Abstract: Systems and methods are described for developing and using neural network models. An example method of training a neural network includes: oscillating a learning rate while performing a preliminary training of a neural network; determining, based on the preliminary training, a number of training epochs to perform for a subsequent training session, and training the neural network using the determined number of training epochs. The systems and methods can be used to build neural network models that efficiently and accurately handle heterogeneous data.

Abstract: Systems and methods are described for developing and using neural network models. An example method of training a neural network includes: oscillating a learning rate while performing a preliminary training of a neural network; determining, based on the preliminary training, a number of training epochs to perform for a subsequent training session; and training the neural network using the determined number of training epochs. The systems and methods can be used to build neural network models that efficiently and accurately handle heterogeneous data.

Abstract: Systems and methods are described for developing and using neural network models. An example method of training a neural network includes: oscillating a learning rate while performing a preliminary training of a neural network; determining, based on the preliminary training, a number of training epochs to perform for a subsequent training session; and training the neural network using the determined number of training epochs. The systems and methods can be used to build neural network models that efficiently and accurately handle heterogeneous data.

Abstract: The system and method described herein relates to managing multiple network device connections, collecting event source data from one or more network devices with one or more collectors, filtering the event source data, continuously monitoring the network device connections, controlling raw data collection from the one or more network devices, parsing the event source data into normalized data structures, and managing configurations for the collectors, among other things. Event sources may be physical or logical network devices distributed across a network, including but not limited to, firewalls, routers, biometric devices, mainframes, databases, and applications. The network devices may be sources from which the collectors may receive or request the event source data.

Abstract: The system and method described herein relates to managing multiple network device connections, collecting event source data from one or more network devices with one or more collectors, filtering the event source data, continuously monitoring the network device connections, controlling raw data collection from the one or more network devices, parsing the event source data into normalized data structures, and managing configurations for the collectors, among other things. Event sources may be physical or logical network devices distributed across a network, including but not limited to, firewalls, routers, biometric devices, mainframes, databases, and applications. The network devices may be sources from which the collectors may receive or request the event source data.

Abstract: This disclosure describes a low-density parity-check (LDPC) decoder that is configured to decode a codeword using an iterative process. The decoder includes a first syndrome memory configured to store a syndrome result determined in a previous iteration. The decoder further includes circuitry to flip bits of the codeword based on the syndrome result and one or more parity-check equations, and a second syndrome memory configured to update a current syndrome result during a current iteration based on the bits of the codeword that are flipped by the circuitry.

Abstract: This disclosure describes a low-density parity-check (LDPC) decoder that is configured to decode a codeword using an iterative process. The decoder includes a memory to store the codeword and a first syndrome memory configured to store a syndrome result determined in a previous iteration. The decoder further includes circuitry to flip bits of the codeword based on the syndrome result and one or more parity-check equations, and a second syndrome memory configured to update a current syndrome result during a current iteration based on the bits of the codeword that are flipped by the circuitry.

Abstract: The system and method described herein relates to managing multiple network device connections, collecting event source data from one or more network devices with one or more collectors, filtering the event source data, continuously monitoring the network device connections, controlling raw data collection from the one or more network devices, parsing the event source data into normalized data structures, and managing configurations for the collectors, among other things. Event sources may be physical or logical network devices distributed across a network, including but not limited to, firewalls, routers, biometric devices, mainframes, databases, and applications. The network devices may be sources from which the collectors may receive or request the event source data.

Abstract: The system and method described herein relates to managing multiple network device connections, collecting event source data from one or more network devices with one or more collectors, filtering the event source data, continuously monitoring the network device connections, controlling raw data collection from the one or more network devices, parsing the event source data into normalized data structures, and managing configurations for the collectors, among other things. Event sources may be physical or logical network devices distributed across a network, including but not limited to, firewalls, routers, biometric devices, mainframes, databases, and applications. The network devices may be sources from which the collectors may receive or request the event source data.

Abstract: A computer-implemented device provides security events from publishers to subscribers. There is provided a message bus, configured to contain a plurality of security events. Also provided is a receiver unit, responsive to a plurality of publishers, to receive the plurality of security events from the publishers. There is also a queue unit, responsive to receipt of the security events, to queue the plurality of security events in the message bus. Also, there is a transport unit, responsive to the security events in the message bus, to transport the plurality of security events in the message bus to a plurality of subscribers.

Abstract: A computer-implemented device provides security events from publishers to subscribers. There is provided a message bus, configured to contain a plurality of security events. Also provided is a receiver unit, responsive to a plurality of publishers, to receive the plurality of security events from the publishers. There is also a queue unit, responsive to receipt of the security events, to queue the plurality of security events in the message bus. Also, there is a transport unit, responsive to the security events in the message bus, to transport the plurality of security events in the message bus to a plurality of subscribers.

Abstract: A system and method that relates to managing multiple network device connections and/or collectors for collecting event source data from one or more network devices, filtering event source data, continuously monitoring connection status to the one or more network devices, controlling raw data collection from the one or more network devices, parsing event source data into normalized data structures, and/or managing collector configurations, among other things. Event sources may be network devices (physical or logical) across a network, including but not limited to, firewalls, routers, biometric devices, mainframes, databases and/or applications. A network device may be a source from which a collector may receive and/or request event data.