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公开(公告)号：US20210406767A1
公开(公告)日：2021-12-30
申请号：US17142822
申请日：2021-01-06
Inventor： Daxiang DONG , Weibao GONG , Yi LIU , Dianhai YU , Yanjun MA , Haifeng WANG
IPC: G06N20/00 , G06F16/182 , G06N5/04
Abstract: The present application discloses a distributed training method and system, a device and a storage medium, and relates to technical fields of deep learning and cloud computing. The method includes: sending, by a task information server, a first training request and information of an available first computing server to at least a first data server; sending, by the first data server, a first batch of training data to the first computing server, according to the first training request; performing, by the first computing server, model training according to the first batch of training data, sending model parameters to the first data server so as to be stored after the training is completed, and sending identification information of the first batch of training data to the task information server so as to be recorded; wherein the model parameters are not stored at any one of the computing servers.
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12.发明申请公开(公告)号：US20210294975A1
公开(公告)日：2021-09-23
申请号：US17015411
申请日：2020-09-09
Inventor： Xinchao XU , Haifeng WANG , Hua WU , Zhanyi LIU
IPC: G06F40/284 , G10L15/06 , G06N3/08 , G10L15/04 , G06F40/274
Abstract: A method, an electronic device and a readable storage medium for creating a label marking model are disclosed. According to an embodiment, the method for creating the label marking model includes: obtaining text data and determining a word or phrase to be marked in the text data; according to the word or phrase to be marked, constructing a first training sample of the text data corresponding to a word or phrase replacing task and a second training sample corresponding to a label marking task; training a neural network model with a plurality of the first training samples and a plurality of the second training samples, respectively, until a loss function of the word or phrase replacing task and a loss function of the label marking task satisfy a preset condition, to obtain the label marking model. The technical solution may improve the accuracy of the label marking model.
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公开(公告)号：US20210209417A1
公开(公告)日：2021-07-08
申请号：US17209576
申请日：2021-03-23
Inventor： Daxiang DONG , Wenhui ZHANG , Zhihua WU , Dianhai YU , Yanjun MA , Haifeng WANG
Abstract: A method and an apparatus for generating a shared encoder are provided, which belongs to a field of computer technology and deep learning. The method includes: sending by a master node a shared encoder training instruction to child nodes, so that each child node obtains training samples based on a type of a target shared encoder included in the training instruction; sending an initial parameter set of the target shared encoder to be trained to each child node after obtaining a confirmation message returned by each child node; obtaining an updated parameter set of the target shared encoder returned by each child node; determining a target parameter set corresponding to the target shared encoder based on a first preset rule and the updated parameter set of the target shared encoder returned by each child node.
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公开(公告)号：US20210034993A1
公开(公告)日：2021-02-04
申请号：US16936190
申请日：2020-07-22
Inventor： Miao FAN , Jizhou HUANG , An ZHUO , Ying LI , Ping LI , Haifeng WANG
Abstract: A POI valuation method, apparatus, device and computer storage medium are disclosed. The method comprises: obtaining information of first POIs with known values and information of second POIs with unknown values within a regional range; creating a valuation model which is configured to revaluate a first POI using values of surrounding POIs of the first POI, the surrounding POIs including other first POIs and second POIs within a predetermined range of distance from the first POI, and adjusting values of second POIs in the surrounding POIs using an error between a revaluated value of first POI and the known value of the first POI; training the valuation model until the error is minimized; obtaining the values of the second POIs from the valuation model. The solutions may reduce the requirement for manpower and improve the valuation efficiency as compared with manually valuation of POIs one by one.
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公开(公告)号：US20180357570A1
公开(公告)日：2018-12-13
申请号：US16006208
申请日：2018-06-12
Inventor： Ke SUN , Shiqi ZHAO , Dianhai YU , Haifeng WANG
CPC classification number: G06N99/005 , G06F7/14 , G06F17/2785
Abstract: A method and apparatus for building a conversation understanding system based on artificial intelligence, a device and a computer-readable storage medium. In embodiments of the present disclosure, it is feasible to obtain the training feedback information provided by conversation service conducted by the user and the basic conversation understanding system, then according to the training feedback information, perform adjustment processing for a service state of the basic conversation understanding system, to obtain an adjustment state of the basic conversation understanding system. It is possible to perform data merging processing according to the training feedback information and the adjustment state of the basic conversation understanding system, to obtain model training data for building the model conversation understanding system. This method does not require persons to participate in annotation operations of the training data, exhibits simple operations and a high correctness rate, improving the efficiency and reliability of the conversation understanding system.
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Patent Agency Ranking
公开(公告)号：US20170228459A1
公开(公告)日：2017-08-10
申请号：US15384141
申请日：2016-12-19
Inventor： Haifeng WANG , Shiqi ZHAO , Haifeng WU , Tian WU , Daisong GUAN
CPC classification number: G06F16/951 , G06F16/9535 , G06N20/00
Abstract: A method and a device for mobile searching based on artificial intelligence are provided in the present disclosure. The method includes: displaying a search box, and receiving a query inputted by a user via the search box; obtaining a search result according to the query, and displaying the search result on a search result page; after receiving a click instruction on the search result, displaying a context page corresponding to the search result; and after receiving a click instruction on a result in the search result or in the context page, displaying a content page corresponding to the result clicked. The method can break through the concept of PC search and provide a search method which is more suitable for a mobile search scene.
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公开(公告)号：US20220100786A1
公开(公告)日：2022-03-31
申请号：US17407320
申请日：2021-08-20
Inventor： Yuchen DING , Yingqi QU , Jing LIU , Kai LIU , Dou HONG , Hua WU , Haifeng WANG
Abstract: The present application discloses a method and apparatus for training a retrieval model, device and computer storage medium that relate to intelligent search and natural language processing technologies. An implementation includes: acquiring initial training data; performing a training operation using the initial training data to obtain an initial retrieval model; selecting texts with the correlation degrees with a query in the training data meeting a preset first requirement from candidate texts using the initial retrieval model; performing a training operation using the updated training data to obtain a first retrieval model; and selecting texts with the correlation degrees with the query in the training data meeting a preset second requirement from the candidate texts using the first retrieval model; and/or selecting texts with the correlation degrees with the query meeting a preset third requirement; and performing a training operation using the expanded training data to obtain a second retrieval model.
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公开(公告)号：US20220019744A1
公开(公告)日：2022-01-20
申请号：US17319189
申请日：2021-05-13
Inventor： Fei YU , Jiji TANG , Weichong YIN , Yu SUN , Hao TIAN , Hua WU , Haifeng WANG
Abstract: A multi-modal pre-training model acquisition method, an electronic device and a storage medium, which relate to the fields of deep learning and natural language processing, are disclosed. The method may include: determining, for each image-text pair as training data, to-be-processed fine-grained semantic word in the text; masking the to-be-processed fine-grained semantic words; and training the multi-modal pre-training model using the training data with the fine-grained semantic words masked.
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公开(公告)号：US20210255896A1
公开(公告)日：2021-08-19
申请号：US17076346
申请日：2020-10-21
Inventor： Daxiang DONG , Haifeng WANG , Dianhai YU , Yanjun MA
Abstract: Embodiments of the present disclosure disclose a method for processing tasks in parallel, a device and a storage medium, and relate to a field of artificial intelligent technologies. The method includes: determining at least one parallel computing graph of a target task; determining a parallel computing graph and an operator scheduling scheme based on a hardware execution cost of each operator task of each of the at least one parallel computing graph in a cluster, in which the cluster includes a plurality of nodes for executing the plurality of operator tasks, and each parallel computing graph corresponds to at least one operator scheduling scheme; and scheduling and executing the plurality of operator tasks of the determined parallel computing graph in the cluster based on the determined parallel computing graph and the determined operator scheduling scheme.
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公开(公告)号：US20210192151A1
公开(公告)日：2021-06-24
申请号：US16861750
申请日：2020-04-29
Inventor： Haifeng WANG , Hua Wu , Zhongjun He , Hao Xiong
Abstract: The present disclosure provides a method, apparatus, electronic device and readable storage medium for translation and relates to translation technologies. In the embodiments of the present disclosure, the at least one knowledge element is obtained according to associated information of content to be translated, and respective knowledge element in the at least one knowledge element comprise an element of the first language type and an element of the second language type so that the at least one knowledge element can be used to obtain a translation result of the content to be translated. Since the at least one knowledge element obtained in advance is taken as global information of the translation task of this time, it can be ensured that the translation result of the same content to be translated is consistent, thereby improving the quality of the translation result.
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