating dynamic shadow testing environments for machine-learning models. The method includes storing a testing policy including an identifier of a machine-learning model and an identifier of a transaction service. The method includes generating a shadow testing environment operating the transaction service using the machine-learning model. The method also includes receiving, at a transaction service provider system, a transaction authorization request including transaction data of a transaction associated with a payment device. The method further includes identifying the machine-learning model associated with the transaction based on a parameter of the transaction data. The method further includes determining, based on the identifier of the machine-learning model, the testing policy and the shadow testing environment. The method further includes replicating the transaction data in the shadow testing environment as input for testing the transaction service using the machine-learning model.

System, method, and computer program product for operating dynamic shadow testing environments

A virtual system environment in a computing system allows non-root users to perform administrative operations normally requiring root privileges. A virtual control module has a virtual file system with virtual directories corresponding to one or more of the system directories of a root file system. Each virtual directory contains one or more symbolic links symbolically linking to one or more system files as link targets. The symbolic links have non-root permissions that allow the non-root users to perform administrative operations in the virtual control module that delete, change or replace the symbolic links. A capability is provided to resolve the symbolic links within the virtual control module to allow the non-root users to execute the link targets via the symbolic links. One or more non-root users may be placed in the virtual control module by setting their apparent root directory to a root directory of the virtual file system.

Virtual system administration environment for non-root user

An information handling system (IHS) employs operating system software to manage IHS resources. The operating system software manages software application programs as processes executing within the IHS. The processes run in foreground and background mode within the IHS. Processes running in foreground mode are subject to hang-up events with negative process output results, such as output data loss. In one embodiment, the operating system software supports a 'no hang-up now' command for use with processes running in foreground mode. The 'no hang-up now' command provides system users the ability to hang-up or log-out of an IHS terminal without negative effects on the current foreground process. A user may invoke the &#x201c;no hang-up now&#x201d; command after execution of the foreground process is already underway. The no hang-up command moves the foreground application to the background for continued execution. A signal handler program prevents termination of the background process until the process completes.

Growing community of inventors

Austin, TX, United States of America

Yinhe Cheng