Capital One Services, LLC

Other

Austin Grant Walters

Jeremy Edward Goodsitt

Vincent Pham

Anh Truong

Fardin Abdi Taghi Abad

Reza Farivar

Mark Watson

Galen Rafferty

Kenneth Taylor

Kate Key

Grant Eden

Samuel Sharpe

Mark Louis Watson

Ernest Kwak

Brian Chandler Barr

Alvin Hua

Christopher Wallace

Joseph Ford, Iii

Rittika Adhikari

Ahn Truong

Noriaki Tatsumi

Kenny Bean

Paul Hurlocker

Robert P Seaton

Fardin Abdi Abad

Michael Walters

Fardin Abdi Taghi

Fardin Abdi Tagh Abad

Fardi Abdi Taghi Abad

Anh Troung

Daniele Rosa

Exemplary embodiments may provide an approach to converting multidimensional color data for an image encoded in a first color space into an intermediate form that is a single dimensional value. The exemplary embodiments may then decode the intermediate form value to produce an encoding of the color data that is encoded in a second color space that differs from the first color space. In this manner, the data for the image may be efficiently converted from an encoding in the first color space into an encoding in the second color space.

Color conversion between color spaces using reduced dimension embeddings

Disclosed herein are system, method, and computer program product embodiments for process corruption prevention. An embodiment operates by determining security vulnerabilities for an entity and correlation values for the security vulnerabilities by applying completed processed records of the entity to a machine learning model. Each of the correlation values quantifies a relationship strength between a security vulnerability and fraudulent activity. The embodiment further operates by generating a security vulnerability score for the entity using the correlation values and identifying one or more patches for at least one of the security vulnerabilities. The one or more patches may be ranked and the ranking may be revised using a feedback mechanism after the one or more patches are implemented by the entity.

Patching security vulnerabilities using machine learning

An apparatus includes a display, a memory, a light sensor array and a light source array. The light source array emits light to display an image on the display. A controller is configured to receive a sensor output from each light sensor in the light sensor array. An ambient-light illuminance difference between a first illuminance of a first ambient light externally directed onto a first region of the displayed image of the display and a second illuminance of a second ambient light externally directed respectively onto a second region of the displayed image of the display is computed. Light source controls of light sources of the light source array are varied to change a luminous emittance of the light source array within the at least one second region of the displayed image so as to reduce a luminance difference between the first region and the second region of the displayed image.

Systems and methods for correcting ambient-light illuminance differences of ambient light directed onto regions of a display

Techniques for providing a localized blockchain that uses a mesh network to facilitate transactions for a localized event are provided. An electronic device can receive data from a localized mesh network to establish the device as a node on the localized mesh network. The established node can generate a cryptocurrency wallet that can be loaded with an initial amount of localized cryptocurrency tokens from a total amount of localized cryptocurrency tokens. The total amount of localized cryptocurrency tokens can be previously mined by a central authority of the localized mesh network. The established node can conduct transactions within the localized mesh network utilizing the localized cryptocurrency tokens. The established node can receive a portion of a cryptocurrency token for transmitting transactional data to a next nearest node on the localized mesh network to help facilitate a transaction involving other nodes on the network.

Localized blockchain utilizing mesh networks for localized events

Disclosed embodiments may include systems and methods for utilizing gesture-based transaction cards. Examples include: first, using a mobile device to preauthorize transaction cards to enter an unlocked state before making a purchase by making a gesture with the transaction card toward the mobile device. Second, using a first transaction card to change an authorization condition of a second transaction card associated with the same account by making a gesture from the first transaction card to the second transaction card. Third, using a first transaction card to distribute a predebited virtual card to the user device of a second user by making a gesture from the first transaction card to the user device of the second user. Additionally, the primary user may be able to upload new authorization conditions to the transaction card and control the system through a related mobile application on a connected mobile device.

Systems and methods for authorizing a transfer

A system for returning synthetic database query results. The system may include a memory unit for storing instructions, and a processor configured to execute the instructions to perform operations comprising: receiving a query input by a user at a user interface; determining, based on natural language processing, a type of the query input; determining, based on the received query input and a database language interpreter, an output data format; returning, based on a generation model and the output data format, a result of the query input; providing, to a plurality of training models and based on the determined query type, the query input and the result; and training the training models, based on the query input and the result.

Systems and methods for synthetic database query generation

A device may receive a preauthorization associated with missed transaction prevention for a transaction account of a user, wherein the missed transaction prevention involves preventing a missed transaction associated with merchant accounts of the user. The device may monitor a transaction log of the transaction account and identify a transaction pattern associated with a merchant account based on a plurality of historical transactions identified in the transaction log related to the merchant account. The device may determine that a historical transaction of the plurality of historical transactions is not designated for automatic execution and that an execution of an upcoming transaction corresponding to the plurality of historical transactions is not scheduled. The device may cause an account transaction associated with the upcoming transaction to be automatically executed before a transaction period expiration, associated with the merchant account, passes.

Automatic transaction execution based on transaction log analysis

A computer-implemented method may include: receiving financial information regarding a user; categorizing transaction information of the user based on the financial information; displaying the categorized transaction information of the user; receiving information regarding at least one financial preference and at least one transaction preference of the user; training a machine learning engine based on the at least one financial preference and at least one transaction preference of the user to determine one or more activities available to the user; calculating, for each of the one or more activities available to the user, an estimated influence on the at least one financial preference; displaying the estimated influence on the at least one financial preference based on a user selected one of the one or more activities available to the user; filtering the one or more activities available to the user with a positive estimated influence to the at least one financial preference; and presenting a recommendation of action relating to the one of the one or more activities available to the user, wherein the recommendation of action relating to the one of the one or more activities available to the user is presented by at least one of voice notification, application notification, tactile notification, or graphic notification.

Systems and methods for debt management with spending recommendation

In the disclosed transaction processing system, members of an authorized network of consumers and merchants manage account information using blockchain ledgers. Because both consumers and merchants maintain copies of the blockchain, for any consumer/merchant transaction, both entities can quickly validate the transaction because both are aware, via their blockchain entries, of the current status of the account sourcing the transaction, allowing fast and accurate transaction validation without the need to incur the processing charges inherent in traditional fiat currency credit transactions.

System and method for authorizing transactions in an authorized member network

Embodiments include systems and techniques to perform secure transactions including processing registration information for each computing device of a plurality of computing devices having authority over a financial account. In one example, embodiments include receiving a pending transaction against the financial account from a computing device. Embodiments include executing an authentication protocol to determine the computing device is a member of the plurality of computing devices based upon the registration information, and processing data identifying another computing device within a configurable distance from the computing device. Embodiments further include the system to execute the authentication protocol to determine the other computing device is a member of the plurality of computing devices based upon the registration information and bypass a portion of a security procedure for authorizing execution of the pending transaction.

Mobile authentification method via peer mobiles

Systems and methods for censoring text-based data are provided. In some embodiments a censoring system may include at least one processor and at least one non-transitory memory storing application programming interface instructions. The censoring system may be configured to perform operations comprising storing a target pattern type and a computer-based model for identifying a target data pattern corresponding to a target pattern type within text based data. The censoring system may also be configured to receive text-based data by a server, and to retrieve the stored target pattern type to be censored in the text-based data. The censoring system may be configured to identify within the received text-based data, a target data pattern corresponding to the retrieved target pattern type. The censoring system may be configured to censor target characters within the identified target data pattern, and transmit the censored text-based data to a receiving party.

Systems and methods for censoring text inline

Systems and methods for generating synthetic data are disclosed. For example, a 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 receiving a dataset including time-series data. The operations may include generating a plurality of data segments based on the dataset, determining respective segment parameters of the data segments, and determining respective distribution measures of the data segments. The operations may include training a parameter model to generate synthetic segment parameters. Training the parameter model may be based on the segment parameters. The operations may include training a distribution model to generate synthetic data segments. Training the distribution model may be based on the distribution measures and the segment parameters. The operations may include generating a synthetic dataset using the parameter model and the distribution model and storing the synthetic dataset.

Systems and methods for synthetic data generation for time-series data using data segments

Systems and methods for providing encryption and decryption involving texture warping, comprising: obtaining a visual input; obtaining a private key; generating an encrypted visual representation (visual representation A) based on the private key and the visual input; determining at least one 3D object configured so that the private key is derivable when the visual representation A is mapped to a digital model of the at least one 3D object; transmitting the visual representation A to a second computing device associated with a second user; transmitting a representation of the digital model of the at least one 3D model to the second computing device; and instructing the second computing device so that the second computing device is configured to map the visual representation A to the digital model generated based on the representation of the digital model of the at least one 3D model to extract the private key.

Computer-based systems configured for texture warping-based encryption and methods of use thereof

Systems and methods of procuring real data items based on user affinity gauged via synthetic data items are disclosed. In one embodiment, an exemplary computer-implemented method may comprise: utilizing a trained machine learning model to generate a synthetic data item based on real user data; presenting the synthetic data item to those users; obtaining indications identifying user responses to the synthetic data item; obtaining user-defined control parameters from the users; configuring a user-defined control mechanism to share a portion of the real user data based thereon; obtaining a subset of the real user data based the user-defined control parameters; providing to a particular third-party data source at least one of: data regarding the synthetic data item, the at least one portion of the real user data, and the indications of the users; and then receiving a second real data item from the particular third-party data source.

Computer-based systems configured for procuring real content items based on user affinity gauged via synthetic content items and methods of use thereof

Methods and systems described herein relate to authenticating users-based on generating images that have modified features. More specifically, the methods and systems generate these images by processing existing training data to identify a common feature in existing photos that may be modified, and then modifying that feature with the use of generative adversarial networks.

Growing community of inventors

Savoy, IL, United States of America

Austin Grant Walters