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SYSTEM AND METHOD FOR OPTIMIZING DATA PROCESSING IN CLOUD-BASED, MACHINE LEARNING ENVIRONMENTS THROUGH THE USE OF SELF ORGANIZING MAP
SYSTEM AND METHOD FOR OPTIMIZING DATA PROCESSING IN CLOUD-BASED, MACHINE LEARNING ENVIRONMENTS THROUGH THE USE OF SELF ORGANIZING MAP
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机译:通过使用自组织映射在基于云的机器学习环境中优化数据处理的系统和方法
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摘要
Methods and system are described for optimizing data processing in cloud-based, machine learning environments. For example, through the use of a machine learning model utilizing a self organizing map and/or the use of specific processing nodes in a computer system to perform specific tasks the methods and system may more efficiently distribute tasks through a cloud computing environment and increase overall processing speeds despite increasing amounts of data. The methods and system described herein are particularly related to collateral allocation computer systems that automate the management of numerous collateral assets. For example, as the amount of collateral assets and the complexity of given transactions grow, typical allocation systems face frequent processing delays related to collateral allocations (e.g., allocations of collateral associated with Tri-Party Repos).
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