{"id":26481,"date":"2021-05-24T23:02:55","date_gmt":"2021-05-24T15:02:55","guid":{"rendered":"https:\/\/swarma.org\/?p=26481"},"modified":"2021-05-24T23:02:55","modified_gmt":"2021-05-24T15:02:55","slug":"%e5%89%8d%e6%b2%bf%e7%bb%bc%e8%bf%b0%ef%bc%9a%e8%81%94%e9%82%a6%e5%ad%a6%e4%b9%a0%e5%9c%a8%e5%8c%bb%e7%96%97%e4%b8%ad%e7%9a%84%e5%ba%94%e7%94%a8","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=26481","title":{"rendered":"\u524d\u6cbf\u7efc\u8ff0\uff1a\u8054\u90a6\u5b66\u4e60\u5728\u533b\u7597\u4e2d\u7684\u5e94\u7528"},"content":{"rendered":"
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<\/strong>\u8054\u90a6\u5b66\u4e60\uff08Federated learning\uff09\u53ef\u901a\u8fc7\u4e2d\u592e\u670d\u52a1\u5668\uff0c\u5728\u4fdd\u8bc1\u6570\u636e\u9690\u79c1\u6027\u7684\u524d\u63d0\u4e0b\uff0c\u4f7f\u7528\u5206\u6563\u5728\u5404\u5730\u7684\u6570\u636e\uff0c\u8bad\u7ec3\u673a\u5668\u5b66\u4e60\/\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3002\u4ece\u800c\u5728\u9075\u5b88\u9690\u79c1\u4fdd\u62a4\u6cd5\u5f8b\u7684\u524d\u63d0\u4e0b\uff0c\u901a\u8fc7\u534f\u4f5c\u5efa\u6a21\uff0c\u63d0\u5347\u673a\u5668\u5b66\u4e60\u7684\u6548\u7387\u3002\u5176\u5728\u667a\u80fd\u96f6\u552e\u3001\u91d1\u878d\u3001\u81ea\u52a8\u9a7e\u9a76\u7b49\u9886\u57df\u5df2\u6709\u5e7f\u6cdb\u5e94\u7528\u3002\u6700\u8fd1\u4e00\u7bc7\u7efc\u8ff0\u6587\u7ae0\u6982\u8ff0\u4e86\u8054\u90a6\u5b66\u4e60\u7684\u57fa\u672c\u6982\u5ff5\u53ca\u5176\u5728\u751f\u7269\u533b\u5b66\u9886\u57df\u7684\u5e94\u7528\u573a\u666f\uff0c\u672c\u6587\u662f\u5bf9\u8be5\u7efc\u8ff0\u7684\u7b80\u4ecb\u3002<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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Federated Learning for Healthcare Informatics<\/span><\/p>\n

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https:\/\/link.springer.com\/article\/10.1007\/s41666-020-00082-4<\/span><\/p>\n<\/section>\n<\/section>\n<\/blockquote>\n


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       <\/span>\u56fe1. \u8054\u90a6\u5b66\u4e60\u7684\u56db\u4e2a\u6b65\u9aa4\u4e28\u56fe\u7247\u6765\u6e90\uff1a\u7ef4\u57fa\u767e\u79d1<\/span><\/section>\n

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\u9488\u5bf9\u5e94\u5bf9\u7edf\u8ba1\u4e0a\u7684\u6311\u6218\uff0c\u4f20\u7edf\u7684 FedAvg \u7b97\u6cd5\uff0c\u5728\u6570\u636e\u5206\u5e03\u6781\u7aef\u65f6\u662f\u65e0\u6548\u7684\uff0c\u5728\u5c0f\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u91c7\u7528 agnostic federated learning [1]\u2014\u2014\u5373\u5148\u62ff\u5230\u5206\u5e03\u7684\u5ba2\u6237\u7aef\u6570\u636e\u7684\u6570\u636e\u5206\u5e03\uff0c\u518d\u9488\u5bf9\u4efb\u610f\u53ef\u80fd\u5206\u5e03\u7684\u6570\u636e\u4f18\u5316\u6a21\u578b\u53c2\u6570<\/strong>\u3002\u53e6\u4e00\u79cd\u7b97\u6cd5\u662f q-Fair Federated Learning [2]\uff0c\u8be5\u65b9\u6cd5\u5bf9\u4e8e\u8868\u73b0\u8f83\u5dee\u7684\u5ba2\u6237\u7aef\u8bad\u7ec3\u7684\u6a21\u578b\u53c2\u6570\u7ed9\u4e88\u66f4\u9ad8\u7684\u6743\u91cd\uff0c\u4ece\u800c\u964d\u4f4e\u7f51\u7edc\u4e2d\u540c\u65f6\u8bad\u7ec3\u6a21\u578b\u7684\u53c2\u6570\u65b9\u5dee\uff0c\u4ece\u800c\u5e94\u5bf9\u6570\u636e\u5206\u5e03\u7684\u5f02\u8d28\u6027\u3002<\/strong><\/span><\/section>\n


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\u9664\u4e86\u5177\u4f53\u7684\u7b97\u6cd5\uff0c\u8ba9\u5404\u4e2a\u5ba2\u6237\u7aef\u968f\u673a\u62bd\u53d6\u4e00\u90e8\u5206\u6570\u636e\u5171\u4eab\uff0c\u4e5f\u662f\u89e3\u51b3\u7edf\u8ba1\u6311\u6218\u7684\u4e00\u4e2a\u5e38\u7528\u65b9\u6cd5<\/span><\/strong>\u3002\u800c\u591a\u4efb\u52a1\u5b66\u4e60\u901a\u8fc7\u5c06\u5f85\u4f18\u5316\u7684\u53c2\u6570\u5206\u4e3a\u591a\u4e2a\u9636\u6bb5\uff0c\u6839\u636e\u8bad\u7ec3\u6570\u636e\u9884\u6d4b\u672a\u66fe\u89c1\u8fc7\u7684\u6570\u636e\u96c6\uff0c\u53ef\u4ee5\u8ba9\u5404\u4e2a\u5ba2\u6237\u7aef\u5229\u7528\u5df2\u63d0\u53d6\u7684\u6a21\u5f0f\uff0c\u6765\u5e2e\u52a9\u4e3a\u5176\u5b83\u5ba2\u6237\u7aef\u5b66\u4e60\u5f97\u5230\u66f4\u4e3a\u51c6\u786e\u7684\u5206\u7c7b\u5668\uff0c\u5e76\u6355\u6349\u4e0d\u540c\u5ba2\u6237\u7aef\u6570\u636e\u96c6\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u4e5f\u9002\u5408\u89e3\u51b3\u8054\u90a6\u5b66\u4e60\u9762\u5bf9\u7684\u7edf\u8ba1\u4e0a\u7684\u6311\u6218\u3002<\/span><\/section>\n


<\/p>\n

\u800c\u4e3a\u4e86\u51cf\u5c11\u5ba2\u6237\u7aef\u4e0e\u4e2d\u592e\u8282\u70b9\u95f4\u901a\u8baf\u7684\u4fe1\u606f\u91cf\uff0c\u6709\u4e09\u79cd\u65b9\u6cd5\uff0c\u4e00\u662f\u51cf\u5c11\u5ba2\u6237\u7aef\u7684\u6570\u76ee\uff0c\u4e8c\u662f\u51cf\u5c11\u6bcf\u6b21\u66f4\u65b0\u901a\u8baf\u7684\u6bd4\u7279\u6570\uff0c\u4e09\u662f\u51cf\u5c11\u8bad\u7ec3\u8fc7\u7a0b\u6240\u9700\u7684\u66f4\u65b0\u6570\u3002\u4e3a\u6b64\uff0c\u5bf9\u5e94\u7684\u56db\u79cd\u65b9\u6cd5\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/span><\/section>\n
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\u56fe3. <\/span>\u56db\u79cd\u5e94\u5bf9\u8054\u90a6\u5b66\u4e60\u901a\u8baf\u4e0a\u6311\u6218\u7684\u65b9\u6cd5\uff1a<\/span>\u5206\u522b\u662f\u6a21\u578b\u538b\u7f29\u3001\u5ba2\u6237\u7aef\u7b5b\u9009\u3001\u51cf\u5c11\u66f4\u65b0\u9891\u6b21\u3001P2P\u5b66<\/span>\u4e60\uff08\u4e0d\u5f15\u5165\u4e2d\u5fc3\u8282\u70b9\uff09<\/span>
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<\/p>\n

\u800c\u4e3a\u4e86\u907f\u514d\u6076\u610f\u7684\u5ba2\u6237\u7aef\u4ece\u6a21\u578b\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u5b66\u4e60\u63a8\u6d4b\u51fa\u5176\u4ed6\u5ba2\u6237\u7aef\u7684\u6570\u636e\u3001\u4fdd\u62a4\u6a21\u578b\u6784\u5efa\u8005\u53ca\u6570\u636e\u63d0\u4f9b\u65b9\u7684\u9690\u79c1\uff0c\u6709\u4e24\u79cd\u5e38\u7528\u7684\u7406\u8bba\u6846\u67b6\uff0c\u4e00\u662f\u5dee\u5206\u9690\u79c1<\/span>\uff08Differential Privacy\uff09<\/span>\uff1a\u8be5\u65b9\u6cd5\u901a\u8fc7\u5bf9\u6570\u636e\u589e\u52a0\u566a\u97f3\uff0c\u540c\u65f6\u4fdd\u8bc1\u6dfb\u52a0\u566a\u97f3\u540e\u7684\u6570\u636e\u548c\u6e90\u6570\u636e\u80fd\u5f97\u51fa\u65e0\u5dee\u522b\u7684\u6a21\u578b\u66f4\u65b0\uff0c\u4ece\u800c\u63d0\u5347\u8ba1\u7b97\u7684\u9690\u79c1\u6027\uff1b\u53e6\u4e00\u79cd\u65b9\u6cd5\u662f\u53ef\u4fe1\u591a\u6765\u6e90\u8ba1\u7b97<\/span>\uff08Secure Multi-party Computation\uff09<\/span>\uff0c\u901a\u8fc7\u5c06\u6a21\u578b\u8bad\u7ec3\u7684\u6240\u9700\u6570\u636e\u5206\u4e3aN\u4efd\uff0c\u518d\u5c06\u4e0d\u540c\u5ba2\u6237\u7aef\u7684\u6570\u636e\u6c47\u603b\uff0c\u4ece\u800c\u4fdd\u8bc1\u6ca1\u6709\u4efb\u4f55\u8ba1\u7b97\u8282\u70b9\u80fd\u591f\u5f97\u5230\u5b8c\u6574\u7684\u8bad\u7ec3\u6570\u636e\u96c6\u3002<\/span><\/section>\n
       <\/span>\u56fe4. \u53ef\u4fe1\u591a\u6765\u6e90\u8ba1\u7b97\u548c\u5dee\u5206\u9690\u79c1\u793a\u610f\u56fe<\/span><\/span><\/section>\n


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4. \u8054\u90a6\u5b66\u4e60\u5728\u533b\u5b66\u754c\u7684\u5e94\u7528\u6848\u4f8b<\/strong><\/strong><\/p>\n<\/section>\n

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<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u57fa\u4e8e\u7535\u5b50\u75c5\u4f8b\u6570\u636e\uff0c\u8054\u90a6\u5b66\u4e60\u5728\u533b\u7597\u9886\u57df\u7684\u5e94\u7528\u53ef\u4ee5\u5206\u4e3a:<\/span><\/section>\n


<\/p>\n

1\uff09\u7535\u5b50\u75c5\u4f8b\u76f8\u4f3c\u6027\u641c\u7d22\uff1a\u4f8b\u5982[4]\u4e2d\u63d0\u51fa\u7684\u8de8\u673a\u6784\u7684\u75c5\u4eba\u76f8\u4f3c\u6027\u5b66\u4e60\u3002\u4ed6\u4eec\u7684\u6a21\u578b\u53ef\u4ee5\u5728\u4e0d\u5171\u4eab\u4e8e\u60a3\u8005\u76f8\u5173\u7684\u4e2a\u4eba\u4fe1\u606f\u7684\u60c5\u51b5\u4e0b\uff0c\u5728\u591a\u5bb6\u533b\u9662\u95f4\u5bfb\u627e\u7684\u76f8\u4f3c\u75c7\u72b6\u7684\u60a3\u8005\u3002<\/span><\/p>\n


<\/p>\n

2\uff09\u75c5\u4eba\u8868\u5f81\u5b66\u4e60\uff1a[5] \u63cf\u8ff0\u4e86\u4ece\u6587\u6863\u683c\u5f0f\u7684\u75c5\u4f8b\u4e2d\u8fdb\u884c\u7279\u5f81\u63d0\u53d6\uff0c\u5728\u4e0d\u9700\u8981\u83b7\u53d6\u5404\u4e2a\u533b\u7597\u673a\u6784\u7684\u75c5\u4f8b\u6570\u636e\u65f6\uff0c\u80fd\u591f\u4ece\u7535\u5b50\u75c5\u4f8b\u4e2d\u63d0\u53d6\u51fa\u8d85\u91cd\u8fd9\u4e00\u5f71\u54cd\u5065\u5eb7\u7684\u56e0\u7d20\u3002<\/span><\/p>\n


<\/span><\/p>\n

3\uff09SplitNN[6]\uff1a\u4e00\u4e2a\u80fd\u591f\u5728\u4e0d\u5171\u4eab\u654f\u611f\u7684\u539f\u59cb\u6570\u636e\u6216\u6a21\u578b\u7ec6\u8282\u7684\u524d\u63d0\u4e0b\uff0c\u4fc3\u8fdb\u533b\u7597\u673a\u6784\u534f\u4f5c\u8bad\u7ec3\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u6846\u67b6\u3002<\/span><\/p>\n


<\/p>\n

4\uff09\u793e\u533a\u7279\u5f02\u6027\u6a21\u578b\uff1a\u9488\u5bf9\u4e0d\u540c\u6765\u6e90\u7684\u6570\u636e\u6709\u7740\u4e0d\u540c\u7684\u5206\u5e03\u8fd9\u4e00\u95ee\u9898\uff0c[7]\u5c06\u75c5\u4eba\u805a\u96c6\u5230\u591a\u4e2a\u6709\u4e34\u5e8a\u610f\u4e49\u7684\u793e\u533a\u4e2d\uff0c\u6355\u83b7\u76f8\u4f3c\u7684\u8bca\u65ad\u548c\u5730\u7406\u4f4d\u7f6e\u95f4\u7684\u5173\u7cfb\uff0c\u540c\u65f6\u4e3a\u6bcf\u4e2a\u793e\u533a\u57f9\u8bad\u4e00\u4e2a\u6a21\u578b\u3002<\/span><\/p>\n


<\/span><\/p>\n

\u533b\u7597\u9886\u57df\u66f4\u591a\u7684\u5e94\u7528\u5728\u4e8e\u57fa\u4e8e\u7535\u5b50\u75c5\u4f8b\uff0c\u9884\u6d4b\u5065\u5eb7\u98ce\u9669\uff0c\u4ece\u800c\u4e3a\u4e34\u5e8a\u533b\u751f\u63d0\u4f9b\u66f4\u591a\u5173\u4e8e\u65e9\u671f\u6cbb\u7597\u60a3\u8005\u7684\u98ce\u9669\u7684\u8bc4\u4f30\uff1a\u4f8b\u5982\u60a3\u8005\u662f\u5426\u4f1a\u4ea7\u751f\u6297\u836f\u6027\u3001\u836f\u7269\u526f\u53cd\u5e94\u9884\u6d4b\u3001\u5b55\u5987\u662f\u5426\u4f1a\u65e9\u4ea7\u3001\u4f4f\u9662\u75c5\u4eba\u662f\u5426\u4f1a\u6b7b\u4ea1\u7b49\u3002\u8fd9\u7c7b\u5e94\u7528\u573a\u666f\u4e2d\uff0c\u7528\u5230\u7684\u6a21\u578b\u65e2\u5305\u62ec\u4f20\u7edf\u7684\u652f\u6301\u5411\u91cf\u673a\u548c\u4e3b\u6210\u5206\u5206\u6790\uff0c\u4e5f\u5305\u542b\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u591a\u5c42\u611f\u77e5\u673a\u548c\u53d8\u5206\u81ea\u7f16\u7801\u5668\u3002<\/strong><\/span><\/section>\n


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5. \u603b\u7ed3\uff1a<\/strong><\/strong><\/p>\n

\u8054\u90a6\u5b66\u4e60\u5728\u533b\u7597\u9886\u57df\u5e94\u7528\u9700\u89e3\u51b3\u7684\u56f0\u96be<\/strong><\/strong><\/p>\n<\/section>\n

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<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u8be5\u6587\u5728\u4ecb\u7ecd\u4e86\u8054\u90a6\u5b66\u4e60\u7684\u57fa\u7840\u6982\u5ff5\u540e\uff0c\u6307\u51fa\u4e86\u5176\u5728\u4e00\u822c\u60c5\u51b5\u4e0b\u9762\u5bf9\u7684\u4e09\u79cd\u6311\u6218\u53ca\u5e38\u7528\u7684\u89e3\u51b3\u4e4b\u6cd5\u3002\u4e4b\u540e\u9488\u5bf9\u533b\u7597\u9886\u57df\uff0c\u7ed9\u51fa\u6765\u5df2\u6709\u7684\u6210\u719f\u5e94\u7528\u573a\u666f\u3002\u7136\u800c\uff0c\u5728\u533b\u7597\u4fdd\u5065\u9886\u57df\u5e94\u7528\u8054\u90a6\u5b66\u4e60\u65f6\u53ef\u80fd\u9047\u5230\u4e0b\u9762\u4e94\u4e2a\u5f00\u653e\u6027\u7684\u95ee\u9898\u4e9f\u5f85\u89e3\u51b3\u3002<\/span><\/section>\n


<\/p>\n

1\uff09\u6570\u636e\u8d28\u91cf\u3002\u8054\u90a6\u5b66\u4e60\u6709\u53ef\u80fd\u5c06\u6240\u6709\u5b64\u7acb\u7684\u533b\u7597\u673a\u6784\u53ca\u68c0\u6d4b\u8bbe\u5907\u8fde\u63a5\u8d77\u6765\uff0c\u4f7f\u5b83\u4eec\u5206\u4eab\u6709\u9690\u79c1\u4fdd\u969c\u7684\u6570\u636e\u3002\u7136\u800c\uff0c\u5927\u591a\u6570\u536b\u751f\u7cfb\u7edf\u4e2d\uff0c\u6570\u636e\u7ba1\u7406\u6df7\u4e71\uff0c\u7f3a\u5c11\u6570\u636e\u8d28\u63a7\u73af\u8282\u3002\u4ece\u591a\u4e2a\u6765\u6e90\u6536\u96c6\u7684\u6570\u636e\u8d28\u91cf\u53c2\u5dee\u4e0d\u9f50\uff0c\u6ca1\u6709\u7edf\u4e00\u7684\u6570\u636e\u6807\u51c6\u3002\u800c\u4f7f\u7528\u5305\u542b\u5927\u91cf\u9519\u8bef\u6807\u7b7e\u7684\u6570\u636e\uff0c\u4f1a\u4f7f\u9884\u6d4b\u6a21\u578b\u6beb\u65e0\u4ef7\u503c\u3002\u6709\u7b56\u7565\u6027\u5730\u5229\u7528\u533b\u7597\u6570\u636e\u56e0\u6b64\u53d8\u5f97\u81f3\u5173\u91cd\u8981\u3002\u56e0\u6b64\uff0c\u5982\u4f55\u5bf9\u4e0d\u540c\u6765\u6e90\u7684\u6570\u636e\u8fdb\u884c\u6e05\u7406\u3001\u4fee\u6b63\u548c\u8865\u5168\uff0c\u4ece\u800c\u4fdd\u8bc1\u6570\u636e\u8d28\u91cf\u662f\u6539\u8fdb\u8054\u90a6\u673a\u5668\u5b66\u4e60\u5728\u533b\u7597\u4e2d\u5e94\u7528\u6f5c\u529b\u7684\u5173\u952e\u3002<\/span><\/section>\n

<\/span><\/section>\n
2\uff09\u7ed3\u5408\u4e13\u5bb6\u77e5\u8bc6\u30022016\u5e74\uff0cIBM \u63a8\u51fa\u4e86\u6c83\u68ee\uff0c\u8fd9\u662f\u4e00\u4e2a\u4f7f\u7528\u81ea\u7136\u8bed\u8a00\u5904\u7406\u7cfb\u7edf\u6765\u6c47\u603b\u75c5\u4eba\u7535\u5b50\u5065\u5eb7\u8bb0\u5f55\uff0c\u5e76\u641c\u7d22\u5176\u80cc\u540e\u7684\u6d77\u91cf\u6570\u636e\u5e93\u6765\u4e3a\u533b\u751f\u63d0\u4f9b\u6cbb\u7597\u5efa\u8bae\u7684\u5de5\u5177\u3002\u4e0d\u5e78\u7684\u662f\uff0c\u4e00\u4e9b\u80bf\u7624\u5b66\u5bb6\u8bf4\uff0c\u4ed6\u4eec\u66f4\u76f8\u4fe1\u81ea\u5df1\u7684\u5224\u65ad\uff0c\u800c\u4e0d\u662f\u6c83\u68ee\u544a\u8bc9\u4ed6\u4eec\u9700\u8981\u505a\u4ec0\u4e48\u3002\u56e0\u6b64\uff0c\u8ba9\u533b\u751f\u80fd\u53c2\u4e0e\u5230\u6a21\u578b\u7684\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u4ece\u800c\u5438\u6536\u4e13\u5bb6\u77e5\u8bc6\uff0c\u53d8\u5f97\u6781\u4e3a\u91cd\u8981\u3002<\/strong>\u7531\u4e8e\u8bad\u7ec3\u6570\u636e\u96c6\u4e0d\u4e00\u5b9a\u90fd\u8d28\u91cf\u53ef\u9760\uff0c\u56e0\u6b64\u5f15\u5165\u4e13\u5bb6\u7684\u77e5\u8bc6\uff0c\u5c06\u4f1a\u975e\u5e38\u6709\u5e2e\u52a9\uff0c\u533b\u751f\u80fd\u770b\u5230\u4eba\u5de5\u667a\u80fd\u7684\u8bca\u65ad\u6807\u51c6\u3002\u5982\u679c\u9519\u8bef\uff0c\u533b\u751f\u5c06\u8fdb\u4e00\u6b65\u6307\u5bfc\u4eba\u5de5\u667a\u80fd\uff0c\u4ee5\u63d0\u9ad8\u673a\u5668\u5b66\u4e60\u6a21\u578b\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u7684\u51c6\u786e\u6027\u3002<\/span><\/section>\n


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5\uff09\u6a21\u578b\u7cbe\u5ea6\u3002\u8054\u90a6\u5b66\u4e60\u8bd5\u56fe\u4f7f\u5b64\u7acb\u7684\u533b\u7597\u673a\u6784\u6216\u8bbe\u5907\u5206\u4eab\u4ed6\u4eec\u7684\u6570\u636e\uff0c\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u6027\u80fd\u5c06\u968f\u7740\u5927\u578b\u533b\u5b66\u6570\u636e\u96c6\u7684\u4ea7\u751f\u800c\u663e\u8457\u63d0\u5347\u3002\u7136\u800c\uff0c\u76ee\u524d\u53ef\u884c\u7684\u9884\u6d4b\u4efb\u52a1\u662f\u6709\u9650\u7684\uff0c\u800c\u4e14\u90fd\u76f8\u5bf9\u7b80\u5355\u3002\u533b\u7597\u672c\u8eab\u662f\u4e00\u4e2a\u975e\u5e38\u4e13\u4e1a\u9700\u8981\u6781\u9ad8\u51c6\u786e\u6027\u7684\u9886\u57df<\/strong>\u3002\u867d\u7136\u533b\u9662\u7684\u533b\u7597\u8bbe\u5907\uff0c\u76f8\u6bd4\u53ef\u7a7f\u6234\u8bbe\u5907\u5728\u6d4b\u91cf\u51c6\u786e\u5ea6\u4e0a\u5177\u6709\u65e0\u53ef\u6bd4\u62df\u7684\u4f18\u52bf\u3002\u4f46\u8fdb\u4e00\u6b65\u7684\u5e94\u7528\uff0c\u9700\u8981\u4f7f\u7528\u4e0d\u90a3\u4e48\u7cbe\u51c6\u7684\u6570\u636e\uff0c\u4f8b\u5982doc.ai\uff0c\u6839\u636e\u81ea\u62cd\u7167\u7247\u4e2d\u7684\u8eab\u9ad8\u3001\u4f53\u91cd\u3001\u5e74\u9f84\u3001\u6027\u522b\u548c\u4f53\u91cd\u7b49\u7279\u5f81\uff0c\u5c06\u4e00\u4e2a\u4eba\u7684\u4f53\u68c0\u7ed3\u679c\u7ed3\u5408\u57fa\u4e8e\u8fd9\u7c7b\u81ea\u6211\u6536\u96c6\u7684\u6570\u636e\uff0c\u9884\u6d4b\u4e2a\u4f53\u672a\u6765\u7684\u5065\u5eb7\u72b6\u51b5\uff0c\u5c06\u662f\u53e6\u4e00\u4e2a\u503c\u5f97\u63a2\u7d22\u7684\u95ee\u9898\u3002<\/span><\/section>\n

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\u53c2\u8003\u6587\u732e\uff1a<\/span><\/strong><\/span><\/section>\n

1. Mohri M, Sivek G, Suresh AT (2019) Agnostic federated learning. In: Chaudhuri K, Salakhutdinov R (eds) Proceedings of the 36th International conference on machine learning, proceedings of machine learning research, vol 97. PMLR, Long Beach, pp 4615\u20134625<\/span><\/p>\n

2. Li T, Sanjabi M, Smith V (2019) Fair resource allocation in federated learning. arXiv:1905.10497<\/span><\/p>\n

3. Obermeyer Z, Powers B, Vogeli C, Mullainathan S (2019) Dissecting racial bias in an algorithm used to manage the health of populations. Science 366(6464):447\u2013453<\/span><\/p>\n

4. Lee J, Sun J, Wang F, Wang S, Jun CH, Jiang X (2018) Privacy-preserving patient similarity learning in a federated environment: development and analysis. JMIR Medical Informatics 6(2):e20<\/span><\/p>\n

5. Liu D, Dligach D, Miller T (2019) Two-stage federated phenotyping and patient representation learning. arXiv:1908.05596<\/span><\/p>\n

6. Gupta O, Raskar R (2018) Distributed learning of deep neural network over multiple agents. J Netw Comput Appl 116:1\u20138<\/span><\/p>\n

7. Huang L, Liu D (2019) Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records. arXiv:1903.09296<\/span><\/p>\n


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