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1.发明授权公开(公告)号：US11481671B2
公开(公告)日：2022-10-25
申请号：US16413987
申请日：2019-05-16
发明人： Vishwas Siravara , Peijie Li , Yu Gu
摘要： Provided is a system for verifying integrity of a machine learning model, the system includes at least one processor programmed or configured to determine whether an output of a machine learning model based on an input corresponds to a reference output of the machine learning model based on the input, serialize the machine learning model into a file, calculate a file integrity value of the file using a file integrity detection function, determine whether the file integrity value corresponds to a reference file integrity value of the file, and perform an operation with the machine learning model based on determining that the file integrity value corresponds to the reference file integrity value of the file. A method and computer program product are also disclosed.
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公开(公告)号：US11243929B2
公开(公告)日：2022-02-08
申请号：US16058724
申请日：2018-08-08
发明人： Peijie Li , Yu Gu , Hongqin Song
IPC分类号： G06F16/22 , G06F16/23 , G06F12/0875 , G06F12/126
摘要： A data system may dynamically prioritize and ingest data so that, regardless of the memory size of the dataset hosted by the data system, it may process and analyze the hosted dataset in constant time. The system and method may implement a first space-efficient probabilistic data structure on the dataset, wherein the dataset includes a plurality of profile data. It may then receive update data corresponding to some of the plurality of profile data and implement a second space-efficient probabilistic data structure on the dataset including the update data. The system and method may then determine a set of non-shared profile data of the second space-efficient probabilistic data structure and prioritize the set of non-shared profile data of the second space-efficient probabilistic data structure over other profile data of the dataset for caching.
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