Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: The disclosed embodiments relate to implementation, such as by a message processing system architecture, of a message handling system and/or protocol which mitigates optimistic messaging behavior. As used herein optimistic messaging behavior may at least refer to the transmission, in whole or in part, of a message, or of one or more messages of a sequence thereof, to a receiving system, such as the system implemented by the disclosed embodiments, prior to the sender determining that the message(s) is/are desired, alone or in conjunction with subsequently canceling or otherwise invalidating the message(s) once it has been determined that it is not desired. The disclosed embodiments mitigate such behavior by detecting and taking action with respect to these types of messages to deter optimizing behavior which may or may not be manipulative, while maintaining reliable message handling under increasing processing loads with minimal impact on users being able to send messages to the system.

Abstract: The disclosed embodiments relate to implementation, such as by a message processing system architecture, of a message handling system and/or protocol which mitigates optimistic messaging behavior. Optimistic messaging behavior may at least refer to the transmission, in whole or in part, of a message, or of one or more messages of a sequence thereof, to a receiving system, such as the system implemented by the disclosed embodiments, prior to the sender determining that the message(s) is/are desired, alone or in conjunction with subsequently canceling or otherwise invalidating the message(s) once it has been determined that it is not desired. The disclosed embodiments mitigate such behavior by detecting and taking action with respect to these types of messages to deter optimizing behavior which may or may not be manipulative, while maintaining reliable message handling under increasing processing loads with minimal impact on users being able to send messages to the system.

Abstract: The disclosed embodiments relate to implementation, such as by a message processing system architecture, of a message handling system and/or protocol which mitigates optimistic messaging behavior. As used herein optimistic messaging behavior may at least refer to the transmission, in whole or in part, of a message, or of one or more messages of a sequence thereof, to a receiving system, such as the system implemented by the disclosed embodiments, prior to the sender determining that the message(s) is/are desired, alone or in conjunction with subsequently canceling or otherwise invalidating the message(s) once it has been determined that it is not desired. The disclosed embodiments mitigate such behavior by detecting and taking action with respect to these types of messages to deter optimizing behavior which may or may not be manipulative, while maintaining reliable message handling under increasing processing loads with minimal impact on users being able to send messages to the system.

Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors.