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公开(公告)号：US10776334B2
公开(公告)日：2020-09-15
申请号：US16736673
申请日：2020-01-07
发明人： Shaosheng Cao , Xinxing Yang , Jun Zhou , Xiaolong Li
IPC分类号： G06F16/00 , G06F16/22 , G06F16/27 , G06F16/28 , G06F16/906
摘要： Embodiments of the present specification disclose random walking and a cluster-based random walking method, apparatus and device. A solution includes: obtaining information about each node included in graph data, generating, according to the information about each node, an index vector reflecting a degree value of a respective node, then generating an element vector reflecting an identifier of an adjacent node of the node, and generating a random sequence according to the index vector and the element vector, to implement random walks in the graph data. The solution is applicable to clusters and individual machines.
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2.发明申请公开(公告)号：US20200034740A1
公开(公告)日：2020-01-30
申请号：US16587977
申请日：2019-09-30
发明人： Xinxing Yang , Shaosheng Cao , Jun Zhou , Xiaolong Li
摘要： An N×M dimensional target matrix is generated based on N data samples and M dimensional data features respectively corresponding to the N data samples. Encryption calculation is performed on the N×M dimensional target matrix based on a Principal Component Analysis (PCA) algorithm to obtain an N×K dimensional encryption matrix K is less than M. The N×K dimensional encryption matrix is transmitted to a modeling server. The modeling server trains a machine learning model by using the N×K dimensional encryption matrix as a training sample.
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公开(公告)号：US10769383B2
公开(公告)日：2020-09-08
申请号：US16743224
申请日：2020-01-15
发明人： Shaosheng Cao , Xinxing Yang , Jun Zhou , Xiaolong Li
摘要： Embodiments of the present application disclose a cluster-based word vector processing method, apparatus, and device. Solutions are include: in a cluster having a server cluster and a worker computer cluster, in which each worker computer in the worker computer cluster separately reads some corpuses in parallel, extracts a word and context words of the word from the read corpuses, obtains corresponding word vectors from a server in the server cluster, and trains the corresponding word vectors, and the server cluster updates word vectors of same words that are stored before the training according to training results of one or more respective worker computers with respect to the word vectors of the same words.
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公开(公告)号：US20200349416A1
公开(公告)日：2020-11-05
申请号：US16812105
申请日：2020-03-06
发明人： Xinxing Yang , Longfei Li , Jun Zhou
摘要： Implementations of the present specification provide a method for determining a computer-executed ensemble model. The method includes: obtaining a current ensemble model and a plurality of untrained candidate submodels; integrating each of the plurality of candidate submodels into the current ensemble model to obtain a plurality of first candidate ensemble models; training at least the plurality of first candidate ensemble models to obtain a plurality of second candidate ensemble models after this training; performing performance evaluation on each of the plurality of second candidate ensemble models to obtain corresponding performance evaluation results; determining, based on the performance evaluation results, an optimal candidate ensemble model with optimal performance from the plurality of second candidate ensemble models; and updating the current ensemble model with the optimal candidate ensemble model if the performance of the optimal candidate ensemble model satisfies a predetermined condition.
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公开(公告)号：US20200177390A1
公开(公告)日：2020-06-04
申请号：US16779498
申请日：2020-01-31
发明人： Xinxing Yang , Benquan Yu , Yize Li , Yuan Zhang , Haizhen Zhuo
摘要： Implementations of this specification provide a method and an apparatus for providing data verification in a blockchain ledger. An example method includes receiving, from a client and by a database server that is configured to store data using the blockchain ledger, an instruction that includes a verification method parameter and a verification range parameter for the database server. The verification method parameter is used to indicate a computing device on which verification is to be performed, and the verification range parameter includes a block height or a hash value, and is used to determine a range of a to-be-verified data block or a data record in the ledger. The database server determines the computing device on which verification is to be performed, based on the verification method parameter. The database server determines to-be-verified data based on the verification range parameter.
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