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公开(公告)号：US20230162087A1
公开(公告)日：2023-05-25
申请号：US17989243
申请日：2022-11-17
Inventor： Ji LIU , Chendi ZHOU , Beichen MA , Jiwen ZHOU , Dejing DOU
CPC classification number: G06N20/00 , G06F9/4881
Abstract: A federated learning method, an electronic device, and a storage medium, which relate to a field of artificial intelligence, in particular to fields of distributed data processing and deep learning. The method includes: determining, for each task in a current learning period, a set of target devices corresponding to the task according to respective scheduling information of a plurality of candidate devices corresponding to the task based on a scheduling policy, the scheduling policy enables a time cost information and a device fairness evaluation information of completing the task in the current learning period to meet a predetermined condition; transmitting a global model corresponding to each task to a set of target devices corresponding to the task; and updating the corresponding global model based on trained models in response to receiving the trained models from the corresponding set of target devices.
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公开(公告)号：US20230153550A1
公开(公告)日：2023-05-18
申请号：US18096297
申请日：2023-01-12
Inventor： Liwen ZHANG , Meng SUN , Zhi LI , Zhongjun HE
Abstract: A machine translation method can include: acquiring a to-be-translated source text; generating an intervention text corresponding to the to-be-translated source text by using intervention symbols, the intervention text including a term vocabulary part and an other text part; translating the intervention text to obtain a first translation result of the intervention text, where the first translation result includes a translation result of the other text part and the term vocabulary part; and generating a target translated text of the to-be-translated source text based on the first translation result and preset translated content of the term vocabulary part.
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公开(公告)号：US20230153543A1
公开(公告)日：2023-05-18
申请号：US17951216
申请日：2022-09-23
Inventor： Ruiqing ZHANG , Xiyang WANG , Hui LIU , Zhongjun HE , Zhi LI , Hua WU
Abstract: A translation method, a model training method, apparatuses, electronic devices and storage mediums, which relate to the field of artificial intelligence technologies, such as machine learning technologies, information processing technologies, are disclosed. In an implementation, a weight for each translation model in at least two pre-trained translation models translating a to-be-translated specified sentence is acquired based on the specified sentence and a pre-trained weighting model; and the specified sentence is translating using the at least two translation models based on the weight for each translation model translating the specified sentence.
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704.发明公开公开(公告)号：US20230153357A1
公开(公告)日：2023-05-18
申请号：US18157470
申请日：2023-01-20
Inventor： Chang LIU , Wei LIU , Qian ZHANG
IPC: G06F16/903
CPC classification number: G06F16/90335
Abstract: A method of processing an observation information, an electronic device and a storage medium are provided, which are related to a field of data processing technology, in particular to fields of intelligent searching, cloud computing and big data. The method includes: obtaining the observation information generated in a process of processing a query request; determining a scene identification corresponding to the observation information; and outputting the observation information to a corresponding target position for storage according to the scene identification.
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705.发明公开公开(公告)号：US20230153337A1
公开(公告)日：2023-05-18
申请号：US18157452
申请日：2023-01-20
Inventor： Wenbin JIANG , Yajuan LV , Chunguang CHAI , Yong ZHU
IPC: G06F16/332 , G06F40/30
CPC classification number: G06F16/3329 , G06F40/30
Abstract: A question answering method, a method of training a question answering model, a device, and a medium are provided, which relate to a field of artificial intelligence technology, in particular to fields of natural language processing technology, deep learning technology, and knowledge mapping technology. The question answering method includes: obtaining data to be processed, wherein the data to be processed includes a question and candidate answers; performing general semantic understanding on the data to be processed to obtain a general data feature; selecting a target question answering mode from candidate question answering modes based on the general data feature; and processing the general data feature by using the target question answering mode, to obtain a target answer for the question from the candidate answers.
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Patent Agency Ranking
公开(公告)号：US20230147594A1
公开(公告)日：2023-05-11
申请号：US18150994
申请日：2023-01-06
Inventor： Deguo XIA , Hongfei ZHU , Yaqian SHEN , Jiaqi LIU , Yuting LIU
IPC: G01C21/00
CPC classification number: G01C21/3815
Abstract: The present disclosure provides a method for integratedly updating map data, a device, and a storage medium, relates to the field of artificial intelligence technology such as vehicle-road coordination and intelligent transportation. An embodiment of the method includes: acquiring map update data; generating an updated confidence of map features based on the map update data; and updating uniformly a first-precision map and a second-precision map based on the updated confidence of the map features, where precision of the first-precision map is higher than precision of the second-precision map.
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707.发明公开公开(公告)号：US20230146519A1
公开(公告)日：2023-05-11
申请号：US18148904
申请日：2022-12-30
Inventor： Minlong Peng , Mingming Sun , Ping Li
IPC: G06F40/30
CPC classification number: G06F40/30
Abstract: The present disclosure provides a method for selecting an annotated sample. The method includes: determining a first attribute and a second attribute of a sample characteristic; in which the first attribute is a characteristic attribute of the sample characteristic in a source field sample set, and the second attribute is a characteristic attribute of the sample characteristic in a target field sample set; and determining a target annotated sample from a plurality of candidate annotated samples of the source field sample set according to the first attribute and the second attribute; in which the target annotated sample is configured to train a classification model, the classification model includes a model for determining an emotion polarity by analyzing an input sample to be classified.
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公开(公告)号：US20230145408A1
公开(公告)日：2023-05-11
申请号：US18148177
申请日：2022-12-29
Inventor： Haocheng LIU , Jingyu XU , Cai CHEN , Shuo LI
IPC: G06F16/26
CPC classification number: G06F16/26
Abstract: A method of processing a feature information is provided, which relates to a field of data processing, in particular to fields of artificial intelligence and big data. The method includes: determining at least one candidate division point in a value range of the feature information, and determining an information value corresponding to each candidate division point; determining a target division point based on the information value; dividing the value range based on the target division point, so as to obtain two sub-ranges; determining a sub-range meeting a termination condition in the two sub-ranges as a target interval, determining a sub-range not meeting the termination condition in the two sub-ranges as a new value range, and returning to perform the step of determining at least one candidate division point in a value range until both sub-ranges meet the termination condition, so as to obtain a plurality of target intervals.
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公开(公告)号：US20230140148A1
公开(公告)日：2023-05-04
申请号：US18148775
申请日：2022-12-30
Inventor： Zheng Dong , Peng Wang , Xin Song , Hengshu Zhu , Kaichun Yao
IPC: G06F16/9536
Abstract: A method for community search is performed by an electronic device. The method includes: obtaining graph data to be processed, in which the graph data includes a plurality of nodes and a plurality of connection edges between the nodes; determining a query node from the plurality of nodes based on the graph data, and determining a target community to which the query node belongs by performing a community search for the query node, in which the target community includes the query node, and at least one node other than the query node in the plurality of nodes; and determining the query node and performing the community search for the query node repeatedly until the community to which each node included in the graph data belongs is determined.
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公开(公告)号：US20230137502A1
公开(公告)日：2023-05-04
申请号：US18091704
申请日：2022-12-30
Inventor： Yingyu JI , Yanlong ZHANG , Jingjing SUN
Abstract: A method for processing a feature image includes: grouping parameters in a parameter matrix to obtain a plurality of arrays; the parameter matrix being a matrix converted and obtained from a convolutional layer in a convolutional neural network; performing thinning processing on the parameter matrix according to parameter values in the plurality of arrays to obtain a thinned parameter matrix; performing calculation by using the thinned parameter matrix and a data matrix to determine an output feature map corresponding to the convolutional layer in the case where a sparsity of the thinned parameter matrix satisfies a predetermined condition; the data matrix including a matrix converted and obtained from an input feature map inputted into the convolutional layer.
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