Capital One Services, LLC

Kate Key

Austin Grant Walters

Vincent Pham

Jeremy Edward Goodsitt

Anh Truong

Fardin Abdi Taghi Abad

Reza Farivar

Mark Watson

Kenneth Taylor

Galen Rafferty

Noriaki Tatsumi

Mark Louis Watson

Ernest Kwak

Alvin Hua

Michael Walters

Ahn Truong

Fardi Abdi Taghi Abad

A cloud computing system can be configured to generate a synthetic data stream that tracks a reference data stream. A model optimizer of the cloud computing system can receive, from an interface of the cloud computing system, a synthetic data stream request indicating a reference data stream. A dataset generator of the cloud computing system can generate a synthetic data stream that tracks the reference data stream by repeatedly swapping data models of the reference data stream. One such repeat can include retrieving, by the dataset generator from a model storage, a current data model of the reference data stream and generating a new data model of the reference data stream. The model optimizer can store the new data model in the model storage. The dataset generator can generate a synthetic data stream using the current data model of the reference data stream.

Systems and methods for data stream simulation

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

A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.

Systems and methods for facilitating candidate interviews

An exemplary system, method and computer-accessible medium can include receiving information regarding a purchase by a person, receiving financial account information regarding a financial account associated with the person that was used to fund the purchase, generating rewards information associated with the purchase, generating an authentication token(s) based on the financial account information, sending the rewards information and the authentication token(s) over a network, and receiving a confirmation, over the network, that a rewards account associated with the person has been updated.

System, method and computer-accessible medium for authentication of rewards information

Systems and methods for searching datasets and classifying datasets 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 test dataset from a client device and generating a test data model output using a data model, based on the test dataset. The operations may include processing test data model output by implementing an encoding method, a factorizing method, and/or a vectorizing method. The operations may include retrieving a reference data model output from a dataset index, based on a reference dataset. The operations may include generating a similarity metric based on the reference data model output and the test data model output. The operations may include classifying the test dataset based on the similarity metric and transmitting, to the client device, information comprising the classification.

Systems and methods for quickly searching datasets by indexing synthetic data generating models

A computer-implemented method may include: receiving, from at least one camera, image data associated with a first user at a public access user computing device; detecting, based on the received image data, by employing a machine learning model trained using a dataset of actions collected from a plurality of previous users, that the first user has moved away from the public access user computing device; automatically encrypting, based upon the detection, a user session associated with the first user, wherein the encrypted user session is configured to be subsequently activated by the first user; and initiating a new generic user session on the public access user computing device for a second user.

Methods and systems for automatically preserving a user session on a public access shared computer

The present disclosure relates to systems and methods for parsing unstructured data with neural networks. In one implementation, a system for parsing unstructured data may include at least one processor and at least one non-transitory memory storing instructions that, when executed by the at least one processor, cause the system to: receive unstructured data; apply a classifier to the unstructured data to identify a type of the unstructured data; based on the identification, select a corresponding neural network; apply the selected neural network to the unstructured data to obtain structured data; and output the structured data.

Systems and methods for parsing log files using classification and a plurality of neural networks

Techniques and apparatus for providing peer-based management of user accounts are described. In one embodiment, for example, an apparatus may include at least one memory and logic coupled to the at least one memory. The logic may be configured to receive a request from at least one first user account to unlock a second user account locked responsive to a fraud event, determine a safe authentication value for the fraud event, and unlock the second user account responsive to the at least one first user account being a safe authentication account and the safe authentication value being over a safe authentication threshold value. Other embodiments are described.

Techniques for peer entity account management

Methods and systems for providing changes to a live voice stream of a person are disclosed. A change to be made to the live voice stream based on user information can be identified. The live voice stream can be changed based on the user information.

Methods and systems for providing changes to a live voice stream

Disclosed are methods, systems, and non-transitory computer-readable medium for automatically queuing participants during a conference call. For instance, the method may include receiving call data associated with a conference call; analyzing the call data to identify the participants on the conference call; and determining whether two or more participants of the plurality of participants are speaking at a same time. The method can also include tracking a first participant that continues speaking and a second participant that stops speaking; and displaying a queuing element on a graphical user interface (GUI) to indicate that the second participant is in a queue to speak once the first participant has finished speaking.

Methods and systems for automatic queuing in conference calls

Systems and methods are presented for establishing secure transactions among a group of transacting parties through use of multi-party computation including garbled circuits. The system uses a set of distributed garbled circuit servers, each having a garbled circuit module, to collectively and securely perform a transactional function, such that any party only has access to its own input and output. Each garbled circuit module may receive input financial data for a transacting party and financial data for at least one other transacting party, and perform an operation to obtain output financial data. The operation may relate to a function for determining a plurality of financial transactions among the plurality of transacting parties.

System and method for establishing secure transactions among a group of transacting parties

A method includes storing, by one or more processors of one or more computing devices, a plurality of datasets in a non-transitory computer memory associated with the one or more computing devices. A plurality of index representations is generated where each one of the plurality of index representations includes a compressed representation of a respective one of the plurality of datasets. The plurality of index representations is stored in the non-transitory computer memory. A sample dataset is received by the one or more processors. A sample dataset representation is generated that includes a compressed representation of the sample dataset. A determination that at least one of the plurality of datasets is most similar to the sample dataset based on the sample dataset representation and the plurality of index representations is performed.

Method and system for implementing a fast dataset search using a compressed representation of a plurality of datasets

Aspects described herein may relate to methods, systems, and apparatuses that provide new capabilities for recommending purchases to a user based on a new descriptor referred to as 'purchase embeddings.' The purchase embedding may include a tuple in a new multi-dimensional search space for describing and tracking purchases of goods and services. Recommendations may be based on a distance between tuples in the search space, which provides a measure of similarity between items represented by the tuples.

Generating recommendations based on descriptors in a multi-dimensional search space

Aspects described herein may relate to methods, systems, and apparatuses that provide new capabilities for recommending purchases to a user based on the user's past purchasing history and the purchase history of others. A new descriptor referred to as 'purchase embeddings' is disclosed, which are data records in a new multi-dimensional space for describing and tracking purchases of goods and services.

Growing community of inventors

Effingham, IL, United States of America

Kate Key