Abstract: A method for controlling a robotic system includes determining a location and/or a pose of a power system component based on data received from one or more sensors, and determining a mapping of a location of a robotic system within a model of an external environment of the robotic system based on the data. The model of the external environment provides locations of objects external to the robotic system. A sequence of movements of components of the robotic system is determined to perform maintenance on the power system component based on the locations of the objects external to the robotic system and/or the location or pose of the power system component. One or more control signals are communicated to remotely control movement of the components of the robotic system based on the sequence or movements of the components to perform maintenance on the power system component.

Abstract: Methods, computer readable media, devices, and systems provide for distributed machine learning. In one aspect, a method of training a model is disclosed. The method includes receiving, by a client device, from one or more servers, an intermediate model, training, by the client device, the intermediate model based on private data, and transmitting, by the client device, to the one or more servers, the trained intermediate model.

Abstract: Provided are systems and methods that improve the computational efficiency of Transformers or other attention-based neural networks or machine learning models by re-using a number of attention scores between layers and/or heads of the model. To reduce the computational cost of self-attention-based models while achieving comparable or even superior results, example aspects of the present disclosure propose a novel architecture that reuses attention scores computed in one layer in one or multiple subsequent layers.

Abstract: Embodiments are described that are directed to optimizing the provisioning of payment account credentials to mobile devices utilizing mobile wallets. In some embodiments, one of multiple provisioning schemes may be selectively chosen for payment account credential provisioning based upon a determined risk involved with a particular provisioning request. A low risk provisioning request leads to an immediate provisioning of a payment credential, whereas a provisioning request of high risk results in the provisioning request being denied. In some embodiments, medium risk provisioning requests will cause an additional user authentication to be performed before the payment account provisioning is finalized. The additional user authentication may occur using a separate communication channel than the channel in which the provisioning request was received.

Abstract: Methods, computer readable media, devices, and systems provide for distributed machine learning. In one aspect, a method of training a model is disclosed. The method includes receiving, by a client device, from one or more servers, an intermediate model, training, by the client device, the intermediate model based on private data, and transmitting, by the client device, to the one or more servers, the trained intermediate model.

Abstract: Embodiments are described that are directed to optimizing the provisioning of payment account credentials to mobile devices utilizing mobile wallets. In some embodiments, one of multiple provisioning schemes may be selectively chosen for payment account credential provisioning based upon a determined risk involved with a particular provisioning request. A low risk provisioning request leads to an immediate provisioning of a payment credential, whereas a provisioning request of high risk results in the provisioning request being denied. In some embodiments, medium risk provisioning requests will cause an additional user authentication to be performed before the payment account provisioning is finalized. The additional user authentication may occur using a separate communication channel than the channel in which the provisioning request was received.

Abstract: Methods, computer readable media, devices, and systems provide for distributed machine learning. In one aspect, a method of training a model is disclosed. The method includes receiving, by a client device, from one or more servers, an intermediate model, training, by the client device, the intermediate model based on private data, and transmitting, by the client device, to the one or more servers, the trained intermediate model.

Abstract: A method for authentication using location correlation is disclosed. The method includes determining geographic zones and zone identifiers associated with a location of a mobile communication device. Later, transaction data is received and a zone identifier is determined from that transaction data. If the zone identifier matches one of the previously determined zone identifiers, then a match indicator is sent to an authorizing entity computer system or the transaction may be allowed to proceed.

Abstract: Embodiments of the present invention are directed to methods, apparatuses, computer readable media and systems for securely processing remote transactions. One embodiment of the invention is directed to a method of processing a remote transaction initiated by a mobile device comprising a server computer receiving a payment request including encrypted payment information. The encrypted payment information being generated by a mobile payment application of the mobile device and being encrypted using a third party key. The method further comprises decrypting the encrypted payment information using the third party key, determining a transaction processor public key associated with the payment information, and re-encrypting the payment information using the transaction processor public key. The method further comprises sending a payment response including the re-encrypted payment information to a transaction processor.

Abstract: A method for authentication using location correlation is disclosed. The method includes determining geographic zones and zone identifiers associated with a location of a mobile communication device. Later, transaction data is received and a zone identifier is determined from that transaction data. If the zone identifier matches one of the previously determined zone identifiers, then a match indicator is sent to an authorizing entity computer system or the transaction may be allowed to proceed.

Abstract: Embodiments of the present invention are directed to methods, apparatuses, computer readable media and systems for securely processing remote transactions. One embodiment of the invention is directed to a method of processing a remote transaction initiated by a mobile device comprising a server computer receiving a payment request including encrypted payment information. The encrypted payment information being generated by a mobile payment application of the mobile device and being encrypted using a third party key. The method further comprises decrypting the encrypted payment information using the third party key, determining a transaction processor public key associated with the payment information, and re-encrypting the payment information using the transaction processor public key. The method further comprises sending a payment response including the re-encrypted payment information to a transaction processor.

Abstract: A method for authentication using location correlation is disclosed. The method includes determining geographic zones and zone identifiers associated with a location of a mobile communication device. Later, transaction data is received and a zone identifier is determined from that transaction data. If the zone identifier matches one of the previously determined zone identifiers, then a match indicator is sent to an authorizing entity computer system or the transaction may be allowed to proceed.

Abstract: Embodiments of the present invention are directed to methods, apparatuses, computer readable media and systems for securely processing remote transactions. One embodiment of the invention is directed to a method of processing a remote transaction initiated by a mobile device comprising a server computer receiving a payment request including encrypted payment information. The encrypted payment information being generated by a mobile payment application of the mobile device and being encrypted using a third party key. The method further comprises decrypting the encrypted payment information using the third party key, determining a transaction processor public key associated with the payment information, and re-encrypting the payment information using the transaction processor public key. The method further comprises sending a payment response including the re-encrypted payment information to a transaction processor.

Abstract: Embodiments of the present invention are directed to methods, apparatuses, computer readable media and systems for securely processing remote transactions. One embodiment of the invention is directed to a method of processing a remote transaction initiated by a mobile device comprising a server computer receiving a payment request including encrypted payment information. The encrypted payment information being generated by a mobile payment application of the mobile device and being encrypted using a third party key. The method further comprises decrypting the encrypted payment information using the third party key, determining a transaction processor public key associated with the payment information, and re-encrypting the payment information using the transaction processor public key. The method further comprises sending a payment response including the re-encrypted payment information to a transaction processor.

Abstract: Embodiments are described that are directed to optimizing the provisioning of payment account credentials to mobile devices utilizing mobile wallets. In some embodiments, one of multiple provisioning schemes may be selectively chosen for payment account credential provisioning based upon a determined risk involved with a particular provisioning request. A low risk provisioning request leads to an immediate provisioning of a payment credential, whereas a provisioning request of high risk results in the provisioning request being denied. In some embodiments, medium risk provisioning requests will cause an additional user authentication to be performed before the payment account provisioning is finalized. The additional user authentication may occur using a separate communication channel than the channel in which the provisioning request was received.

Abstract: Embodiments are described that are directed to optimizing the provisioning of payment account credentials to mobile devices utilizing mobile wallets. In some embodiments, one of multiple provisioning schemes may be selectively chosen for payment account credential provisioning based upon a determined risk involved with a particular provisioning request. A low risk provisioning request leads to an immediate provisioning of a payment credential, whereas a provisioning request of high risk results in the provisioning request being denied. In some embodiments, medium risk provisioning requests will cause an additional user authentication to be performed before the payment account provisioning is finalized. The additional user authentication may occur using a separate communication channel than the channel in which the provisioning request was received.

Abstract: Rules, applied to deny authorization of likely fraudulent transactions, are derived from a modified Patient Rule Induction Method algorithm that uses a target variable and a data set of past transactions each associated with a plurality of input variables and a hyper-rectangle enclosing a multi-dimensional space defined by a representation of the input variable values as points within the multi-dimensional space. While a count of the points within the hyper-rectangle is greater than a minimum support parameter, a first plurality of points proximal to edges of the hyper-rectangle are removed, where each such removing maximizes a mean value of the target variable, and then, while the mean value remains maximized, a second plurality of points proximal to the edges is added, where each adding maximizes or maintains the mean value. The hyper-rectangle is bounded within a minimum bounding box that defines the rules.

Abstract: Rules, applied to deny authorization of likely fraudulent transactions, are derived from a modified Patient Rule Induction Method algorithm that uses a target variable and a data set of past transactions each associated with a plurality of input variables and a hyper-rectangle enclosing a multi-dimensional space defined by a representation of the input variable values as points within the multi-dimensional space. While a count of the points within the hyper-rectangle is greater than a minimum support parameter, a first plurality of points proximal to edges of the hyper-rectangle are removed, where each such removing maximizes a mean value of the target variable, and then, while the mean value remains maximized, a second plurality of points proximal to the edges is added, where each adding maximizes or maintains the mean value. The hyper-rectangle is bounded within a minimum bounding box that defines the rules.

Abstract: Rules, applied to deny authorization of likely fraudulent transactions, are derived from a modified Patient Rule Induction Method algorithm that uses a target variable and a data set of past transactions each associated with a plurality of input variables and a hyper-rectangle enclosing a multi-dimensional space defined by a representation of the input variable values as points within the multi-dimensional space. While a count of the points within the hyper-rectangle is greater than a minimum support parameter, a first plurality of points proximal to edges of the hyper-rectangle are removed, where each such removing maximizes a mean value of the target variable, and then, while the mean value remains maximized, a second plurality of points proximal to the edges is added, where each adding maximizes or maintains the mean value. The hyper-rectangle is bounded within a minimum bounding box that defines the rules.

Abstract: Rules, applied to deny authorization of likely fraudulent transactions, are derived from a modified Patient Rule Induction Method algorithm that uses a target variable and a data set of past transactions each associated with a plurality of input variables and a hyper-rectangle enclosing a multi-dimensional space defined by a representation of the input variable values as points within the multi-dimensional space. While a count of the points within the hyper-rectangle is greater than a minimum support parameter, a first plurality of points proximal to edges of the hyper-rectangle are removed, where each such removing maximizes a mean value of the target variable, and then, while the mean value remains maximized, a second plurality of points proximal to the edges is added, where each adding maximizes or maintains the mean value. The hyper-rectangle is bounded within a minimum bounding box that defines the rules.