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    PERSONAL ADVISOR FOR MANAGING PRIVATE INFORMATION
    2.
    发明申请
    PERSONAL ADVISOR FOR MANAGING PRIVATE INFORMATION 有权

    公开(公告)号：US20210049020A1

    公开(公告)日：2021-02-18

    申请号：US16543219

    申请日：2019-08-16

    申请人： International Business Machines Corporation

    发明人： Dinesh C. Verma ,  Bong Jun KO ,  Wei-Han Lee ,  Seraphin Bernard Calo

    IPC分类号： G06F9/445 ,  H04L29/06 ,  G06F21/62

    摘要： Regulating a flow of data from an electronic device comprises generating a user profile associated with a user. Further, a resource profile is generated and is associated with one or more resources external to the electronic device. Additionally, a context profile is generated and describes an outcome of one or more previous interactions between the user of the electronic device and one or more resources. Rules are generated based on a comparison the user profile, the context profile and the site profile. Further, data sent from an electronic device is modified based on the set of rules.

    Efficient Bootstrapping of Transmitter Authentication and Use Thereof
    3.
    发明申请
    Efficient Bootstrapping of Transmitter Authentication and Use Thereof 审中-公开

    公开(公告)号：US20200213354A1

    公开(公告)日：2020-07-02

    申请号：US16238134

    申请日：2019-01-02

    申请人： International Business Machines Corporation

    发明人： Supriyo CHAKRABORTY ,  Bodhisatwa SADHU ,  Bong Jun KO ,  Dinesh C. VERMA

    IPC分类号： H04L29/06 ,  G06F9/4401 ,  G06N20/00

    摘要： A GAN includes a first device and a second device. A discriminator model in the first device is trained to discriminate samples from a transmitter in the first device from samples from other transmitters, by collaborating by the first device with the second device to train the discriminator model to discriminate between samples from its transmitter and spoofed samples received from a generator model in the second device and to train the generator model in the second device to produce more accurate spoofed samples received by the first device during the training. The training results in a trained discriminator model, which is distributed to another device for use by the other device to discriminate samples received by the other device in order to perform authentication of the transmitter in the first device. The other device performs authentication of the transmitter of the first device using the distributed model.

    EXECUTING MAP-REDUCE JOBS WITH NAMED DATA
    4.
    发明申请
    EXECUTING MAP-REDUCE JOBS WITH NAMED DATA 审中-公开
    执行地图减少作业与命名数据

    公开(公告)号：US20160092493A1

    公开(公告)日：2016-03-31

    申请号：US14499725

    申请日：2014-09-29

    申请人： International Business Machines Corporation

    发明人： Bong Jun KO ,  Vasileios PAPPAS ,  Robert D. GRANDL

    IPC分类号： G06F17/30

    CPC分类号： G06F16/2471 ,  G06F16/24532

    摘要： Various embodiments execute MapReduce jobs. In one embodiment, at least one MapReduce job is received from one or more user programs. At least one input file associated with the MapReduce job is divided into a plurality of data blocks each including a plurality of key-value pairs. A first unique name is associated with each of the data blocks. Each of a plurality of mapper nodes generates an intermediate dataset for at least one of the plurality of data blocks. A second unique name is associated with the intermediate dataset generated by each of the plurality of mapper nodes. The second unique name is based on at least one of the first unique name, a set of mapping operations performed on the at least one of the plurality of data blocks, and a number associated with a reducer node in a set of reducer nodes assigned to the intermediate dataset.

    摘要翻译： 各种实施例执行MapReduce作业。 在一个实施例中，从一个或多个用户程序接收至少一个MapReduce作业。 与MapReduce作业相关联的至少一个输入文件被分成多个数据块，每个数据块包括多个键值对。 第一个唯一的名称与每个数据块相关联。 多个映射器节点中的每一个生成多个数据块中的至少一个数据块的中间数据集。 第二唯一名称与由多个映射器节点中的每一个生成的中间数据集相关联。 所述第二唯一名称基于所述第一唯一名称，对所述多个数据块中的所述至少一个数据块执行的一组映射操作以及与分配给所述多个数据块的所述一组还原器节点中的reducer节点相关联的数字中的至少一个 中间数据集。

    FEDERATED LEARNING OF CLIENTS
    5.
    发明申请
    FEDERATED LEARNING OF CLIENTS 有权

    公开(公告)号：US20210158099A1

    公开(公告)日：2021-05-27

    申请号：US16695268

    申请日：2019-11-26

    申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

    发明人： Tiffany Tuor ,  Shiqiang Wang ,  Changchang Liu ,  Bong Jun KO ,  Wei-Han Lee

    IPC分类号： G06K9/62 ,  G06N3/04 ,  G06Q10/10

    摘要： A method, a computer program product, and a computer system determine when to perform a federated learning process. The method includes identifying currently available contributors among contributors of a federated learning task for which the federated learning process is to be performed. The method includes determining a usefulness metric of the currently available contributors for respective datasets from each of the currently available contributors used in performing the federated learning process. The method includes, as a result of the usefulness metric of the currently available contributors being at least a usefulness threshold, generating a recommendation to perform the federated learning process with the datasets of the currently available contributors. The method includes transmitting the recommendation to a processing component configured to perform the federated learning process.

    LOCALIZING FAULTS IN WIRELESS COMMUNICATION NETWORKS
    6.
    发明申请
    LOCALIZING FAULTS IN WIRELESS COMMUNICATION NETWORKS 有权
    在无线通信网络中定位故障

    公开(公告)号：US20150280973A1

    公开(公告)日：2015-10-01

    申请号：US14230044

    申请日：2014-03-31

    申请人： International Business Machines Corporation

    发明人： Bong Jun KO ,  Lee KANG-WON ,  Ramya RAGHAVENDRA ,  Murtaza ZAFER

    IPC分类号： H04L12/24 ,  H04L12/26

    CPC分类号： H04L41/0677 ,  H04L1/12 ,  H04L41/142 ,  H04L43/0847 ,  H04M3/36 ,  H04W24/08

    摘要： Various embodiments manage service issues within a wireless communication network. In one embodiment, a one or more call detail records associated with a set of wireless communication devices of a wireless communication network is received. A set of information within each of the one or more call detail records is compared to a baseline statistical model. The baseline statistical model identifies a normal operating state of the wireless communication network. At least one outlier call detail record in the one or more call detail records is identified based on the comparison. The at least one outlier call detail record indicates that at least one wireless communication device associated with the at least one outlier call detail record experienced one or more service issues.

    摘要翻译： 各种实施例管理无线通信网络内的服务问题。 在一个实施例中，接收与无线通信网络的一组无线通信设备相关联的一个或多个呼叫详细记录。 每个一个或多个呼叫详细记录中的一组信息与基线统计模型进行比较。 基线统计模型识别无线通信网络的正常运行状态。 基于比较来识别一个或多个呼叫详细记录中的至少一个异常值呼叫详细记录。 所述至少一个异常值呼叫详细记录指示与所述至少一个离群通话详细记录相关联的至少一个无线通信设备经历一个或多个服务问题。

    DISTRIBUTED MACHINE LEARNING AT EDGE NODES
    8.
    发明申请
    DISTRIBUTED MACHINE LEARNING AT EDGE NODES 审中-公开

    公开(公告)号：US20190318268A1

    公开(公告)日：2019-10-17

    申请号：US15952625

    申请日：2018-04-13

    申请人： International Business Machines Corporation

    发明人： Shiqiang Wang ,  Tiffany Tuor ,  Theodoros Salonidis ,  Christian Makaya ,  Bong Jun KO

    IPC分类号： G06N99/00 ,  H04L29/08

    摘要： A training process of a machine learning model is executed at the edge node for a number of iterations to generate a model parameter based at least in part on a local dataset and a global model parameter. A resource parameter set indicative of resources available at the edge node is estimated. The model parameter and the resource parameter set are sent to a synchronization node. Updates to the global model parameter and the number of iterations are received from the synchronization node based at least in part on the model parameter and the resource parameter set of edge nodes. The training process of the machine learning model is repeated at the edge node to determine an update to the model parameter based at least in part on the local dataset and updates to the global model parameter and the number of iterations from the synchronization node.