Abstract: In one aspect, a system for managing data processes in a network of computing resources is configured to: receive, from an instructor device, a parent request for execution of at least one parent data process executable by a plurality of computing resources at least one computing resource; generate at least one child request for execution of at least one corresponding child data process for routing to at least one corresponding destination device, each of the at least one child data process for executing at least a portion of the at least one parent data process, and each of the at least one child request including a respective destination key derived from at least one instructor key; and route each of the at least one child request to the at least one corresponding destination device. The at least one child request can be obtained by a supervisor server via the routing.

Abstract: Systems 100, 1000, methods, and machine-interpretable programming or other instruction products for the management of data transmission by multiple networked computing resources 106, 1106. In particular, the disclosure relates to the synchronization of related requests for transmitting data using distributed network resources.

Abstract: A computer system and method for verifying a data lineage of a data element is provided. The system comprises at least processor and a memory storing instructions which when executed by the processor cause the processor to perform the method. The method comprises extracting data transformation code from programming logic, extracting and describing data transformation semantics from the code using a data transformation ontology, filtering out non-business-significant transformations, and determining that remaining business-significant transformations match a business ontology.

Abstract: A system and method for auto-populating an electronic transaction process is provided. The system comprises at least one processor, and a memory storing instructions which when executed by the at least one processor configure the processor to obtain a scanned payee identifier from an optical character recognition scan of a digital bill document, compare the scanned payee identifier with a set of stored payee identifiers to obtain at least one first identifier match, determine a score for each of the at least one identifier match, and select the stored payee identifier associated with a highest score. The method comprises obtaining a scanned payee identifier from an optical character recognition scan of a digital bill document, comparing the scanned payee identifier with a set of stored payee identifiers to obtain at least one first identifier match, determining a score for each of the at least one identifier match, and selecting the stored payee identifier associated with a highest score.

Abstract: Systems, methods, and computer-readable media for coordinating processing of data by multiple networked computing resources include monitoring data associated with a plurality of networked computing resources, and coordinating the routing of data processing segments to the networked computing resources.

Abstract: Embodiments generally relate to the field of reward processing, and more particularly, systems, methods, and computer readable media for digital reward processing utilizing distributed ledger technology. Distributed ledger technology is utilized wherein distributed ledgers are stored on a plurality of node computing devices, the distributed ledgers including sequential entries that are cryptographically linked to one another.

Abstract: Systems 10, devices 106, methods, and non-transient machine-interpretable programming and/or other instruction products for the generation, transfer, storage, and other processing of secure data sets 11 used in electronic payment transactions, including particularly the secure creation, administration, manipulation, processing, and storage of electronic data useful in processing of pre-funded, pre-paid, and/or otherwise pre-authorized payment transactions. Devices 106, 100, 101 and methods in accordance with the disclosure can be used to create pre-funded payment token data sets 11, the token data sets comprising secure data items or records representing negotiable monetary or other economic value, and to share them between network communication devices 106 such as smart phones, home or business desktop computers, etc., for use in purchases and other transactions.

Abstract: Systems 100, 1000, methods, and machine-interpretable programming or other instruction products for the management of data processing by multiple networked computing resources 106, 1106. In particular, the disclosure relates to the synchronization of related requests for processing of data using distributed network resources.

Abstract: A system is provided comprising a processor and a memory storing instructions which configure the processor to process an original sentence structure through an encoder neural network to decompose the original sentence structure into an original semantics component and an original syntax component, process the original syntax component through a syntax variation autoencoder (VAE) to receive a syntax mean vector and a syntax covariance matrix, obtain a sampled syntax value from a syntax Gaussian posterior parameterized by the syntax mean vector and the syntax covariance matrix, process the original semantics component through a semantics VAE to receive a semantics mean vector and a semantics covariance matrix, obtain a sampled semantics vector from the Gaussian semantics posterior parameterized by the semantics mean vector and the semantics covariance matrix, and process the sampled syntax vector and the sampled semantics vector through a decoder neural network to compose a new sentence.

Abstract: A system, electronic device and method for improved neural network training are provided. The improved system is adapted for tracking long range dependence in sequential data during training, and includes bootstrapping a lower bound on the mutual information (MI) over groups of variables (segments or sentences) and subsequently applying the bound to encourage high MI.

Abstract: An improved computer implemented method and corresponding systems and computer readable media for improving performance of a deep neural network are provided to mitigate effects related to catastrophic forgetting in neural network learning. In an embodiment, the method includes storing, in memory, logits of a set of samples from a previous set of tasks (D1); and maintaining classification information from the previous set of tasks by utilizing the logits for matching during training on a new set of tasks (D2).

Abstract: A system for controlling access to hosted services using computer generated question answer sets is described. The question answer sets are generated and include relationships which are designed to distinguish between human and automated system interpretation through the inclusion of a dynamically established transformation of characteristics in relation to objects described in the question answer sets. The dynamically established transformation provides an additional defense against malicious neural networks used to overcome mechanisms for distinguishing between humans and automated systems. Corresponding methods and devices are contemplated. In an additional embodiment, a decoy set of answer sets are also established to maintain a blacklisted set of suspected automated systems.

Abstract: Disclosed are systems, methods, and devices for pattern extraction. A graph data structure is generated, reflective of a directed graph having vertices representative of entities and edges representative of relationships between two entities. A subgraph data structure is generated, reflective of a plurality of subgraphs of the directed graph. A similarity matrix data structure is generated by applying a graph kernel to obtain a subgraph similarity matrix including a plurality of entries, each entry providing a score of the similarity between two subgraphs of the plurality of subgraphs. A clustering data structure is generated, reflective of a plurality of groups of the plurality entities upon processing the similarity matrix data structure. For at least a given one of the plurality of groups, a common pattern data structure is generated corresponding to a subgraph that is similar to subgraphs in the given group.

Abstract: Current systems for data authentication, such as in the course of financial transactions to comply with anti-money laundering and know-your-customer legislation, are burdensome and inefficient for banks and their clients. A platform of some embodiments provides a system for utilizing distributed ledger technologies, such as a blockchain data structure residing on a distributed ledger. A client may use this blockchain data structure to register the client's personal information in a data object that then may be routed to specific identified trusted individuals who verify that the information in the data object is correct. Once verification is complete, the client or other trusted individuals may use the data object as necessary to register the client for various programs or services, such as additional bank services.

Abstract: An access management system and method provisions credentials to access a resource, such as external web user accounts. Credentials are generated, encrypted and stored. To access the resource, encrypted credentials are decrypted, masked, and served to users, such that they are not visible to the user requiring access. The user is unaware of the credentials used to authenticate and unable to access the provisioned web resources outside set parameters.

Abstract: A system for detecting phishing events is provided. A data receiver is configured to receive datasets representative of web traffic associated with access to or on-going usage of an application hosted on a server of a production environment by a user. A machine learning engine is configured to generate a score based at least on the datasets representative of the web traffic indicative of whether the user is a malicious user or a non-malicious user. A routing modification engine is configured to route downstream web traffic associated with access to or on-going usage of the application by the user if the score is greater than a threshold to a server of a sandbox environment that is configured to emulate a graphic user interface of the production environment.

Abstract: Disclosed are systems, methods, and devices for generating a visualization of a deep reinforcement learning (DRL) process. State data is received, reflective of states of an environment explored by an DRL agent, each state corresponding to a time step. For each given state, saliency metrics are calculated by processing the state data, each metric measuring saliency of a feature at the time step corresponding to the given state. A graphical visualization is generated, having at least two dimensions in which: each feature of the environment is graphically represented along a first axis; and each time step is represented along a second axis; and a plurality of graphical markers representing corresponding saliency metrics, each graphical marker having a size commensurate with the magnitude of the particular saliency metric represented, and a location along the first and second axes corresponding to the feature and time step for the particular saliency metric.

Abstract: Systems are methods are provided for training an automated agent. The automated agent maintains a reinforcement learning neural network and generates, according to outputs of the reinforcement learning neural network, signals for communicating resource task requests. First and second task data are received. The task data are processed to compute a first performance metric reflective of performance of the automated agent relative to other entities in a first time interval, and a second performance metric reflective of performance of the automated agent relative to other entities in a second time interval. A reward for the reinforcement learning neural network that reflects a difference between the second performance metric and the first performance metric is computed and provided to the reinforcement learning neural network to train the automated agent.

Abstract: A system for reinforcement learning in a dynamic resource environment includes at least one memory and at least one processor configured to provide an electronic resource environment comprising: a matching engine and the resource generating agent configured for: obtaining from a historical data processing task database a plurality of historical data processing tasks, each historical data processing task including respective task resource requirement data; for a historical data processing task of the plurality of historical data processing tasks, generating layers of data processing tasks wherein a first layer data processing task has an incremental variant in its resource requirement data relative to resource requirement data for a second layer data processing task; and providing the layers of data processing tasks for matching by the machine engine.

Abstract: A de-coupled computing infrastructure is described that is adapted to provide domain specific contextual engines based on conversational flow. The computing infrastructure further includes, in some embodiments, a mechanism for directing conversational flow in respect of a backend natural language processing engine. The computing infrastructure is adapted to control or manage conversational flows using a plurality of natural language processing agents.