Abstract: Systems and methods for document classification are described. Embodiments of the present disclosure generate classification data for a plurality of samples using a neural network trained to identify a plurality of known classes; select a set of samples for annotation from the plurality of samples using an open-set metric based on the classification data, wherein the annotation includes an unknown class; and train the neural network to identify the unknown class based on the annotation of the set of samples.

Abstract: Exemplary embodiments relate to techniques for improving startup times of a cloud-based virtual servers in response to a spike in service usage (although other applications are contemplated and described). According to some embodiments, in response to a request to provision a new virtual server in a cluster, high-priority services (e.g., those that enable the server to respond to system health checks or that support an application providing the service) are started while lower-priority services are delayed. In some embodiments, prior to receiving such a request, a new server may be started and then hibernated to create a “hot spare.” When the request is received, the hot spare may be taken out of hibernation to quickly bring the hot spare online. It is contemplated that the delayed-startup and hot spare embodiments may be used together to further improve performance.

Abstract: Exemplary embodiments relate to techniques for improving startup times of a cloud-based virtual servers in response to a spike in service usage (although other applications are contemplated and described). According to some embodiments, in response to a request to provision a new virtual server in a cluster, high-priority services (e.g., those that enable the server to respond to system health checks or that support an application providing the service) are started while lower-priority services are delayed. In some embodiments, prior to receiving such a request, a new server may be started and then hibernated to create a “hot spare.” When the request is received, the hot spare may be taken out of hibernation to quickly bring the hot spare online. It is contemplated that the delayed-startup and hot spare embodiments may be used together to further improve performance.

Abstract: Exemplary embodiments relate to techniques for improving startup times of a cloud-based virtual servers in response to a spike in service usage (although other applications are contemplated and described). According to some embodiments, in response to a request to provision a new virtual server in a cluster, high-priority services (e.g., those that enable the server to respond to system health checks or that support an application providing the service) are started while lower-priority services are delayed. In some embodiments, prior to receiving such a request, a new server may be started and then hibernated to create a “hot spare.” When the request is received, the hot spare may be taken out of hibernation to quickly bring the hot spare online. It is contemplated that the delayed-startup and hot spare embodiments may be used together to further improve performance.

Abstract: Exemplary embodiments relate to techniques for improving startup times of a cloud-based virtual servers in response to a spike in service usage (although other applications are contemplated and described). According to some embodiments, in response to a request to provision a new virtual server in a cluster, high-priority services (e.g., those that enable the server to respond to system health checks or that support an application providing the service) are started while lower-priority services are delayed. In some embodiments, prior to receiving such a request, a new server may be started and then hibernated to create a “hot spare.” When the request is received, the hot spare may be taken out of hibernation to quickly bring the hot spare online. It is contemplated that the delayed-startup and hot spare embodiments may be used together to further improve performance.