Abstract: 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.

Abstract: A method for generating a cluster-based machine learning model based on federated learning with cluster feedback includes providing a current machine learning model to a plurality of user devices that train the current machine learning model, receiving respective model states, generating updated model states, causing the plurality of user devices to obtain a respective instance of an updated machine learning model based on the updated model states, receiving an applicability feedback for the updated machine learning model for each of the plurality of user devices, determining a plurality of user clusters including a subset of the plurality of user devices, identifying a first user cluster and a second user cluster, the first user cluster having a higher cluster applicability feedback than the second user cluster, receiving the additional model states from the clusters and updating the updated machine learning model to generate the cluster-based machine learning model.

Abstract: Systems and methods for architecture embeddings for efficient dynamic synthetic data generation are disclosed. The disclosed systems and methods may include a system for generating synthetic data configured to perform operations. The operations may include retrieving a set of rules associated with a first data profile and generating, by executing a hyperparameter search, a plurality of hyperparameter sets for generative adversarial networks (GANs) that satisfy the set of rules. The operations may include generating mappings between the hyperparameter sets and the first data profile and storing the mappings in a hyperparameter library. The operations may include receiving a request for synthetic data, the request indicating a second data profile and selecting, from the mappings in the hyperparameter library, a hyperparameter set mapped to the second data profile. The operations may include building a GAN using the selected hyperparameter set and generating, using the GAN, a synthetic data set.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Methods and systems are described herein for modifying scheduled events based on bandwidth availability. To modify the scheduled event, the system determines a plurality of user devices corresponding to an event. The system receives first network conditions for a first user device and generates a feature input based on the first network conditions. The system inputs the feature input into an artificial intelligence model to determine a first available bandwidth metric and aggregates the first available bandwidth metric with respective available bandwidth metrics for other user devices of the plurality of user devices to determine a composite available bandwidth metric. The system can compare the composite available bandwidth metric to a threshold available bandwidth metric and in response to determining that the composite available bandwidth metric equals or exceeds the threshold available bandwidth metric, the system generates for display, on a user device interface, a recommendation for modifying the event.

Abstract: In some implementations, a data processing device may receive, from a data source, a set of delimiter-separated values and may divide the set of delimiter-separated values into a plurality of subsets. Each subset may correspond to at least a portion of a column or correspond to at least a portion of a row. The data processing device may generate a plurality of vectors, corresponding to the plurality of subsets, according to an embedding space. The data processing device may compare the plurality of vectors to each other and may select a row or a column of the set of delimiter-separated values as one or more headers based on comparing the plurality of vectors to each other. Accordingly, the data processing device may output a tabular data structure including the one or more headers distinguished from a remainder of the set of delimiter-separated values.

Abstract: Disclosed embodiments include systems and methods for providing a secure physical storage system. The system may receive a request to register a first physical storage box from an entity including location information and security information. The request can be validated by comparing the security information to a predetermined security threshold. The location information associated with the first physical storage box can be recorded to a blockchain. The first registration information can be received from a first user device. The first physical storage box can be assigned to the first user device and a first identity token associated with the first physical storage box. The assignment information associated with the first physical storage box can be recorded to the blockchain. A first identity token can be received from the first user device. Instructions can be transmitted to the first physical storage box to transition from a locked to an unlocked state.

Abstract: A method for object protection identification is provided. The method may: monitor, using a processor, at least one of audio data or history data associated with a user; detect an object replacement triggering event, based on a result of the monitoring; receive user data for a user associated with the at least one of audio data or history data; identify an object corresponding to the object replacement triggering event based on the user data; identify object-related information, the object-related information including at least one of an object protection information or an object replacement information; and transmit the at least one of the object protection information or the object replacement information based on identifying the object-related information.

Abstract: In some implementations, a user device may determine that the user device was granted access to a first set of resources by a first authentication process. The user device may receive a request to access a second set of resources. The user device may generate, based on the request, a token that indicates that the user device was granted access to the first set of resources by the first authentication process. The user device may transmit, based on the request, the token to a server device to cause a second authentication process to be performed on the token. The user device may receive, from the server device, access information indicating whether access to the second set of resources is granted or denied based on transmitting the token to the server device.

Abstract: In some implementations, a server may receive, from a user device, one or more credentials associated with a user. Accordingly, the server may transmit, to the user device, instructions for generating a user interface including a plurality of visual components based on authenticating the user with the one or more credentials. The server may detect, during a first interval, a lack of interaction with the user interface. Accordingly, the server may remove one of the plurality of visual components from the user interface based on the lack of interaction. Additionally, the server may detect, during a second interval, one or more interactions with the user interface and may update a similarity score associated with the user based on properties associated with the one or more interactions. Accordingly, the server may restore the visual component to the user interface based on the updated similarity score satisfying a similarity threshold.

Abstract: Disclosed embodiments may include a system for providing automated bill splitting. The system may receive speech data. The system may identify, from the speech data and using natural language processing, one or more users. The system may determine, from the speech data and using natural language processing, orders of the one or more users. The system may determine, from the speech data and using natural language processing, rules for the orders of the one or more users. The system may process one or more payments for the orders based on the rules and one or more credentials associated with the one or more users.

Abstract: Logic may receive one or more heatmaps captured by one or more user devices associated with a user, wherein each of the one or more heatmaps include data related to wireless communications. The logic may store the one or more heatmaps in a heatmap data structure associated with a user profile for the user. The logic may receive a login attempt with a heatmap, the login attempt associated with the user. The logic may generate a score for the login attempt by comparing the heatmap with the one or more heatmaps stored in a heatmap data structure associated with the user profile for the user. And, in some embodiments, the logic may determine to authenticate the login attempt based on the score.

Abstract: Disclosed embodiments may include a method and system for automated incremental payments. The system may identify recurring charges from historical account data. Based on the recurring charges and an incremental period, the system may calculate an incremental amount and expected amount. At each iteration of the incremental period, the incremental amount may be assigned to a savings bucket. The value of the savings bucket may be subtracted from an actual account balance to calculate a reduced account balance. The system may generate and transmit a graphical user interface to a user device showing the reduced account balance. The system may receive current data containing a charge that corresponds to the recurring charges. The system may reduce the value of the savings bucket by the amount of the current data charge. If the current data charge is different from the expected amount, the system may adjust the incremental amount accordingly.

Abstract: In some implementations, a recording device may obtain a settings configuration associated with deactivating an audio recording function or an audio processing function of the recording device, wherein the settings configuration indicates one or more deactivation events. The recording device may obtain first audio content associated with the recording device for identifying audio prompts associated with causing the recording device to perform one or more actions. The recording device may detect a deactivation event of the one or more deactivation events. The recording device may refrain from obtaining audio content based on detecting the deactivation event and until an activation event is detected. The recording device may obtain second audio content associated with the recording device based on detecting the activation event.

Abstract: In some implementations, a server may receive, from a user device, one or more credentials associated with a user. Accordingly, the server may transmit, to the user device, instructions for generating a user interface including a plurality of visual components based on authenticating the user with the one or more credentials. The server may detect, during a first interval, a lack of interaction with the user interface. Accordingly, the server may remove one of the plurality of visual components from the user interface based on the lack of interaction. Additionally, the server may detect, during a second interval, one or more interactions with the user interface and may update a similarity score associated with the user based on properties associated with the one or more interactions. Accordingly, the server may restore the visual component to the user interface based on the updated similarity score satisfying a similarity threshold.

Abstract: In some aspects, a computing system may generate graph data structures that can be compared with each other to make recommendations. A first graph data structure of the contrasting graphs may be generated based on a first subset of a dataset. For example, the first graph data structure may be generated based on users that have left an organization and graph inference techniques may be used to identify sources that caused the users to leave. A second graph data structure may be generated based on high-performing users of the organization and graph inference techniques may be used to identify potential causes of the users' high performance. The computing system may compare the first and second graph data structures to make recommendations. For example, the computing system may compare the two graphs to determine a modification to make the first graph more similar to the second graph.

Abstract: In some implementations, a data processing device may receive, from a data source, a set of delimiter-separated values and may divide the set of delimiter-separated values into a plurality of subsets. Each subset may correspond to at least a portion of a column or correspond to at least a portion of a row. The data processing device may generate a plurality of vectors, corresponding to the plurality of subsets, according to an embedding space. The data processing device may compare the plurality of vectors to each other and may select a row or a column of the set of delimiter-separated values as one or more headers based on comparing the plurality of vectors to each other. Accordingly, the data processing device may output a tabular data structure including the one or more headers distinguished from a remainder of the set of delimiter-separated values.

Abstract: Systems, methods, and apparatuses for automatically generating reduced training datasets are described. A training dataset may be inputted into a machine learning model to train the machine learning model to output a label. The machine learning model may comprise nodes, and each of the nodes may be associated with a weight. Based on datapoints, changes to the weight associated with each node of the plurality of nodes may be determined. Using model explainability techniques and based on the changes to the weight associated with each node of the plurality of nodes, pathways that decrease an accuracy of the machine learning model are identified. A first set of the datapoints that correlate with pathways that decrease the accuracy of the machine learning model outputting the label may be determined. Furthermore, the first set of the datapoints may be removed from the training dataset to generate a reduced training dataset.