Abstract: A valve for endovascular heart valve repair that provides improved sealing of the valve against the native wall. The valve assembly has a sealing region at a distal end of the valve. The sealing region having a delivery position and a sealing position, wherein in the delivery position, the sealing region has a first length, and in the sealing position, the sealing region has a second length less than the first length and a thickness in the sealing position is greater in the sealing position than in the delivery position.

Abstract: The present disclosure provides efficient communication techniques for transmission of model updates within a machine learning framework, such as, for example, a federated learning framework in which a high-quality centralized model is trained on training data distributed overt a large number of clients each with unreliable network connections and low computational power. In an example federated learning setting, in each of a plurality of rounds, each client independently updates the model based on its local data and communicates the updated model back to the server, where all the client-side updates are used to update a global model. The present disclosure provides systems and methods that reduce communication costs. In particular, the present disclosure provides at least: structured update approaches in which the model update is restricted to be small and sketched update approaches in which the model update is compressed before sending to the server.

Abstract: The present disclosure provides efficient communication techniques for transmission of model updates within a machine learning framework, such as, for example, a federated learning framework in which a high-quality centralized model is trained on training data distributed overt a large number of clients each with unreliable network connections and low computational power. In an example federated learning setting, in each of a plurality of rounds, each client independently updates the model based on its local data and communicates the updated model back to the server, where all the client-side updates are used to update a global model. The present disclosure provides systems and methods that reduce communication costs. In particular, the present disclosure provides at least: structured update approaches in which the model update is restricted to be small and sketched update approaches in which the model update is compressed before sending to the server.

Abstract: The present disclosure provides efficient communication techniques for transmission of model updates within a machine learning framework, such as, for example, a federated learning framework in which a high-quality centralized model is trained on training data distributed overt a large number of clients each with unreliable network connections and low computational power. In an example federated learning setting, in each of a plurality of rounds, each client independently updates the model based on its local data and communicates the updated model back to the server, where all the client-side updates are used to update a global model. The present disclosure provides systems and methods that reduce communication costs. In particular, the present disclosure provides at least: structured update approaches in which the model update is restricted to be small and sketched update approaches in which the model update is compressed before sending to the server.

Abstract: The present disclosure provides efficient communication techniques for transmission of model updates within a machine learning framework, such as, for example, a federated learning framework in which a high-quality centralized model is trained on training data distributed overt a large number of clients each with unreliable network connections and low computational power. In an example federated learning setting, in each of a plurality of rounds, each client independently updates the model based on its local data and communicates the updated model back to the server, where all the client-side updates are used to update a global model. The present disclosure provides systems and methods that reduce communication costs. In particular, the present disclosure provides at least: structured update approaches in which the model update is restricted to be small and sketched update approaches in which the model update is compressed before sending to the server.

Abstract: The present disclosure provides efficient communication techniques for transmission of model updates within a machine learning framework, such as, for example, a federated learning framework in which a high-quality centralized model is trained on training data distributed overt a large number of clients each with unreliable network connections and low computational power. In an example federated learning setting, in each of a plurality of rounds, each client independently updates the model based on its local data and communicates the updated model back to the server, where all the client-side updates are used to update a global model. The present disclosure provides systems and methods that reduce communication costs. In particular, the present disclosure provides at least: structured update approaches in which the model update is restricted to be small and sketched update approaches in which the model update is compressed before sending to the server.

Abstract: This disclosure relates to a waste heat recovery (WHR) system and method for regulating exhaust gas recirculation (EGR) cooling, and more particularly, to a Rankine cycle WHR system and method, including a recuperator bypass arrangement to regulate EGR exhaust gas cooling for engine efficiency improvement and thermal management. This disclosure describes other unique bypass arrangements for increased flexibility in the ability to regulate EGR exhaust gas cooling.

Abstract: This disclosure relates to a waste heat recovery (WHR) system and method for regulating exhaust gas recirculation (EGR) cooling, and more particularly, to a Rankine cycle WHR system and method, including a recuperator bypass arrangement to regulate EGR exhaust gas cooling for engine efficiency improvement and thermal management. This disclosure describes other unique bypass arrangements for increased flexibility in the ability to regulate EGR exhaust gas cooling.

Abstract: This disclosure relates to a waste heat recovery (WHR) system and method for regulating exhaust gas recirculation (EGR) cooling, and more particularly, to a Rankine cycle WHR system and method, including a recuperator bypass arrangement to regulate EGR exhaust gas cooling for engine efficiency improvement and thermal management. This disclosure describes other unique bypass arrangements for increased flexibility in the ability to regulate EGR exhaust gas cooling.

Abstract: This disclosure relates to a waste heat recovery (WHR) system and method for regulating exhaust gas recirculation (EGR) cooling, and more particularly, to a Rankine cycle WHR system and method, including a recuperator bypass arrangement to regulate EGR exhaust gas cooling for engine efficiency improvement and thermal management. This disclosure describes other unique bypass arrangements for increased flexibility in the ability to regulate EGR exhaust gas cooling.

Abstract: The invention relates to a cap (1, 1') for closing a bottle (2) or similar container having a projecting outer annular ridge (10) in the region of its container aperture. The cap (1, 1') has an inner cap section (3) with spring pins (7) which engage the annular ridge (10) of the bottle (2) from under in the closed position and can be secured in this engaged position by an outer cap section (4) in the form of a slide ring.