Capital One Services, LLC

Anil Konduru

Kirankumar Kulkarni

Gunjan Patel

Patrick James Manion

Savio Joseph Darivemula

Jie Shen

Kelly L Birch

Amit Ramesh Deshpande

Jameskutty Mony

Anvitha Banakal Sadananda

Dillon Forsberg

Sunil Subrahmanyam Vasisht

Ranganathan Mohan

Dirgh Rabadia

A method, apparatus, and computer-readable medium are described that enable agent instances to be instantiated in secure, containerized environments. When a new container is detected, a list of agent instances expected to be running in a compute instance or in a container may be obtained and compared with status information regarding which agent instances are active. For a non-active agent instance, an agent object and configuration information for the agent instance may be obtained from a storage. Based on the available name, the agent object, and the configuration information, the agent instance may be instantiated and connected to an agent status server. An application related to the new agent instance may be deployed in the secure containerized environment.

Securely rehydrating containerized agents

A method, apparatus, and computer-readable medium are described that provide integrated testing and validation of multi-phase instructions before deployment. Aspects of the disclosure relate to testing ETL instructions using an efficient process that individually and/or holistically validates the ETL instructions and, using a random number generator, varies various aspects of the source datasets. A benefit of running the combination of instructions includes finding errors that are not apparent during testing of each instruction phase separately. Instructions may be separately provided that identify the framework of an in-memory source dataset (e.g., a quantity of rows, a quantity of columns, types of the various columns, data for each record, and the like). The instructions for the framework may also identify a variability of one or more of the items of the framework.

In-memory databases for integration testing of extraction, transformation, and/or loading jobs

Disclosed embodiments provide systems and methods related to updating creatives generation models. The system may include at least one memory unit for storing instructions and at least one processor configured to execute the instructions to perform operations. The operations may include receiving a feedback indication concerning an email message sent to a target, the email message constructed using a first template and associated with a first context, the feedback indication including a recommendation identifier; updating, in response to receiving the feedback indication, a feedback value for the email message stored in a delay buffer; obtaining the updated feedback value upon satisfaction of a time delay condition; updating, using the updated feedback data and the recommendation identifier, a machine learning model configured to recommend templates based on contexts; and constructing and providing a second email message using a second template recommended by the updated machine learning model for a second context.

Systems and methods for updating creatives generation models

A system for online advertising. The system may include at least one memory unit for storing instructions and at least one processor configured to execute the instructions to perform operations. The operations may include receiving a plurality of creatives for a webpage published to a viewer and resulting in a viewer experience; measuring, based on the viewer experience, a result including conversion rates for a plurality of variants of the webpage; determining confidence intervals in association with the conversion rates; dynamically comparing the received creatives, the conversion rates, and the determined confidence intervals of the variants; automatically analyzing, based on the comparison, the variants to select a winning webpage, the winning webpage exceeding a computed threshold; and automatically adjusting online traffic such that the selected winning webpage is displayed more frequently than other webpages.

Systems and methods for self-serve marketing pages with multi-armed bandit

Systems and methods for managing feedback for a multi-ARM bandit algorithm are disclosed. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include sending, to a device, a creative configured for display on the device. The operations may include receiving, from the device, feedback data associated with the creative, wherein the feedback data indicates a degree of user interaction with the creative. The operations may include checking the feedback data for a baked time associated with the creative. The operations may include sending the feedback data to a node based on the baked time. The operations may include updating, by the node, a model associated with the feedback data.

Systems and methods to manage feedback for a multi-arm bandit algorithm

Growing community of inventors

Plano, TX, United States of America

Anil Konduru