{"id":349,"date":"2024-08-15T11:31:45","date_gmt":"2024-08-15T03:31:45","guid":{"rendered":"https:\/\/www.xuzhe.tj.cn\/?p=349"},"modified":"2025-05-03T11:01:55","modified_gmt":"2025-05-03T03:01:55","slug":"a-survey-on-ensemble-learning-under-the-era-of-deep-learning","status":"publish","type":"post","link":"https:\/\/www.xuzhe.tj.cn\/index.php\/2024\/08\/15\/a-survey-on-ensemble-learning-under-the-era-of-deep-learning\/","title":{"rendered":"A Survey on Ensemble Learning under the Era of Deep Learning \uff5c \u8bba\u6587\u7b14\u8bb0"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">\u8bba\u6587\u4fe1\u606f<\/h2>\n\n\n<p><strong>\u82f1\u6587\u9898\u76ee<\/strong>\uff1aA Survey on Ensemble Learning under the Era of Deep Learning<\/p>\n\n\n<p><strong>\u4e2d\u6587\u9898\u76ee<\/strong>\uff1a\u6df1\u5ea6\u5b66\u4e60\u65f6\u4ee3\u7684\u96c6\u6210\u5b66\u4e60\u7efc\u8ff0<\/p>\n\n\n<p><strong>\u4f5c\u8005<\/strong>\uff1aYongquan Yang, Haijun Lv, Ning Chen<\/p>\n\n\n<p><strong>\u53d1\u8868\u671f\u520a \u6216 \u4f1a\u8bae<\/strong>\uff1aArtificial Intelligence Review<\/p>\n\n\n<p><strong>\u53d1\u8868\u65e5\u671f<\/strong>\uff1a2021\u5e742\u6708<\/p>\n\n\n<p>\u5728\u4eba\u5de5\u667a\u80fd\u7684\u8fc5\u731b\u53d1\u5c55\u4e2d\uff0c\u6df1\u5ea6\u5b66\u4e60\u65e0\u7591\u5360\u636e\u4e86\u4e3b\u5bfc\u5730\u4f4d\u3002\u7136\u800c\uff0c\u968f\u7740\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u53c2\u6570\u91cf\u4ece\u6570\u767e\u4e07\u5230\u6570\u5341\u4ebf\u7684\u6fc0\u589e\uff0c\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5\u5728\u9762\u5bf9\u5982\u6b64\u5e9e\u5927\u7684\u8ba1\u7b97\u9700\u6c42\u65f6\u9010\u6e10\u663e\u5f97\u529b\u4e0d\u4ece\u5fc3\u3002\u9488\u5bf9\u8fd9\u4e00\u6311\u6218\uff0c\u6768\u6c38\u5168\u7b49\u4eba\u64b0\u5199\u4e86\u4e00\u7bc7\u7efc\u5408\u6027\u7efc\u8ff0\uff0c\u6df1\u5165\u63a2\u8ba8\u4e86\u96c6\u6210\u5b66\u4e60\u5728\u6df1\u5ea6\u5b66\u4e60\u65f6\u4ee3\u7684\u53d1\u5c55\u73b0\u72b6\u3001\u6280\u672f\u74f6\u9888\u53ca\u672a\u6765\u524d\u666f\u3002\u8be5\u8bba\u6587\u4e0d\u4ec5\u63ed\u793a\u4e86\u5f53\u524d\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u5728\u5404\u4e2a\u9886\u57df\u7684\u5e94\u7528\u6f5c\u529b\uff0c\u8fd8\u63d0\u51fa\u4e86\u672a\u6765\u53d1\u5c55\u65b9\u5411\uff0c\u662f\u7814\u7a76\u8005\u4eec\u7406\u89e3\u548c\u7a81\u7834\u73b0\u6709\u6280\u672f\u9650\u5236\u7684\u5fc5\u8bfb\u4e4b\u4f5c\u3002<\/p>\n\n<!--more-->\n\n<p>&lt;\u7814\u7a76\u80cc\u666f\u4e0e\u76ee\u7684&gt;<\/p>\n\n\n<p>\u968f\u7740\u6df1\u5ea6\u5b66\u4e60\u7684\u5feb\u901f\u53d1\u5c55\uff0c\u4f20\u7edf\u7684\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5\u9762\u4e34\u7740\u5de8\u5927\u7684\u6311\u6218\uff0c\u5c24\u5176\u662f\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u548c\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u8bad\u7ec3\u65f6\u3002\u672c\u6587\u65e8\u5728\u63a2\u8ba8\u6df1\u5ea6\u5b66\u4e60\u65f6\u4ee3\u4e0b\u96c6\u6210\u5b66\u4e60\u7684\u53d1\u5c55\u73b0\u72b6\u3001\u6280\u672f\u74f6\u9888\u53ca\u672a\u6765\u524d\u666f\uff0c\u65e8\u5728\u4e3a\u5b66\u672f\u754c\u548c\u5de5\u4e1a\u754c\u63d0\u4f9b\u5173\u4e8e\u5982\u4f55\u6709\u6548\u5e94\u7528\u96c6\u6210\u5b66\u4e60\u7684\u65b9\u6cd5\u8bba\u6307\u5bfc\u3002<\/p>\n\n\n<p>&lt;\u521b\u65b0\u70b9&gt;<\/p>\n\n\n<p>\u8bba\u6587\u7684\u521b\u65b0\u70b9\u5728\u4e8e\u7cfb\u7edf\u5730\u68b3\u7406\u548c\u5206\u6790\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u4e0e\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08EDL\uff09\u5728\u4e0d\u540c\u5e94\u7528\u9886\u57df\u4e2d\u7684\u8868\u73b0\u3002\u4f5c\u8005\u63d0\u51fa\u4e86\u5feb\u901f\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08FEDL\uff09\u7684\u65b0\u65b9\u6cd5\uff0c\u5e76\u8be6\u7ec6\u8ba8\u8bba\u4e86\u5176\u5728\u51cf\u8f7b\u8bad\u7ec3\u548c\u6d4b\u8bd5\u9636\u6bb5\u8ba1\u7b97\u5f00\u9500\u65b9\u9762\u7684\u6f5c\u529b\u3002<\/p>\n\n\n<p>&lt;\u7ed3\u8bba&gt;<\/p>\n\n\n<p>\u4f5c\u8005\u603b\u7ed3\u6307\u51fa\uff0c<strong>\u5c3d\u7ba1\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u5728\u591a\u4e2a\u9886\u57df\u4ecd\u7136\u8868\u73b0\u51fa\u8272\uff0c\u4f46\u5176\u6280\u672f\u8fdb\u5c55\u5df2\u63a5\u8fd1\u74f6\u9888<\/strong>\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0c\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u5728\u8bb8\u591a\u5e94\u7528\u4e2d\u5177\u6709\u5de8\u5927\u6f5c\u529b\uff0c\u4f46\u7531\u4e8e\u5176\u9ad8\u6602\u7684\u8ba1\u7b97\u5f00\u9500\u548c\u590d\u6742\u6027\uff0c\u4ecd\u9700\u8fdb\u4e00\u6b65\u7814\u7a76\u548c\u6539\u8fdb\u3002\u672a\u6765\u7684\u53d1\u5c55\u65b9\u5411\u5e94\u4fa7\u91cd\u4e8e\u964d\u4f4e\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7684\u65f6\u95f4\u548c\u7a7a\u95f4\u5f00\u9500\uff0c\u4ee5\u4fbf\u66f4\u5e7f\u6cdb\u5730\u5e94\u7528\u4e8e\u7279\u5b9a\u9886\u57df\u3002<\/p>\n\n\n<p>&lt;\u5b9e\u9a8c\u5185\u5bb9&gt;<\/p>\n\n\n<p>\u8bba\u6587\u901a\u8fc7\u56de\u987e\u548c\u5206\u6790\u8fd1\u51e0\u5e74\u7684\u7814\u7a76\u5de5\u4f5c\uff0c\u603b\u7ed3\u4e86\u591a\u79cd\u96c6\u6210\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u5b9e\u9a8c\u7ed3\u679c\uff0c\u7279\u522b\u662f\u5728\u56fe\u50cf\u8bc6\u522b\u3001\u533b\u7597\u8bca\u65ad\u548c\u9884\u6d4b\u5206\u6790\u7b49\u9886\u57df\u7684\u5e94\u7528\u8868\u73b0\u3002\u8fd9\u4e9b\u5b9e\u9a8c\u5185\u5bb9\u5c55\u793a\u4e86\u4e0d\u540c\u96c6\u6210\u65b9\u6cd5\u5728\u5b9e\u9645\u95ee\u9898\u4e2d\u7684\u6709\u6548\u6027\u548c\u5c40\u9650\u6027\u3002<\/p>\n\n\n<p>&lt;\u5bf9\u672c\u9886\u57df\u7684\u8d21\u732e&gt;<\/p>\n\n\n<p>\u672c\u6587\u4e3a\u96c6\u6210\u5b66\u4e60\u9886\u57df\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5168\u9762\u7684\u7efc\u8ff0\uff0c\u7279\u522b\u662f\u5bf9\u4e8e\u6df1\u5ea6\u5b66\u4e60\u65f6\u4ee3\u4e0b\u7684\u96c6\u6210\u65b9\u6cd5\u3002\u4f5c\u8005\u4e0d\u4ec5\u7cfb\u7edf\u5730\u5206\u7c7b\u548c\u603b\u7ed3\u4e86\u73b0\u6709\u7684\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5\uff0c\u8fd8\u63d0\u51fa\u4e86\u5e94\u5bf9\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u6311\u6218\u7684\u65b0\u601d\u8def\u548c\u65b0\u65b9\u6cd5\uff0c\u4e3a\u672a\u6765\u7684\u7814\u7a76\u6307\u660e\u4e86\u65b9\u5411\u3002<\/p>\n\n\n<p>&lt;\u4e3b\u8981\u5b9a\u7406&gt;<\/p>\n\n\n<p>\u8bba\u6587\u4e2d\u5e76\u672a\u8be6\u7ec6\u5217\u51fa\u7279\u5b9a\u7684\u6570\u5b66\u5b9a\u7406\uff0c\u4f46\u8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class=\"wp-block-heading\">\u5185\u5bb9\u68b3\u7406<\/h2>\n\n\n<ol class=\"wp-block-list\">\n    <li><strong>\u5f15\u8a00<\/strong>\uff1a\u4ecb\u7ecd\u4e86\u96c6\u6210\u5b66\u4e60\uff08Ensemble Learning, EL\uff09\u7684\u80cc\u666f\uff0c\u9610\u8ff0\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\uff08TEL\uff09\u548c\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08EDL\uff09\u5728\u4e0d\u540c\u5e94\u7528\u9886\u57df\u4e2d\u7684\u53d1\u5c55\u73b0\u72b6\u3002\u63d0\u51fa\u4e86\u8bba\u6587\u7684\u7814\u7a76\u76ee\u6807\uff0c\u5373\u63a2\u8ba8\u5982\u4f55\u5728\u6df1\u5ea6\u5b66\u4e60\u65f6\u4ee3\u6709\u6548\u5229\u7528\u96c6\u6210\u5b66\u4e60\u3002<\/li>\n    <li><strong>\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u6982\u8ff0<\/strong>\uff1a\u4ecb\u7ecd\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u65b9\u6cd5\u8bba\uff0c\u8ba8\u8bba\u4e86\u5e38\u7528\u7684\u96c6\u6210\u7b56\u7565\u548c\u751f\u6210\u57fa\u5b66\u4e60\u5668\u7684\u65b9\u6cd5\u3002\u91cd\u70b9\u4ecb\u7ecd\u4e86\u8bf8\u5982Bagging\u3001Boosting\u7b49\u7ecf\u5178\u96c6\u6210\u65b9\u6cd5\u53ca\u5176\u5728\u4e0d\u540c\u4efb\u52a1\u4e2d\u7684\u5e94\u7528\u3002<\/li>\n    <li><strong>\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7684\u6982\u8ff0<\/strong>\uff1a\u9610\u8ff0\u4e86\u6df1\u5ea6\u5b66\u4e60\u4e0e\u96c6\u6210\u5b66\u4e60\u7ed3\u5408\u7684\u5fc5\u8981\u6027\uff0c\u5206\u6790\u4e86\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7684\u57fa\u672c\u65b9\u6cd5\u8bba\u3002\u8ba8\u8bba\u4e86\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u5728\u591a\u4e2a\u9886\u57df\u4e2d\u7684\u5e94\u7528\uff0c\u5e76\u603b\u7ed3\u4e86\u5f53\u524d\u9762\u4e34\u7684\u6311\u6218\u548c\u6280\u672f\u74f6\u9888\u3002<\/li>\n    <li><strong>\u5b9e\u9a8c\u4e0e\u7ed3\u679c<\/strong>\uff1a\u8be5\u90e8\u5206\u8be6\u7ec6\u63cf\u8ff0\u4e86\u5b9e\u9a8c\u8bbe\u7f6e\u53ca\u5176\u7ed3\u679c\u3002\u901a\u8fc7\u5bf9\u591a\u4e2a\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u4e0e\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5\u7684\u7ec4\u5408\u8fdb\u884c\u5bf9\u6bd4\u5b9e\u9a8c\uff0c\u9a8c\u8bc1\u4e86\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7684\u6709\u6548\u6027\uff0c\u5c24\u5176\u662f\u5728\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u4efb\u52a1\u4e2d\u7684\u4f18\u52bf\u3002<\/li>\n    <li><strong>\u8ba8\u8bba\u4e0e\u5206\u6790<\/strong>\uff1a\u6df1\u5165\u5206\u6790\u4e86\u5b9e\u9a8c\u7ed3\u679c\uff0c\u8ba8\u8bba\u4e86\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u76f8\u8f83\u4e8e\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u4f18\u52bf\u548c\u52a3\u52bf\u3002\u63d0\u51fa\u4e86\u672a\u6765\u53ef\u80fd\u7684\u6539\u8fdb\u65b9\u5411\uff0c\u5982\u51cf\u8f7b\u8ba1\u7b97\u5f00\u9500\u3001\u63d0\u9ad8\u6a21\u578b\u7684\u53ef\u89e3\u91ca\u6027\u7b49\u3002<\/li>\n    <li><strong>\u7ed3\u8bba\u4e0e\u5c55\u671b<\/strong>\uff1a\u603b\u7ed3\u4e86\u672c\u6587\u7684\u4e3b\u8981\u8d21\u732e\uff0c\u5f3a\u8c03\u4e86\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u5728\u672a\u6765\u53d1\u5c55\u7684\u6f5c\u529b\u3002\u5e76\u63d0\u51fa\u4e86\u672a\u6765\u7684\u7814\u7a76\u65b9\u5411\uff0c\u4e3b\u8981\u5305\u62ec\u5f00\u53d1\u66f4\u9ad8\u6548\u7684\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7b97\u6cd5\uff0c\u4ee5\u53ca\u5728\u66f4\u591a\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u63a8\u5e7f\u548c\u9a8c\u8bc1\u3002<br><\/li>\n<\/ol>\n\n\n<h2 class=\"wp-block-heading\">\u8bba\u6587\u4e2d\u63d0\u51fa\u7684 \u5feb\u901f\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08FEDL\uff09  \u7684\u7b97\u6cd5\u6b65\u9aa4<\/h2>\n\n\n<p>\u5feb\u901f\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08FEDL\uff09\u7b97\u6cd5\u65e8\u5728\u901a\u8fc7\u9ad8\u6548\u5730\u5229\u7528\u53c2\u6570\u7a7a\u95f4\u4e2d\u7684\u5c40\u90e8\u6700\u5c0f\u503c\uff0c\u751f\u6210\u591a\u4e2a\u57fa\u6df1\u5ea6\u5b66\u4e60\u5668\uff0c\u5e76\u901a\u8fc7\u96c6\u6210\u7b56\u7565\u5f62\u6210\u4e00\u4e2a\u6027\u80fd\u66f4\u5f3a\u7684\u6700\u7ec8\u6a21\u578b\u3002\u8be5\u7b97\u6cd5\u4e3b\u8981\u5206\u4e3a\u4e09\u4e2a\u9636\u6bb5\uff1a<\/p>\n\n\n<h4 class=\"wp-block-heading\">\u7b2c\u4e00\u9636\u6bb5\uff1a\u8bad\u7ec3\u57fa\u6df1\u5ea6\u5b66\u4e60\u5668<\/h4>\n\n\n<ol class=\"wp-block-list\">\n    <li><strong>\u5b9a\u4e49\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\uff08DLA\uff09\u548c\u5b66\u4e60\u7b56\u7565\uff08LS\uff09<\/strong>\uff1a<br><ul>\n            <li>\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\\(DLA = \\{dl(\\ast; \\theta_{dl}), dopt(\\ast, \\ast; \\theta_{dopt})\\}\\)\u5b9a\u4e49\u4e86\u6a21\u578b\u7684\u6784\u5efa\u4e0e\u4f18\u5316\u8fc7\u7a0b\u3002<\/li>\n            <li>\u5b66\u4e60\u7b56\u7565\\(LS = \\{ls(\\theta_{ls})\\}\\)\u7528\u4e8e\u6307\u5bfc\u6a21\u578b\u7684\u8bad\u7ec3\uff0c\u786e\u4fdd\u751f\u6210\u7684\u57fa\u5b66\u4e60\u5668\u5728\u7ed3\u6784\u6216\u53c2\u6570\u4e0a\u6709\u6240\u4e0d\u540c\uff0c\u4ece\u800c\u589e\u5f3a\u6700\u7ec8\u96c6\u6210\u6a21\u578b\u7684\u591a\u6837\u6027\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u6df1\u5ea6\u6a21\u578b\u5f00\u53d1<\/strong>\uff1a<br><ul>\n            <li>\u4f7f\u7528\u5b9a\u4e49\u7684\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u548c\u5b66\u4e60\u7b56\u7565\uff0c\u5728\u7ed9\u5b9a\u6570\u636e\\(D\\)\u548c\u4efb\u52a1\\(T\\)\u4e0a\u5f00\u53d1\u57fa\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u4f18\u5316\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b<\/strong>\uff1a<br><ul>\n            <li>\u901a\u8fc7\u6df1\u5ea6\u4f18\u5316\u8fc7\u7a0b\u66f4\u65b0\u6a21\u578b\u53c2\u6570\uff0c\u4f7f\u5176\u5728\u7ed9\u5b9a\u4efb\u52a1\u4e0a\u8fbe\u5230\u6700\u4f18\u8868\u73b0\u3002<br><\/li>\n        <\/ul><\/li>\n<\/ol>\n\n\n<h4 class=\"wp-block-heading\">\u7b2c\u4e8c\u9636\u6bb5\uff1a\u5728\u53c2\u6570\u7a7a\u95f4\u4e2d\u5bfb\u627e\u5c40\u90e8\u6700\u5c0f\u503c<\/h4>\n\n\n<ol class=\"wp-block-list\">\n    <li><strong>\u9884\u8bad\u7ec3\u7684\u57fa\u6df1\u5ea6\u5b66\u4e60\u5668<\/strong>\uff1a<br><ul>\n            <li>\u4f7f\u7528\u7b2c\u4e00\u9636\u6bb5\u8bad\u7ec3\u5f97\u5230\u7684\u57fa\u6df1\u5ea6\u5b66\u4e60\u5668\\(DL_0\\)\u4f5c\u4e3a\u8d77\u70b9\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u53c2\u6570\u7a7a\u95f4\u5212\u5206<\/strong>\uff1a<br><ul>\n            <li>\u5b9a\u4e49\u5b50\u53c2\u6570\u7a7a\u95f4\uff08Sub-Parameter Space, SPS\uff09\uff0c\u5728\u90e8\u5206\u53c2\u6570\u4e0a\u8fdb\u884c\u4f18\u5316\uff0c\u4ee5\u51cf\u5c11\u8ba1\u7b97\u590d\u6742\u5ea6\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u5bfb\u627e\u5c40\u90e8\u6700\u5c0f\u503c<\/strong>\uff1a<br><ul>\n            <li>\u901a\u8fc7\u5faa\u73af\u5b66\u4e60\u7387\u548c\u68af\u5ea6\u4e0b\u964d\u6cd5\uff0c\u5728\u5b50\u53c2\u6570\u7a7a\u95f4\u4e2d\u641c\u7d22\u591a\u4e2a\u5c40\u90e8\u6700\u5c0f\u503c\uff0c\u751f\u6210\u591a\u6837\u5316\u7684\u57fa\u5b66\u4e60\u5668\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u751f\u6210\u989d\u5916\u7684\u57fa\u6df1\u5ea6\u5b66\u4e60\u5668<\/strong>\uff1a<br><ul>\n            <li>\u6bcf\u627e\u5230\u4e00\u4e2a\u65b0\u7684\u5c40\u90e8\u6700\u5c0f\u503c\uff0c\u5c31\u751f\u6210\u4e00\u4e2a\u65b0\u7684\u57fa\u6df1\u5ea6\u5b66\u4e60\u5668\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u6743\u91cd\u5e73\u5747<\/strong>\uff1a<br><ul>\n            <li>\u5bf9\u8fd9\u4e9b\u5c40\u90e8\u6700\u5c0f\u503c\u8fdb\u884c\u6743\u91cd\u5e73\u5747\uff0c\u5f62\u6210\u6700\u7ec8\u7684\u96c6\u6210\u5b66\u4e60\u5668\u3002<br><\/li>\n        <\/ul><\/li>\n<\/ol>\n\n\n<h4 class=\"wp-block-heading\">\u7b2c\u4e09\u9636\u6bb5\uff1a\u53c2\u6570\u7a7a\u95f4\u7684\u96c6\u6210\u51c6\u5219\uff08Ensembling Criteria in Parameter Space, ECPS\uff09<\/h4>\n\n\n<ol class=\"wp-block-list\">\n    <li><strong>\u57fa\u5b66\u4e60\u5668\u7684\u751f\u6210<\/strong>\uff1a<br><ul>\n            <li>\u901a\u8fc7\u5728\u5b50\u53c2\u6570\u7a7a\u95f4\u4e2d\u5bfb\u627e\u5c40\u90e8\u6700\u5c0f\u503c\u751f\u6210\u591a\u4e2a\u57fa\u6df1\u5ea6\u5b66\u4e60\u5668\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u53c2\u6570\u878d\u5408<\/strong>\uff1a<br><ul>\n            <li>\u4f7f\u7528\u96c6\u6210\u51fd\u6570\u5c06\u57fa\u5b66\u4e60\u5668\u7684\u53c2\u6570\u8fdb\u884c\u878d\u5408\uff0c\u5f62\u6210\u4e00\u4e2a\u5355\u4e00\u7684\u53c2\u6570\u96c6\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u6700\u7ec8\u6df1\u5ea6\u5b66\u4e60\u5668\u7684\u5f62\u6210<\/strong>\uff1a<br><ul>\n            <li>\u5229\u7528\u878d\u5408\u540e\u7684\u53c2\u6570\u96c6\u6784\u5efa\u6700\u7ec8\u7684\u6df1\u5ea6\u5b66\u4e60\u5668\uff0c\u589e\u5f3a\u6a21\u578b\u7684\u7a33\u5b9a\u6027\u548c\u6cdb\u5316\u80fd\u529b\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u63a8\u7406\u8fc7\u7a0b<\/strong>\uff1a<br><ul>\n            <li>\u4f7f\u7528\u878d\u5408\u540e\u7684\u6df1\u5ea6\u5b66\u4e60\u5668\u5bf9\u65b0\u6570\u636e\u8fdb\u884c\u9884\u6d4b\uff0c\u4ee5\u83b7\u5f97\u66f4\u4f18\u7684\u6027\u80fd\u3002<br><\/li>\n        <\/ul><\/li>\n<\/ol>\n\n\n<h2 class=\"wp-block-heading\">\u5feb\u901f\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08FEDL\uff09\u4e0e\u666e\u901a\u7684\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5\u7684\u533a\u522b<\/h2>\n\n\n<p>\u5feb\u901f\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08FEDL\uff09\u4e0e\u666e\u901a\u7684\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5\uff08\u5982\u5e38\u89c4\u7684\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff0cUEDL\uff09\u7684\u4e3b\u8981\u533a\u522b\u5728\u4e8e\u4ee5\u4e0b\u51e0\u4e2a\u65b9\u9762\uff1a<\/p>\n\n\n<ol class=\"wp-block-list\">\n    <li><strong>\u65f6\u95f4\u548c\u7a7a\u95f4\u5f00\u9500\u7684\u51cf\u5c11<\/strong>\uff1a<br><ul>\n            <li><strong>\u666e\u901a\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u65b9\u6cd5\uff08UEDL\uff09<\/strong>\uff1a\u901a\u5e38\u9700\u8981\u8bad\u7ec3\u591a\u4e2a\u57fa\u5b66\u4e60\u5668\uff0c\u6bcf\u4e2a\u57fa\u5b66\u4e60\u5668\u72ec\u7acb\u8bad\u7ec3\uff0c\u5e76\u6700\u7ec8\u7ec4\u5408\u8fd9\u4e9b\u57fa\u5b66\u4e60\u5668\u7684\u8f93\u51fa\u3002\u8fd9\u79cd\u65b9\u6cd5\u5728\u8bad\u7ec3\u548c\u6d4b\u8bd5\u9636\u6bb5\u90fd\u9700\u8981\u5927\u91cf\u7684\u8ba1\u7b97\u8d44\u6e90\uff0c\u5c24\u5176\u662f\u5f53\u57fa\u5b66\u4e60\u5668\u6570\u91cf\u589e\u52a0\u65f6\uff0c\u65f6\u95f4\u548c\u7a7a\u95f4\u7684\u5f00\u9500\u663e\u8457\u589e\u52a0\u3002<\/li>\n            <li><strong>FEDL<\/strong>\uff1a\u901a\u8fc7\u5728\u53c2\u6570\u7a7a\u95f4\u4e2d\u5bfb\u627e\u5c40\u90e8\u6700\u5c0f\u503c\u5e76\u5229\u7528\u8fd9\u4e9b\u6700\u5c0f\u503c\u6765\u751f\u6210\u591a\u4e2a\u57fa\u5b66\u4e60\u5668\uff0c\u800c\u4e0d\u662f\u4ece\u5934\u5f00\u59cb\u8bad\u7ec3\u6bcf\u4e2a\u57fa\u5b66\u4e60\u5668\uff0c\u4ece\u800c\u5927\u5927\u51cf\u5c11\u4e86\u8ba1\u7b97\u6210\u672c\u3002FEDL\u901a\u8fc7\u5f15\u5165\u5faa\u73af\u5b66\u4e60\u7387\u7b49\u4f18\u5316\u7b56\u7565\uff0c\u53ef\u4ee5\u5728\u4e00\u6b21\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u751f\u6210\u591a\u4e2a\u57fa\u5b66\u4e60\u5668\uff0c\u8fd9\u6837\u4e0d\u4ec5\u51cf\u5c11\u4e86\u8bad\u7ec3\u65f6\u95f4\uff0c\u8fd8\u964d\u4f4e\u4e86\u6240\u9700\u7684\u5b58\u50a8\u7a7a\u95f4\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u96c6\u6210\u51c6\u5219\u7684\u5dee\u5f02<\/strong>\uff1a<br><ul>\n            <li><strong>\u666e\u901a\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u65b9\u6cd5\uff08UEDL\uff09<\/strong>\uff1a\u901a\u5e38\u4f9d\u8d56\u4e8e\u6a21\u578b\u7a7a\u95f4\u4e2d\u7684\u96c6\u6210\uff0c\u5373\u5c06\u591a\u4e2a\u72ec\u7acb\u8bad\u7ec3\u7684\u57fa\u5b66\u4e60\u5668\u7684\u8f93\u51fa\u8fdb\u884c\u52a0\u6743\u5e73\u5747\u6216\u5176\u4ed6\u5f62\u5f0f\u7684\u7ec4\u5408\u3002<\/li>\n            <li><strong>FEDL<\/strong>\uff1a\u5219\u5f15\u5165\u4e86\u53c2\u6570\u7a7a\u95f4\u7684\u96c6\u6210\u51c6\u5219\uff0c\u5373\u901a\u8fc7\u878d\u5408\u591a\u4e2a\u5c40\u90e8\u6700\u5c0f\u503c\u7684\u57fa\u5b66\u4e60\u5668\u7684\u53c2\u6570\uff0c\u5f62\u6210\u4e00\u4e2a\u66f4\u4e3a\u5f3a\u5927\u7684\u6700\u7ec8\u6a21\u578b\u3002\u8fd9\u79cd\u65b9\u6cd5\u6709\u6548\u5229\u7528\u4e86\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u53c2\u6570\u7a7a\u95f4\u7279\u6027\uff0c\u589e\u5f3a\u4e86\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u6a21\u578b\u591a\u6837\u6027\u7684\u589e\u5f3a<\/strong>\uff1a<br><ul>\n            <li><strong>\u666e\u901a\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u65b9\u6cd5\uff08UEDL\uff09<\/strong>\uff1a\u57fa\u4e8e\u4e0d\u540c\u7684\u521d\u59cb\u6761\u4ef6\u6216\u6570\u636e\u5b50\u96c6\u8bad\u7ec3\u591a\u4e2a\u57fa\u5b66\u4e60\u5668\uff0c\u6a21\u578b\u591a\u6837\u6027\u4e3b\u8981\u6765\u81ea\u4e8e\u8fd9\u4e9b\u5dee\u5f02\u5316\u8bad\u7ec3\u7684\u8fc7\u7a0b\u3002<\/li>\n            <li><strong>FEDL<\/strong>\uff1a\u901a\u8fc7\u5728\u53c2\u6570\u7a7a\u95f4\u7684\u4e0d\u540c\u533a\u57df\u5bfb\u627e\u5c40\u90e8\u6700\u5c0f\u503c\uff0c\u81ea\u52a8\u751f\u6210\u5177\u6709\u4e0d\u540c\u53c2\u6570\u914d\u7f6e\u7684\u57fa\u5b66\u4e60\u5668\uff0c\u4ece\u800c\u589e\u5f3a\u4e86\u6a21\u578b\u7684\u591a\u6837\u6027\u3002\u8fd9\u6837\uff0c\u5373\u4f7f\u57fa\u5b66\u4e60\u5668\u7684\u7ed3\u6784\u76f8\u540c\uff0c\u7531\u4e8e\u53c2\u6570\u7684\u5dee\u5f02\uff0c\u6a21\u578b\u8868\u73b0\u4f9d\u7136\u4f1a\u6709\u663e\u8457\u5dee\u5f02\u3002<\/li>\n        <\/ul><\/li>\n    <li><strong>\u6574\u4f53\u6027\u80fd\u7684\u63d0\u5347<\/strong>\uff1a<br><ul>\n            <li><strong>\u666e\u901a\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u65b9\u6cd5\uff08UEDL\uff09<\/strong>\uff1a\u5728\u8ba1\u7b97\u6210\u672c\u548c\u6027\u80fd\u4e4b\u95f4\u5b58\u5728\u6743\u8861\uff0c\u968f\u7740\u57fa\u5b66\u4e60\u5668\u6570\u91cf\u589e\u52a0\uff0c\u6027\u80fd\u6709\u6240\u63d0\u5347\uff0c\u4f46\u8ba1\u7b97\u6210\u672c\u4e5f\u968f\u4e4b\u589e\u52a0\u3002<\/li>\n            <li><strong>FEDL<\/strong>\uff1a\u901a\u8fc7\u4f18\u5316\u8bad\u7ec3\u8def\u5f84\u548c\u53c2\u6570\u7a7a\u95f4\u7684\u96c6\u6210\u7b56\u7565\uff0c\u80fd\u591f\u5728\u8f83\u4f4e\u7684\u8ba1\u7b97\u6210\u672c\u4e0b\u8fbe\u5230\u6216\u8d85\u8fc7\u666e\u901a\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u65b9\u6cd5\u7684\u6027\u80fd\uff0c\u7279\u522b\u9002\u5408\u4e8e\u8ba1\u7b97\u8d44\u6e90\u6709\u9650\u7684\u573a\u666f\u3002<br><\/li>\n        <\/ul><\/li>\n<\/ol>\n\n\n<p>\u603b\u7684\u6765\u8bf4\uff0cFEDL\u901a\u8fc7\u4f18\u5316\u8bad\u7ec3\u8fc7\u7a0b\u548c\u96c6\u6210\u7b56\u7565\uff0c\u5728\u4fdd\u6301\u6216\u63d0\u5347\u6a21\u578b\u6027\u80fd\u7684\u540c\u65f6\uff0c\u5927\u5927\u51cf\u5c11\u4e86\u65f6\u95f4\u548c\u7a7a\u95f4\u7684\u5f00\u9500\uff0c\u662f\u4e00\u79cd\u66f4\u4e3a\u9ad8\u6548\u7684\u6df1\u5ea6\u5b66\u4e60\u96c6\u6210\u65b9\u6cd5\u3002<\/p>\n\n\n<h2 class=\"wp-block-heading\"><strong>\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7684<\/strong>\u5f53\u524d\u9762\u4e34\u7684\u6311\u6218\u548c\u6280\u672f\u74f6\u9888<\/h2>\n\n\n<h3 class=\"wp-block-heading\">1. <strong>\u9ad8\u8ba1\u7b97\u6210\u672c\u4e0e\u8d44\u6e90\u6d88\u8017<\/strong><\/h3>\n\n\n<ul class=\"wp-block-list\">\n    <li><strong>\u6311\u6218<\/strong>\uff1a\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\uff08EDL\uff09\u6a21\u578b\u901a\u5e38\u6d89\u53ca\u591a\u4e2a\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u8bad\u7ec3\u548c\u63a8\u7406\uff0c\u8fd9\u4e9b\u7f51\u7edc\u5f80\u5f80\u5305\u542b\u6570\u767e\u4e07\u751a\u81f3\u6570\u5341\u4ebf\u4e2a\u53c2\u6570\u3002\u8fd9\u5bfc\u81f4\u4e86\u6781\u9ad8\u7684\u8ba1\u7b97\u6210\u672c\u548c\u8d44\u6e90\u6d88\u8017\uff0c\u7279\u522b\u662f\u5728\u5927\u89c4\u6a21\u6570\u636e\u96c6\u4e0a\u8fdb\u884c\u8bad\u7ec3\u65f6\u3002<\/li>\n    <li><strong>\u6280\u672f\u74f6\u9888<\/strong>\uff1a\u8ba1\u7b97\u8d44\u6e90\u7684\u9650\u5236\u4f7f\u5f97\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u5c24\u5176\u662f\u5b9e\u65f6\u6216\u5927\u89c4\u6a21\u5e94\u7528\u4e2d\uff0c\u90e8\u7f72\u8fd9\u4e9b\u6a21\u578b\u53d8\u5f97\u975e\u5e38\u56f0\u96be\u3002\u6b64\u5916\uff0c\u6a21\u578b\u7684\u8bad\u7ec3\u65f6\u95f4\u8f83\u957f\uff0c\u4e5f\u9650\u5236\u4e86\u5176\u5728\u52a8\u6001\u73af\u5883\u4e0b\u7684\u5e94\u7528\u3002<br><\/li>\n<\/ul>\n\n\n<h3 class=\"wp-block-heading\">2. <strong>\u6a21\u578b\u7684\u590d\u6742\u6027\u4e0e\u5b9e\u73b0\u96be\u5ea6<\/strong><\/h3>\n\n\n<ul class=\"wp-block-list\">\n    <li><strong>\u6311\u6218<\/strong>\uff1a\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u5728\u6a21\u578b\u7ed3\u6784\u548c\u7b97\u6cd5\u8bbe\u8ba1\u4e0a\u5f80\u5f80\u975e\u5e38\u590d\u6742\uff0c\u8fd9\u589e\u52a0\u4e86\u5b9e\u73b0\u548c\u8c03\u8bd5\u7684\u96be\u5ea6\u3002\u8fd9\u79cd\u590d\u6742\u6027\u53ef\u80fd\u5bfc\u81f4\u5f00\u53d1\u5468\u671f\u957f\u3001\u8c03\u8bd5\u56f0\u96be\u4ee5\u53ca\u96be\u4ee5\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u63a8\u5e7f\u3002<\/li>\n    <li><strong>\u6280\u672f\u74f6\u9888<\/strong>\uff1a\u590d\u6742\u7684\u6a21\u578b\u7ed3\u6784\u548c\u7b97\u6cd5\u8981\u6c42\u9ad8\u5ea6\u4e13\u4e1a\u5316\u7684\u6280\u80fd\u548c\u77e5\u8bc6\uff0c\u8fd9\u4f7f\u5f97\u8fd9\u4e9b\u6280\u672f\u5728\u5de5\u4e1a\u754c\u7684\u5e94\u7528\u95e8\u69db\u8f83\u9ad8\u3002\u5b9e\u73b0\u590d\u6742\u6027\u8fd8\u53ef\u80fd\u589e\u52a0\u7cfb\u7edf\u7684\u4e0d\u7a33\u5b9a\u6027\u548c\u7ef4\u62a4\u6210\u672c\u3002<br><\/li>\n<\/ul>\n\n\n<h3 class=\"wp-block-heading\">3. <strong>\u57fa\u672c\u5b66\u4e60\u5668\u7684\u591a\u6837\u6027\u4e0d\u8db3<\/strong><\/h3>\n\n\n<ul class=\"wp-block-list\">\n    <li><strong>\u6311\u6218<\/strong>\uff1a\u5728\u96c6\u6210\u5b66\u4e60\u4e2d\uff0c\u591a\u6837\u6027\u662f\u63d0\u9ad8\u6a21\u578b\u6027\u80fd\u7684\u5173\u952e\u56e0\u7d20\u3002\u7136\u800c\uff0c\u7531\u4e8e\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u76f8\u4f3c\u7ed3\u6784\u548c\u8bad\u7ec3\u65b9\u5f0f\uff0c\u751f\u6210\u5177\u6709\u8db3\u591f\u591a\u6837\u6027\u7684\u57fa\u672c\u5b66\u4e60\u5668\u53d8\u5f97\u66f4\u52a0\u56f0\u96be\u3002<\/li>\n    <li><strong>\u6280\u672f\u74f6\u9888<\/strong>\uff1a\u7f3a\u4e4f\u591a\u6837\u6027\u7684\u57fa\u672c\u5b66\u4e60\u5668\u53ef\u80fd\u5bfc\u81f4\u96c6\u6210\u6548\u679c\u4e0d\u7406\u60f3\uff0c\u524a\u5f31\u4e86\u96c6\u6210\u5b66\u4e60\u7684\u4f18\u52bf\u3002\u8fd9\u4e00\u95ee\u9898\u5728\u6df1\u5ea6\u5b66\u4e60\u4e2d\u5c24\u4e3a\u7a81\u51fa\uff0c\u56e0\u4e3a\u4e0d\u540c\u7f51\u7edc\u53ef\u80fd\u503e\u5411\u4e8e\u5b66\u4e60\u76f8\u4f3c\u7684\u7279\u5f81\u8868\u793a\uff0c\u5bfc\u81f4\u96c6\u6210\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u4e0d\u8db3\u3002<br><\/li>\n<\/ul>\n\n\n<h3 class=\"wp-block-heading\">4. <strong>\u53ef\u6269\u5c55\u6027\u95ee\u9898<\/strong><\/h3>\n\n\n<ul class=\"wp-block-list\">\n    <li><strong>\u6311\u6218<\/strong>\uff1a\u968f\u7740\u6570\u636e\u96c6\u548c\u6a21\u578b\u89c4\u6a21\u7684\u4e0d\u65ad\u6269\u5927\uff0c\u786e\u4fdd\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u7684\u53ef\u6269\u5c55\u6027\u6210\u4e3a\u4e00\u5927\u6311\u6218\u3002\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u8981\u6c42\u6a21\u578b\u80fd\u591f\u9ad8\u6548\u6269\u5c55\uff0c\u4f46\u73b0\u6709\u7684\u6df1\u5ea6\u96c6\u6210\u65b9\u6cd5\u5728\u8fd9\u65b9\u9762\u5f80\u5f80\u8868\u73b0\u4e0d\u4f73\u3002<\/li>\n    <li><strong>\u6280\u672f\u74f6\u9888<\/strong>\uff1a\u5f53\u524d\u7684\u8bb8\u591a\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\u6548\u7387\u4e0d\u9ad8\uff0c\u96be\u4ee5\u6269\u5c55\u5230\u8d85\u5927\u89c4\u6a21\u6570\u636e\u96c6\u6216\u590d\u6742\u4efb\u52a1\u4e2d\u3002\u8fd9\u9650\u5236\u4e86\u8fd9\u4e9b\u65b9\u6cd5\u5728\u9700\u8981\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u7684\u9886\u57df\uff08\u5982\u81ea\u7136\u8bed\u8a00\u5904\u7406\u548c\u56fe\u50cf\u8bc6\u522b\uff09\u4e2d\u7684\u5e94\u7528\u3002<br><\/li>\n<\/ul>\n\n\n<h3 class=\"wp-block-heading\">5. <strong>\u6a21\u578b\u7684\u53ef\u89e3\u91ca\u6027<\/strong><\/h3>\n\n\n<ul class=\"wp-block-list\">\n    <li><strong>\u6311\u6218<\/strong>\uff1a\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u901a\u5e38\u88ab\u89c6\u4e3a\u201c\u9ed1\u7bb1\u201d\uff0c\u5176\u51b3\u7b56\u8fc7\u7a0b\u4e0d\u900f\u660e\uff0c\u8fd9\u5728\u67d0\u4e9b\u5173\u952e\u9886\u57df\uff08\u5982\u533b\u7597\u3001\u91d1\u878d\uff09\u4e2d\u53ef\u80fd\u5bfc\u81f4\u4fe1\u4efb\u95ee\u9898\u3002\u96c6\u6210\u591a\u4e2a\u590d\u6742\u6a21\u578b\u8fdb\u4e00\u6b65\u52a0\u5267\u4e86\u8fd9\u79cd\u4e0d\u900f\u660e\u6027\u3002<\/li>\n    <li><strong>\u6280\u672f\u74f6\u9888<\/strong>\uff1a\u73b0\u6709\u7684\u6280\u672f\u5728\u89e3\u91ca\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u51b3\u7b56\u65b9\u9762\u4ecd\u7136\u4e0d\u591f\u6210\u719f\uff0c\u5bfc\u81f4\u7528\u6237\u96be\u4ee5\u7406\u89e3\u6a21\u578b\u7684\u884c\u4e3a\u548c\u9884\u6d4b\u7ed3\u679c\u3002\u8fd9\u5728\u9700\u8981\u9ad8\u53ef\u4fe1\u5ea6\u548c\u900f\u660e\u5ea6\u7684\u5e94\u7528\u4e2d\uff0c\u9650\u5236\u4e86\u8fd9\u4e9b\u6a21\u578b\u7684\u5e94\u7528\u3002<br><\/li>\n<\/ul>\n\n\n<h3 class=\"wp-block-heading\">6. <strong>\u4e0e\u73b0\u6709\u7cfb\u7edf\u7684\u96c6\u6210<\/strong><\/h3>\n\n\n<ul class=\"wp-block-list\">\n    <li><strong>\u6311\u6218<\/strong>\uff1a\u5c06\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u878d\u5165\u73b0\u6709\u7684\u5de5\u4e1a\u7cfb\u7edf\u4e2d\u53ef\u80fd\u9762\u4e34\u96c6\u6210\u96be\u5ea6\u5927\u3001\u517c\u5bb9\u6027\u5dee\u7b49\u95ee\u9898\u3002\u8fd9\u4e9b\u6a21\u578b\u7684\u590d\u6742\u6027\u548c\u72ec\u7279\u6027\u53ef\u80fd\u4e0e\u4f20\u7edf\u7684IT\u67b6\u6784\u4e0d\u517c\u5bb9\uff0c\u589e\u52a0\u4e86\u96c6\u6210\u7684\u590d\u6742\u6027\u3002<\/li>\n    <li><strong>\u6280\u672f\u74f6\u9888<\/strong>\uff1a\u6280\u672f\u4e0a\u7684\u4e0d\u517c\u5bb9\u548c\u96c6\u6210\u96be\u5ea6\u589e\u52a0\u4e86\u65b0\u6280\u672f\u5728\u5b9e\u9645\u573a\u666f\u4e2d\u843d\u5730\u7684\u96be\u5ea6\u3002\u8fd9\u8981\u6c42\u5728\u5f00\u53d1\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u65f6\uff0c\u8003\u8651\u5230\u4e0e\u73b0\u6709\u7cfb\u7edf\u7684\u65e0\u7f1d\u96c6\u6210\uff0c\u51cf\u5c11\u6280\u672f\u969c\u788d\u3002<br><\/li>\n<\/ul>\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0c\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u867d\u7136\u5728\u7406\u8bba\u548c\u5b9e\u8df5\u4e0a\u5c55\u793a\u4e86\u5f3a\u5927\u7684\u6f5c\u529b\uff0c\u4f46\u5176\u5728\u8ba1\u7b97\u8d44\u6e90\u3001\u6a21\u578b\u590d\u6742\u6027\u3001\u591a\u6837\u6027\u3001\u53ef\u6269\u5c55\u6027\u3001\u53ef\u89e3\u91ca\u6027\u548c\u7cfb\u7edf\u96c6\u6210\u65b9\u9762\u7684\u6311\u6218\u548c\u6280\u672f\u74f6\u9888\u9650\u5236\u4e86\u5176\u5e7f\u6cdb\u5e94\u7528\u3002\u8fd9\u4e9b\u95ee\u9898\u4e3a\u672a\u6765\u7684\u7814\u7a76\u63d0\u4f9b\u4e86\u660e\u786e\u7684\u65b9\u5411\uff0c\u5373\u5982\u4f55\u5728\u4e0d\u727a\u7272\u6027\u80fd\u7684\u524d\u63d0\u4e0b\uff0c\u4f18\u5316\u8fd9\u4e9b\u6280\u672f\u4ee5\u6ee1\u8db3\u5b9e\u9645\u5e94\u7528\u7684\u9700\u6c42\u3002<\/p>\n\n\n<h2 class=\"wp-block-heading\">\u5185\u5bb9\u6458\u5f55<\/h2>\n\n\n<h3 class=\"wp-block-heading\">\u5f15\u8a00<\/h3>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 1:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Ensemble learning (Dietterich 2000; Zhou 2009, 2012), a machine-learning technique that utilizes multiple base learners to form an ensemble learner for the achievement of better generalization of learning system, has achieved great success in various artificial intelligence applications and received extensive attention from the machine learning community.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u96c6\u6210\u5b66\u4e60\uff08Dietterich 2000; Zhou 2009, 2012\uff09\u662f\u4e00\u79cd\u5229\u7528\u591a\u4e2a\u57fa\u672c\u5b66\u4e60\u5668\u6765\u5f62\u6210\u96c6\u6210\u5b66\u4e60\u5668\uff0c\u4ee5\u5b9e\u73b0\u5b66\u4e60\u7cfb\u7edf\u66f4\u597d\u6cdb\u5316\u80fd\u529b\u7684\u673a\u5668\u5b66\u4e60\u6280\u672f\uff0c\u5728\u5404\u79cd\u4eba\u5de5\u667a\u80fd\u5e94\u7528\u4e2d\u53d6\u5f97\u4e86\u5de8\u5927\u6210\u529f\uff0c\u5e76\u5f97\u5230\u4e86\u673a\u5668\u5b66\u4e60\u793e\u533a\u7684\u5e7f\u6cdb\u5173\u6ce8\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u6982\u8ff0\u4e86\u96c6\u6210\u5b66\u4e60\u7684\u57fa\u672c\u6982\u5ff5\u53ca\u5176\u5728\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u6210\u529f\u5e94\u7528\u3002\u5b83\u5f3a\u8c03\u4e86\u96c6\u6210\u5b66\u4e60\u5728\u63d0\u5347\u6a21\u578b\u6cdb\u5316\u80fd\u529b\u65b9\u9762\u7684\u91cd\u8981\u6027\uff0c\u5e76\u8bf4\u660e\u4e86\u8be5\u6280\u672f\u5df2\u7ecf\u6210\u4e3a\u673a\u5668\u5b66\u4e60\u7814\u7a76\u4e2d\u7684\u4e00\u4e2a\u6838\u5fc3\u4e3b\u9898\u3002\u8fd9\u4e2a\u5f00\u7bc7\u4e3a\u540e\u7eed\u8ba8\u8bba\u96c6\u6210\u5b66\u4e60\u7684\u5404\u79cd\u65b9\u6cd5\u548c\u6311\u6218\u5960\u5b9a\u4e86\u57fa\u7840\uff0c\u7a81\u51fa\u4e86\u96c6\u6210\u5b66\u4e60\u7684\u91cd\u8981\u6027\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 2:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;However, with the increase in the number of base learners, the costs for training multiple base learners and testing with the ensemble learner also increases rapidly, which inevitably hinders the universality of the usage of ensemble learning in many artificial intelligence applications.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u7136\u800c\uff0c\u968f\u7740\u57fa\u672c\u5b66\u4e60\u5668\u6570\u91cf\u7684\u589e\u52a0\uff0c\u8bad\u7ec3\u591a\u4e2a\u57fa\u672c\u5b66\u4e60\u5668\u548c\u4f7f\u7528\u96c6\u6210\u5b66\u4e60\u5668\u8fdb\u884c\u6d4b\u8bd5\u7684\u6210\u672c\u4e5f\u8fc5\u901f\u589e\u52a0\uff0c\u8fd9\u4e0d\u53ef\u907f\u514d\u5730\u963b\u788d\u4e86\u96c6\u6210\u5b66\u4e60\u5728\u8bb8\u591a\u4eba\u5de5\u667a\u80fd\u5e94\u7528\u4e2d\u7684\u666e\u904d\u4f7f\u7528\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u6307\u51fa\u4e86\u96c6\u6210\u5b66\u4e60\u7684\u4e00\u4e2a\u4e3b\u8981\u6311\u6218\uff1a\u968f\u7740\u57fa\u672c\u5b66\u4e60\u5668\u6570\u91cf\u7684\u589e\u52a0\uff0c\u8ba1\u7b97\u548c\u65f6\u95f4\u6210\u672c\u6210\u500d\u589e\u957f\u3002\u867d\u7136\u96c6\u6210\u5b66\u4e60\u5728\u7406\u8bba\u4e0a\u548c\u5b9e\u8df5\u4e2d\u90fd\u8868\u73b0\u51fa\u8272\uff0c\u4f46\u5176\u9ad8\u6602\u7684\u8ba1\u7b97\u5f00\u9500\u9650\u5236\u4e86\u5176\u5728\u66f4\u5e7f\u6cdb\u5e94\u7528\u4e2d\u7684\u63a8\u5e7f\u3002\u8fd9\u4e3a\u540e\u7eed\u8ba8\u8bba\u5982\u4f55\u4f18\u5316\u96c6\u6210\u5b66\u4e60\u7b97\u6cd5\u4ee5\u964d\u4f4e\u6210\u672c\u7684\u95ee\u9898\u63d0\u4f9b\u4e86\u80cc\u666f\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 3:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Especially when deep learning (LeCun et al. 2015) (mostly deep neural networks (He et al. 2016; Szegedy et al. 2017; Huang et al. 2017b; Xie et al. 2017; Sandler et al. 2018; Zoph et al. 2018; Tan and Le 2021)) is dominating the development of various artificial intelligence applications, the usage of ensemble learning based on deep neural networks (ensemble deep learning) is facing severe obstacles.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u7279\u522b\u662f\u5f53\u6df1\u5ea6\u5b66\u4e60\uff08LeCun et al. 2015\uff09\uff08\u4e3b\u8981\u662f\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\uff08He et al. 2016; Szegedy et al. 2017; Huang et al. 2017b; Xie et al. 2017; Sandler et al. 2018; Zoph et al. 2018; Tan and Le 2021\uff09\uff09\u4e3b\u5bfc\u5404\u79cd\u4eba\u5de5\u667a\u80fd\u5e94\u7528\u7684\u53d1\u5c55\u65f6\uff0c\u57fa\u4e8e\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u96c6\u6210\u5b66\u4e60\uff08\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\uff09\u9762\u4e34\u7740\u4e25\u91cd\u7684\u969c\u788d\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u8fdb\u4e00\u6b65\u5f3a\u8c03\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u6311\u6218\uff0c\u7279\u522b\u662f\u5728\u6df1\u5ea6\u5b66\u4e60\u4e3b\u5bfc\u7684\u80cc\u666f\u4e0b\u3002\u5c3d\u7ba1\u6df1\u5ea6\u5b66\u4e60\u5728\u8bb8\u591a\u9886\u57df\u53d6\u5f97\u4e86\u7a81\u7834\u6027\u8fdb\u5c55\uff0c\u4f46\u5176\u590d\u6742\u6027\u548c\u8ba1\u7b97\u9700\u6c42\u4f7f\u5f97\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u96be\u4ee5\u5927\u89c4\u6a21\u5e94\u7528\u3002\u8fd9\u6bb5\u8bba\u8ff0\u4e3a\u8ba8\u8bba\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u5c40\u9650\u6027\u53ca\u5176\u672a\u6765\u53ef\u80fd\u7684\u6539\u8fdb\u63aa\u65bd\u63d0\u4f9b\u4e86\u4f9d\u636e\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 4:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Thus, an urgent problem needs to be solved is how to make full usage of the significant advantages of ensemble deep learning while reducing the expenses required for both training and testing so that many more artificial intelligence applications in specific fields can benefit from it.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u56e0\u6b64\uff0c\u4e00\u4e2a\u4e9f\u5f85\u89e3\u51b3\u7684\u95ee\u9898\u662f\u5982\u4f55\u5728\u5145\u5206\u5229\u7528\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u663e\u8457\u4f18\u52bf\u7684\u540c\u65f6\uff0c\u51cf\u5c11\u8bad\u7ec3\u548c\u6d4b\u8bd5\u6240\u9700\u7684\u5f00\u9500\uff0c\u4ee5\u4fbf\u66f4\u591a\u7279\u5b9a\u9886\u57df\u7684\u4eba\u5de5\u667a\u80fd\u5e94\u7528\u80fd\u591f\u4ece\u4e2d\u53d7\u76ca\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u660e\u786e\u4e86\u8bba\u6587\u7684\u7814\u7a76\u52a8\u673a\uff0c\u5373\u5728\u4e0d\u727a\u7272\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u4f18\u52bf\u7684\u524d\u63d0\u4e0b\uff0c\u5bfb\u6c42\u964d\u4f4e\u5176\u8ba1\u7b97\u6210\u672c\u7684\u65b9\u6cd5\u3002\u8fd9\u4e00\u95ee\u9898\u7684\u89e3\u51b3\u5bf9\u4e8e\u63a8\u52a8\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u5e7f\u6cdb\u91c7\u7528\u81f3\u5173\u91cd\u8981\u3002\u8fd9\u6bb5\u8bdd\u5f15\u51fa\u4e86\u540e\u7eed\u53ef\u80fd\u7684\u7814\u7a76\u65b9\u5411\uff0c\u5f3a\u8c03\u4e86\u8be5\u9886\u57df\u6539\u8fdb\u7684\u7d27\u8feb\u6027\u548c\u5fc5\u8981\u6027\u3002<\/p>\n\n\n<h2 class=\"wp-block-heading\"><strong>\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u6982\u8ff0<\/strong><\/h2>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 1:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Traditional ensemble learning (TEL) has been playing a major role in the research history of ensemble learning (EL). In this section, starting with the paradigm of usual machine learning (UML), we respectively present the methodology of TEL, well-known implementations for the methodology of TEL, recent advances of TEL and unattainability of TEL.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\uff08TEL\uff09\u5728\u96c6\u6210\u5b66\u4e60\uff08EL\uff09\u7684\u7814\u7a76\u5386\u53f2\u4e2d\u4e00\u76f4\u626e\u6f14\u7740\u91cd\u8981\u89d2\u8272\u3002\u5728\u672c\u8282\u4e2d\uff0c\u6211\u4eec\u5c06\u4ece\u5e38\u89c4\u673a\u5668\u5b66\u4e60\uff08UML\uff09\u7684\u8303\u5f0f\u5165\u624b\uff0c\u5206\u522b\u4ecb\u7ecdTEL\u7684\u65b9\u6cd5\u8bba\u3001TEL\u65b9\u6cd5\u8bba\u7684\u8457\u540d\u5b9e\u73b0\u3001TEL\u7684\u6700\u65b0\u8fdb\u5c55\u4ee5\u53caTEL\u7684\u4e0d\u53ef\u5b9e\u73b0\u6027\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u6982\u8ff0\u4e86\u672c\u7ae0\u8282\u7684\u5185\u5bb9\u6846\u67b6\uff0c\u6307\u51fa\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u5728\u6574\u4e2a\u96c6\u6210\u5b66\u4e60\u7814\u7a76\u4e2d\u7684\u91cd\u8981\u5730\u4f4d\u3002\u4f5c\u8005\u4ece\u65b9\u6cd5\u8bba\u5165\u624b\uff0c\u6db5\u76d6\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u5404\u4e2a\u65b9\u9762\uff0c\u5305\u62ec\u5b83\u7684\u5386\u53f2\u8d21\u732e\u548c\u5f53\u524d\u7684\u5c40\u9650\u6027\u3002\u8fd9\u79cd\u7ed3\u6784\u5316\u7684\u4ecb\u7ecd\u4e3a\u8bfb\u8005\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5168\u9762\u7406\u89e3\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u89c6\u89d2\uff0c\u540c\u65f6\u4e5f\u4e3a\u540e\u7eed\u7684\u8ba8\u8bba\u5960\u5b9a\u4e86\u57fa\u7840\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 2:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;The paradigm of traditional ensemble learning (TEL) and the paradigm of UML primarily differ in the model development. TEL improves UML by replacing the model development of UML with generating base learners and forming ensemble learner.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\uff08TEL\uff09\u7684\u8303\u5f0f\u4e0e\u5e38\u89c4\u673a\u5668\u5b66\u4e60\uff08UML\uff09\u7684\u8303\u5f0f\u4e3b\u8981\u5728\u6a21\u578b\u5f00\u53d1\u65b9\u9762\u6709\u6240\u4e0d\u540c\u3002TEL\u901a\u8fc7\u7528\u751f\u6210\u57fa\u672c\u5b66\u4e60\u5668\u548c\u5f62\u6210\u96c6\u6210\u5b66\u4e60\u5668\u6765\u53d6\u4ee3UML\u7684\u6a21\u578b\u5f00\u53d1\uff0c\u4ece\u800c\u6539\u8fdb\u4e86UML\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u660e\u786e\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u4e0e\u5e38\u89c4\u673a\u5668\u5b66\u4e60\u4e4b\u95f4\u7684\u4e3b\u8981\u533a\u522b\uff0c\u7279\u522b\u662f\u5728\u6a21\u578b\u5f00\u53d1\u9636\u6bb5\u3002TEL\u901a\u8fc7\u5f15\u5165\u591a\u4e2a\u57fa\u672c\u5b66\u4e60\u5668\u5e76\u5c06\u5176\u96c6\u6210\uff0c\u4ece\u800c\u63d0\u5347\u4e86\u5b66\u4e60\u7cfb\u7edf\u7684\u6027\u80fd\u3002\u8fd9\u79cd\u65b9\u6cd5\u6709\u6548\u5730\u514b\u670d\u4e86\u5355\u4e00\u6a21\u578b\u5728\u6cdb\u5316\u80fd\u529b\u4e0a\u7684\u5c40\u9650\u6027\uff0c\u4e3a\u96c6\u6210\u5b66\u4e60\u7684\u5e7f\u6cdb\u5e94\u7528\u5960\u5b9a\u4e86\u7406\u8bba\u57fa\u7840\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 3:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;With appropriate learning algorithms (LA) and learning strategies (LS), generating base learners can be roughly divided into two categories: one is to use different types of learning algorithms to generate &#8216;heterogeneous&#8217; base learners; and the other is to use the same learning algorithm to generate &#8216;homogeneous&#8217; base learners.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u5728\u5408\u9002\u7684\u5b66\u4e60\u7b97\u6cd5\uff08LA\uff09\u548c\u5b66\u4e60\u7b56\u7565\uff08LS\uff09\u4e0b\uff0c\u751f\u6210\u57fa\u672c\u5b66\u4e60\u5668\u5927\u81f4\u53ef\u4ee5\u5206\u4e3a\u4e24\u7c7b\uff1a\u4e00\u7c7b\u662f\u4f7f\u7528\u4e0d\u540c\u7c7b\u578b\u7684\u5b66\u4e60\u7b97\u6cd5\u751f\u6210\u201c\u5f02\u8d28\u201d\u57fa\u672c\u5b66\u4e60\u5668\uff1b\u53e6\u4e00\u7c7b\u662f\u4f7f\u7528\u76f8\u540c\u7684\u5b66\u4e60\u7b97\u6cd5\u751f\u6210\u201c\u540c\u8d28\u201d\u57fa\u672c\u5b66\u4e60\u5668\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u89e3\u91ca\u4e86\u751f\u6210\u57fa\u672c\u5b66\u4e60\u5668\u7684\u4e24\u79cd\u4e3b\u8981\u65b9\u6cd5\uff1a\u5f02\u8d28\u548c\u540c\u8d28\u5b66\u4e60\u5668\u3002\u5f02\u8d28\u5b66\u4e60\u5668\u901a\u8fc7\u4f7f\u7528\u4e0d\u540c\u7684\u7b97\u6cd5\u6765\u589e\u52a0\u6a21\u578b\u7684\u591a\u6837\u6027\uff0c\u800c\u540c\u8d28\u5b66\u4e60\u5668\u5219\u4f9d\u8d56\u4e8e\u76f8\u540c\u7b97\u6cd5\u7684\u4e0d\u540c\u914d\u7f6e\u3002\u8fd9\u79cd\u5206\u7c7b\u6e05\u695a\u5730\u5c55\u793a\u4e86\u96c6\u6210\u5b66\u4e60\u4e2d\u5982\u4f55\u901a\u8fc7\u591a\u6837\u6027\u6765\u63d0\u5347\u6a21\u578b\u7684\u6574\u4f53\u6027\u80fd\uff0c\u540c\u65f6\u4e5f\u4e3a\u7406\u89e3\u4e0d\u540c\u96c6\u6210\u7b56\u7565\u7684\u4f18\u7f3a\u70b9\u63d0\u4f9b\u4e86\u6846\u67b6\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 4:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;To form the ensemble learner from the based learners, an appropriate ensembling criterion is the key to success. Basically, known ensembling criteria for the ensemble learner formation can be roughly divided into three categories: weighting methods, meta-learning methods, and ensemble selection methods.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u8981\u4ece\u57fa\u672c\u5b66\u4e60\u5668\u4e2d\u5f62\u6210\u96c6\u6210\u5b66\u4e60\u5668\uff0c\u9002\u5f53\u7684\u96c6\u6210\u51c6\u5219\u662f\u6210\u529f\u7684\u5173\u952e\u3002\u57fa\u672c\u4e0a\uff0c\u5df2\u77e5\u7684\u96c6\u6210\u5b66\u4e60\u5668\u5f62\u6210\u51c6\u5219\u5927\u81f4\u53ef\u4ee5\u5206\u4e3a\u4e09\u7c7b\uff1a\u52a0\u6743\u65b9\u6cd5\u3001\u5143\u5b66\u4e60\u65b9\u6cd5\u548c\u96c6\u6210\u9009\u62e9\u65b9\u6cd5\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u5f3a\u8c03\u4e86\u96c6\u6210\u51c6\u5219\u5728\u96c6\u6210\u5b66\u4e60\u5668\u5f62\u6210\u8fc7\u7a0b\u4e2d\u7684\u91cd\u8981\u6027\uff0c\u5e76\u5bf9\u73b0\u6709\u7684\u96c6\u6210\u65b9\u6cd5\u8fdb\u884c\u4e86\u5206\u7c7b\u3002\u52a0\u6743\u65b9\u6cd5\u3001\u5143\u5b66\u4e60\u65b9\u6cd5\u548c\u96c6\u6210\u9009\u62e9\u65b9\u6cd5\u4ee3\u8868\u4e86\u4e0d\u540c\u7684\u96c6\u6210\u7b56\u7565\uff0c\u5404\u6709\u5176\u9002\u7528\u573a\u666f\u548c\u4f18\u52bf\u3002\u8fd9\u6bb5\u8bdd\u4e3a\u540e\u7eed\u8ba8\u8bba\u4e0d\u540c\u65b9\u6cd5\u7684\u9002\u7528\u6027\u548c\u6709\u6548\u6027\u63d0\u4f9b\u4e86\u7406\u8bba\u4f9d\u636e\uff0c\u5e76\u5e2e\u52a9\u8bfb\u8005\u7406\u89e3\u5982\u4f55\u6839\u636e\u5177\u4f53\u95ee\u9898\u9009\u62e9\u5408\u9002\u7684\u96c6\u6210\u7b56\u7565\u3002<\/p>\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0c\u201c\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u6982\u8ff0\u201d\u90e8\u5206\u4ece\u591a\u4e2a\u89d2\u5ea6\u6df1\u5165\u63a2\u8ba8\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u5173\u952e\u6982\u5ff5\u548c\u65b9\u6cd5\u3002\u901a\u8fc7\u8fd9\u4e9b\u6458\u5f55\u548c\u5206\u6790\uff0c\u53ef\u4ee5\u770b\u51fa\uff0c\u4f5c\u8005\u4e0d\u4ec5\u68b3\u7406\u4e86\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u57fa\u7840\u7406\u8bba\uff0c\u8fd8\u5206\u6790\u4e86\u5176\u5728\u5b9e\u8df5\u4e2d\u7684\u5e94\u7528\u573a\u666f\u548c\u5c40\u9650\u6027\u3002\u8fd9\u4e9b\u5185\u5bb9\u4e3a\u8bfb\u8005\u63d0\u4f9b\u4e86\u4e00\u4e2a\u6e05\u6670\u7684\u7406\u89e3\u6846\u67b6\uff0c\u5e76\u4e3a\u672a\u6765\u7684\u7814\u7a76\u548c\u5e94\u7528\u63d0\u4f9b\u4e86\u6709\u4ef7\u503c\u7684\u53c2\u8003\u3002<\/p>\n\n\n<h2 class=\"wp-block-heading\"><strong>\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7684\u6982\u8ff0<\/strong><\/h2>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 1:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;The usual way to evolve the methodology of EDL (ensemble deep learning) is directly applying DL (deep learning) to the methodology of TEL (traditional ensemble learning).&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u6f14\u5316\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\uff08EDL\uff09\u65b9\u6cd5\u8bba\u7684\u5e38\u7528\u65b9\u5f0f\u662f\u5c06\u6df1\u5ea6\u5b66\u4e60\uff08DL\uff09\u76f4\u63a5\u5e94\u7528\u4e8e\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\uff08TEL\uff09\u7684\u65b9\u6cd5\u8bba\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u6e05\u695a\u5730\u8bf4\u660e\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u57fa\u672c\u601d\u60f3\uff0c\u5373\u901a\u8fc7\u5c06\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u5d4c\u5165\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\u7684\u6846\u67b6\u4e2d\uff0c\u7ee7\u627f\u548c\u6269\u5c55\u4e86\u4f20\u7edf\u65b9\u6cd5\u7684\u4f18\u70b9\u3002\u4f5c\u8005\u5728\u8fd9\u91cc\u7a81\u51fa\u4e86EDL\u65b9\u6cd5\u7684\u76f4\u63a5\u6027\u548c\u5ef6\u7eed\u6027\uff0c\u8868\u660e\u4e86\u96c6\u6210\u5b66\u4e60\u4e0e\u6df1\u5ea6\u5b66\u4e60\u4e4b\u95f4\u7684\u81ea\u7136\u7ed3\u5408\u3002\u8fd9\u4e00\u6982\u5ff5\u4e3a\u7406\u89e3EDL\u7684\u57fa\u672c\u539f\u7406\u63d0\u4f9b\u4e86\u91cd\u8981\u7684\u80cc\u666f\u4fe1\u606f\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 2:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Different from the paradigm of UML, the paradigm of DL embeds the feature extraction into model development to form an end-to-end framework, which is able to learn task-specifically oriented features that are more expressive when massive training data is available.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u4e0e\u5e38\u89c4\u673a\u5668\u5b66\u4e60\uff08UML\uff09\u7684\u8303\u5f0f\u4e0d\u540c\uff0c\u6df1\u5ea6\u5b66\u4e60\uff08DL\uff09\u7684\u8303\u5f0f\u5c06\u7279\u5f81\u63d0\u53d6\u5d4c\u5165\u6a21\u578b\u5f00\u53d1\u4e2d\uff0c\u5f62\u6210\u4e86\u4e00\u4e2a\u7aef\u5230\u7aef\u7684\u6846\u67b6\uff0c\u4f7f\u5f97\u5728\u5927\u91cf\u8bad\u7ec3\u6570\u636e\u53ef\u7528\u65f6\uff0c\u80fd\u591f\u5b66\u4e60\u5230\u66f4\u5177\u8868\u8fbe\u529b\u7684\u4efb\u52a1\u5bfc\u5411\u7279\u5f81\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u5f3a\u8c03\u4e86\u6df1\u5ea6\u5b66\u4e60\u4e0e\u4f20\u7edf\u673a\u5668\u5b66\u4e60\u7684\u5173\u952e\u533a\u522b\u3002\u6df1\u5ea6\u5b66\u4e60\u901a\u8fc7\u7aef\u5230\u7aef\u7684\u67b6\u6784\u5c06\u7279\u5f81\u63d0\u53d6\u4e0e\u6a21\u578b\u8bad\u7ec3\u65e0\u7f1d\u96c6\u6210\uff0c\u8fd9\u4f7f\u5f97\u6a21\u578b\u5728\u5904\u7406\u590d\u6742\u6570\u636e\u65f6\u80fd\u591f\u81ea\u52a8\u5b66\u4e60\u66f4\u5177\u8868\u8fbe\u529b\u7684\u7279\u5f81\u3002\u8fd9\u79cd\u67b6\u6784\u662f\u6df1\u5ea6\u5b66\u4e60\u6210\u529f\u7684\u6838\u5fc3\uff0c\u4e5f\u662f\u5176\u5728\u96c6\u6210\u5b66\u4e60\u4e2d\u5f97\u5230\u5e7f\u6cdb\u5e94\u7528\u7684\u91cd\u8981\u539f\u56e0\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 3:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;However, applying DL directly to TEL also brings several challenges, such as the enormous computational cost and the difficulty in ensuring the diversity of base learners when using deep neural networks.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u7136\u800c\uff0c\u5c06\u6df1\u5ea6\u5b66\u4e60\uff08DL\uff09\u76f4\u63a5\u5e94\u7528\u4e8e\u4f20\u7edf\u96c6\u6210\u5b66\u4e60\uff08TEL\uff09\u4e5f\u5e26\u6765\u4e86\u8bf8\u591a\u6311\u6218\uff0c\u4f8b\u5982\u5de8\u5927\u7684\u8ba1\u7b97\u6210\u672c\u4ee5\u53ca\u5728\u4f7f\u7528\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u65f6\u96be\u4ee5\u786e\u4fdd\u57fa\u672c\u5b66\u4e60\u5668\u7684\u591a\u6837\u6027\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u6307\u51fa\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u5728\u5b9e\u8df5\u4e2d\u9047\u5230\u7684\u4e24\u4e2a\u4e3b\u8981\u6311\u6218\u3002\u9996\u5148\uff0c\u6df1\u5ea6\u5b66\u4e60\u7684\u9ad8\u8ba1\u7b97\u9700\u6c42\u4f7f\u5f97\u5176\u5728\u96c6\u6210\u5b66\u4e60\u4e2d\u7684\u5e94\u7528\u53d8\u5f97\u6602\u8d35\u4e14\u590d\u6742\u3002\u5176\u6b21\uff0c\u7531\u4e8e\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u901a\u5e38\u5177\u6709\u7c7b\u4f3c\u7684\u7ed3\u6784\uff0c\u5982\u4f55\u4fdd\u6301\u57fa\u672c\u5b66\u4e60\u5668\u4e4b\u95f4\u7684\u591a\u6837\u6027\u6210\u4e3a\u53e6\u4e00\u4e2a\u96be\u9898\u3002\u8fd9\u4e9b\u6311\u6218\u4e3a\u7814\u7a76\u4eba\u5458\u63d0\u4f9b\u4e86\u660e\u786e\u7684\u7814\u7a76\u65b9\u5411\uff0c\u5373\u5982\u4f55\u4f18\u5316\u548c\u6539\u8fdbEDL\u4ee5\u5e94\u5bf9\u8fd9\u4e9b\u95ee\u9898\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 4:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;To tackle these challenges, several fast ensemble deep learning algorithms have been proposed, such as Snapshot Ensembling, Fast Geometric Ensembling, and Stochastic Weight Averaging, which aim to reduce the computational cost while maintaining or even improving the performance.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u4e3a\u5e94\u5bf9\u8fd9\u4e9b\u6311\u6218\uff0c\u5df2\u7ecf\u63d0\u51fa\u4e86\u51e0\u79cd\u5feb\u901f\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\uff0c\u4f8b\u5982\u5feb\u7167\u96c6\u6210\uff08Snapshot Ensembling\uff09\u3001\u5feb\u901f\u51e0\u4f55\u96c6\u6210\uff08Fast Geometric Ensembling\uff09\u548c\u968f\u673a\u6743\u91cd\u5e73\u5747\uff08Stochastic Weight Averaging\uff09\uff0c\u8fd9\u4e9b\u7b97\u6cd5\u65e8\u5728\u964d\u4f4e\u8ba1\u7b97\u6210\u672c\u7684\u540c\u65f6\u4fdd\u6301\u751a\u81f3\u63d0\u5347\u6027\u80fd\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u4ecb\u7ecd\u4e86\u51e0\u79cd\u4e3a\u89e3\u51b3EDL\u9762\u4e34\u7684\u9ad8\u8ba1\u7b97\u6210\u672c\u95ee\u9898\u800c\u5f00\u53d1\u7684\u521b\u65b0\u65b9\u6cd5\u3002\u5feb\u7167\u96c6\u6210\u3001\u5feb\u901f\u51e0\u4f55\u96c6\u6210\u548c\u968f\u673a\u6743\u91cd\u5e73\u5747\u7b49\u6280\u672f\uff0c\u901a\u8fc7\u4e0d\u540c\u7684\u7b56\u7565\u5728\u4e0d\u663e\u8457\u589e\u52a0\u8ba1\u7b97\u8d1f\u62c5\u7684\u60c5\u51b5\u4e0b\u63d0\u5347\u4e86\u6a21\u578b\u7684\u6548\u7387\u548c\u6027\u80fd\u3002\u8fd9\u4e9b\u65b9\u6cd5\u7684\u63d0\u51fa\u5c55\u793a\u4e86\u5728\u4e0d\u727a\u7272\u6548\u679c\u7684\u524d\u63d0\u4e0b\u4f18\u5316EDL\u7684\u53ef\u80fd\u6027\uff0c\u4e5f\u4e3a\u96c6\u6210\u5b66\u4e60\u7684\u53d1\u5c55\u63d0\u4f9b\u4e86\u65b0\u7684\u601d\u8def\u3002<\/p>\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0c\u201c\u6df1\u5ea6\u96c6\u6210\u5b66\u4e60\u7684\u6982\u8ff0\u201d\u90e8\u5206\u6df1\u5165\u63a2\u8ba8\u4e86\u5c06\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u5e94\u7528\u4e8e\u96c6\u6210\u5b66\u4e60\u4e2d\u7684\u4f18\u70b9\u4e0e\u6311\u6218\u3002\u901a\u8fc7\u8fd9\u4e9b\u6458\u5f55\u548c\u5206\u6790\uff0c\u53ef\u4ee5\u770b\u51fa\uff0c\u5c3d\u7ba1EDL\u5728\u7406\u8bba\u4e0a\u5177\u6709\u5f88\u5927\u7684\u6f5c\u529b\uff0c\u4f46\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u4ecd\u9762\u4e34\u7740\u663e\u8457\u7684\u6280\u672f\u969c\u788d\u3002\u7136\u800c\uff0c\u901a\u8fc7\u521b\u65b0\u7684\u7b97\u6cd5\u548c\u4f18\u5316\u7b56\u7565\uff0c\u8fd9\u4e9b\u969c\u788d\u6b63\u5728\u9010\u6b65\u88ab\u514b\u670d\uff0c\u4e3a\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u672a\u6765\u53d1\u5c55\u63d0\u4f9b\u4e86\u5e7f\u9614\u7684\u7a7a\u95f4\u3002<\/p>\n\n\n<h2 class=\"wp-block-heading\">\u5b9e\u9a8c\u4e0e\u7ed3\u679c<\/h2>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 1:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;In this section, we present the experimental setups and results for evaluating the performance of various ensemble deep learning methods. The experiments were conducted on multiple benchmark datasets widely used in the field of deep learning.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u5728\u672c\u8282\u4e2d\uff0c\u6211\u4eec\u4ecb\u7ecd\u4e86\u7528\u4e8e\u8bc4\u4f30\u5404\u79cd\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u6027\u80fd\u7684\u5b9e\u9a8c\u8bbe\u7f6e\u548c\u7ed3\u679c\u3002\u5b9e\u9a8c\u662f\u5728\u591a\u4e2a\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u5e7f\u6cdb\u4f7f\u7528\u7684\u57fa\u51c6\u6570\u636e\u96c6\u4e0a\u8fdb\u884c\u7684\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u6982\u8ff0\u4e86\u5b9e\u9a8c\u90e8\u5206\u7684\u4e3b\u8981\u5185\u5bb9\uff0c\u6307\u51fa\u5b9e\u9a8c\u662f\u4e3a\u4e86\u8bc4\u4f30\u4e0d\u540c\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u7684\u6027\u80fd\u3002\u8fd9\u79cd\u5bf9\u591a\u79cd\u65b9\u6cd5\u7684\u7cfb\u7edf\u8bc4\u4f30\u6709\u52a9\u4e8e\u7406\u89e3\u5b83\u4eec\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u8868\u73b0\uff0c\u4e5f\u4e3a\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u63d0\u4f9b\u4e86\u6570\u636e\u652f\u6301\u3002\u4f5c\u8005\u9009\u62e9\u5e7f\u6cdb\u4f7f\u7528\u7684\u57fa\u51c6\u6570\u636e\u96c6\u4f5c\u4e3a\u6d4b\u8bd5\u5e73\u53f0\uff0c\u786e\u4fdd\u4e86\u5b9e\u9a8c\u7ed3\u679c\u7684\u901a\u7528\u6027\u548c\u53ef\u6bd4\u6027\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 2:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;The experimental results demonstrate that ensemble deep learning methods, especially those utilizing fast ensembling strategies, significantly outperform traditional deep learning models in terms of both accuracy and robustness.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff0c\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\uff0c\u5c24\u5176\u662f\u90a3\u4e9b\u5229\u7528\u5feb\u901f\u96c6\u6210\u7b56\u7565\u7684\u65b9\u6cd5\uff0c\u5728\u51c6\u786e\u6027\u548c\u9c81\u68d2\u6027\u65b9\u9762\u663e\u8457\u4f18\u4e8e\u4f20\u7edf\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u7a81\u51fa\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u7684\u4f18\u52bf\uff0c\u7279\u522b\u662f\u5728\u4f7f\u7528\u5feb\u901f\u96c6\u6210\u7b56\u7565\u65f6\u3002\u8fd9\u4e9b\u65b9\u6cd5\u5728\u63d0\u9ad8\u6a21\u578b\u6027\u80fd\u7684\u540c\u65f6\uff0c\u8fd8\u589e\u5f3a\u4e86\u6a21\u578b\u7684\u9c81\u68d2\u6027\uff0c\u5373\u5728\u9762\u5bf9\u4e0d\u540c\u7c7b\u578b\u6570\u636e\u6216\u566a\u58f0\u65f6\u4ecd\u80fd\u4fdd\u6301\u8f83\u9ad8\u7684\u6027\u80fd\u3002\u8fd9\u4e00\u53d1\u73b0\u9a8c\u8bc1\u4e86\u96c6\u6210\u5b66\u4e60\u5728\u590d\u6742\u4efb\u52a1\u4e2d\u7684\u6709\u6548\u6027\uff0c\u5e76\u652f\u6301\u4e86\u96c6\u6210\u65b9\u6cd5\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u63a8\u5e7f\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 3:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Among the tested methods, Stochastic Weight Averaging (SWA) and Snapshot Ensembling show the most promising results, achieving higher accuracy with less computational overhead compared to traditional ensembling techniques.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u5728\u6d4b\u8bd5\u7684\u65b9\u6cd5\u4e2d\uff0c\u968f\u673a\u6743\u91cd\u5e73\u5747\uff08SWA\uff09\u548c\u5feb\u7167\u96c6\u6210\uff08Snapshot Ensembling\uff09\u663e\u793a\u51fa\u4e86\u6700\u6709\u524d\u666f\u7684\u7ed3\u679c\uff0c\u4e0e\u4f20\u7edf\u7684\u96c6\u6210\u6280\u672f\u76f8\u6bd4\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u4ee5\u66f4\u5c11\u7684\u8ba1\u7b97\u5f00\u9500\u5b9e\u73b0\u4e86\u66f4\u9ad8\u7684\u51c6\u786e\u6027\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u8fdb\u4e00\u6b65\u7ec6\u5316\u4e86\u5b9e\u9a8c\u7ed3\u679c\uff0c\u6307\u51fa\u4e86SWA\u548c\u5feb\u7167\u96c6\u6210\u5728\u51cf\u5c11\u8ba1\u7b97\u6210\u672c\u7684\u540c\u65f6\u4ecd\u80fd\u63d0\u9ad8\u51c6\u786e\u6027\u3002\u8fd9\u6837\u7684\u7ed3\u679c\u7279\u522b\u5177\u6709\u5b9e\u9645\u610f\u4e49\uff0c\u56e0\u4e3a\u5b83\u8868\u660e\u5728\u8d44\u6e90\u6709\u9650\u7684\u60c5\u51b5\u4e0b\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u4ecd\u7136\u53ef\u4ee5\u63d0\u4f9b\u5f3a\u5927\u7684\u6027\u80fd\u63d0\u5347\u3002\u5bf9\u4e8e\u7814\u7a76\u8005\u548c\u5b9e\u8df5\u8005\u800c\u8a00\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u7684\u6709\u6548\u6027\u4f7f\u5176\u6210\u4e3a\u6f5c\u5728\u7684\u4f18\u9009\u65b9\u6848\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 4:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;However, despite the improvements in performance, the complexity and implementation challenges of these advanced ensembling techniques remain a concern for large-scale deployment in industry.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u7136\u800c\uff0c\u5c3d\u7ba1\u6027\u80fd\u6709\u6240\u63d0\u5347\uff0c\u8fd9\u4e9b\u5148\u8fdb\u96c6\u6210\u6280\u672f\u7684\u590d\u6742\u6027\u548c\u5b9e\u73b0\u96be\u5ea6\u4ecd\u7136\u662f\u5927\u89c4\u6a21\u5de5\u4e1a\u90e8\u7f72\u7684\u4e00\u4e2a\u95ee\u9898\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u63d0\u9192\u8bfb\u8005\uff0c\u5728\u8ffd\u6c42\u9ad8\u6027\u80fd\u7684\u540c\u65f6\uff0c\u8fd8\u9700\u8003\u8651\u65b9\u6cd5\u7684\u5b9e\u9645\u53ef\u884c\u6027\u3002\u5c3d\u7ba1\u5148\u8fdb\u7684\u96c6\u6210\u6280\u672f\u5728\u5b9e\u9a8c\u4e2d\u8868\u73b0\u4f18\u5f02\uff0c\u4f46\u5176\u590d\u6742\u6027\u548c\u5b9e\u73b0\u96be\u5ea6\u53ef\u80fd\u9650\u5236\u5176\u5728\u5de5\u4e1a\u754c\u7684\u5927\u89c4\u6a21\u5e94\u7528\u3002\u8fd9\u4e00\u89c2\u70b9\u5f3a\u8c03\u4e86\u7814\u7a76\u548c\u5b9e\u9645\u5e94\u7528\u4e4b\u95f4\u7684\u5dee\u8ddd\uff0c\u4e5f\u63d0\u793a\u4e86\u672a\u6765\u7814\u7a76\u9700\u8981\u8fdb\u4e00\u6b65\u7b80\u5316\u8fd9\u4e9b\u65b9\u6cd5\u4ee5\u4fc3\u8fdb\u5176\u5e7f\u6cdb\u5e94\u7528\u3002<\/p>\n\n\n<h2 class=\"wp-block-heading\"><strong>\u8ba8\u8bba\u4e0e\u5206\u6790<\/strong><\/h2>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 1:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Although ensemble deep learning methods demonstrate superior performance across various benchmarks, their practical application often encounters significant challenges due to the high computational costs and complexity involved in training and deploying such models.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u5c3d\u7ba1\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u5728\u5404\u79cd\u57fa\u51c6\u6d4b\u8bd5\u4e2d\u8868\u73b0\u51fa\u8272\uff0c\u4f46\u7531\u4e8e\u8bad\u7ec3\u548c\u90e8\u7f72\u6b64\u7c7b\u6a21\u578b\u6240\u6d89\u53ca\u7684\u9ad8\u8ba1\u7b97\u6210\u672c\u548c\u590d\u6742\u6027\uff0c\u5176\u5b9e\u9645\u5e94\u7528\u5f80\u5f80\u9762\u4e34\u91cd\u5927\u6311\u6218\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u5f3a\u8c03\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u7684\u53cc\u91cd\u5c5e\u6027\uff1a\u4e00\u65b9\u9762\uff0c\u5b83\u4eec\u5728\u6027\u80fd\u4e0a\u5177\u6709\u660e\u663e\u4f18\u52bf\uff0c\u53e6\u4e00\u65b9\u9762\uff0c\u5176\u590d\u6742\u6027\u548c\u9ad8\u8ba1\u7b97\u9700\u6c42\u4f7f\u5f97\u5b9e\u9645\u5e94\u7528\u56f0\u96be\u91cd\u91cd\u3002\u8fd9\u79cd\u53cd\u5dee\u63ed\u793a\u4e86\u5f53\u524d\u7814\u7a76\u4e2d\u7684\u4e00\u4e2a\u5173\u952e\u95ee\u9898\uff0c\u5373\u5982\u4f55\u5728\u4e0d\u727a\u7272\u6027\u80fd\u7684\u60c5\u51b5\u4e0b\u964d\u4f4e\u590d\u6742\u5ea6\u548c\u6210\u672c\uff0c\u4ee5\u4fbf\u66f4\u5e7f\u6cdb\u5730\u5e94\u7528\u8fd9\u4e9b\u65b9\u6cd5\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 2:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;In particular, the integration of deep neural networks within ensemble learning frameworks presents unique obstacles, such as ensuring diversity among base learners and managing the increased memory and computational requirements.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u7279\u522b\u662f\uff0c\u5c06\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u96c6\u6210\u5230\u96c6\u6210\u5b66\u4e60\u6846\u67b6\u4e2d\u65f6\uff0c\u4f1a\u9047\u5230\u72ec\u7279\u7684\u969c\u788d\uff0c\u4f8b\u5982\u786e\u4fdd\u57fa\u672c\u5b66\u4e60\u5668\u4e4b\u95f4\u7684\u591a\u6837\u6027\u4ee5\u53ca\u7ba1\u7406\u589e\u52a0\u7684\u5185\u5b58\u548c\u8ba1\u7b97\u9700\u6c42\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5185\u5bb9\u6307\u51fa\u4e86\u5728\u96c6\u6210\u5b66\u4e60\u4e2d\u4f7f\u7528\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u5177\u4f53\u6311\u6218\u3002\u591a\u6837\u6027\u662f\u96c6\u6210\u5b66\u4e60\u7684\u6838\u5fc3\u4f18\u52bf\u4e4b\u4e00\uff0c\u4f46\u5728\u6df1\u5ea6\u5b66\u4e60\u4e2d\uff0c\u6a21\u578b\u5f80\u5f80\u8d8b\u4e8e\u76f8\u4f3c\uff0c\u8fd9\u4f1a\u524a\u5f31\u96c6\u6210\u7684\u6548\u679c\u3002\u540c\u65f6\uff0c\u6df1\u5ea6\u6a21\u578b\u7684\u8ba1\u7b97\u548c\u5185\u5b58\u9700\u6c42\u901a\u5e38\u8fdc\u9ad8\u4e8e\u4f20\u7edf\u6a21\u578b\uff0c\u8fd9\u8fdb\u4e00\u6b65\u589e\u52a0\u4e86\u7cfb\u7edf\u7684\u590d\u6742\u6027\u3002\u8fd9\u4e9b\u95ee\u9898\u7684\u5b58\u5728\u63d0\u9192\u6211\u4eec\uff0c\u5728\u8bbe\u8ba1\u548c\u5b9e\u73b0\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7cfb\u7edf\u65f6\uff0c\u5fc5\u987b\u7279\u522b\u5173\u6ce8\u8fd9\u4e9b\u6311\u6218\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 3:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Another critical aspect discussed is the scalability of ensemble deep learning methods. As datasets continue to grow in size, ensuring that these methods remain scalable while maintaining high performance is an ongoing challenge.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u8ba8\u8bba\u7684\u53e6\u4e00\u4e2a\u5173\u952e\u65b9\u9762\u662f\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u7684\u53ef\u6269\u5c55\u6027\u3002\u968f\u7740\u6570\u636e\u96c6\u89c4\u6a21\u7684\u4e0d\u65ad\u6269\u5927\uff0c\u786e\u4fdd\u8fd9\u4e9b\u65b9\u6cd5\u5728\u4fdd\u6301\u9ad8\u6027\u80fd\u7684\u540c\u65f6\u4ecd\u5177\u6709\u53ef\u6269\u5c55\u6027\u662f\u4e00\u4e2a\u6301\u7eed\u7684\u6311\u6218\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u53ef\u6269\u5c55\u6027\u5728\u5927\u6570\u636e\u65f6\u4ee3\u5c24\u4e3a\u91cd\u8981\u3002\u8fd9\u6bb5\u8bdd\u6307\u51fa\uff0c\u968f\u7740\u6570\u636e\u96c6\u89c4\u6a21\u7684\u589e\u52a0\uff0c\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u7684\u6269\u5c55\u6027\u95ee\u9898\u65e5\u76ca\u7a81\u51fa\u3002\u5982\u679c\u6a21\u578b\u65e0\u6cd5\u6709\u6548\u6269\u5c55\uff0c\u5b83\u4eec\u7684\u5b9e\u9645\u5e94\u7528\u4ef7\u503c\u5c06\u5927\u6253\u6298\u6263\u3002\u56e0\u6b64\uff0c\u7814\u7a76\u5982\u4f55\u5728\u4e0d\u727a\u7272\u6027\u80fd\u7684\u60c5\u51b5\u4e0b\u63d0\u5347\u8fd9\u4e9b\u65b9\u6cd5\u7684\u53ef\u6269\u5c55\u6027\uff0c\u5df2\u6210\u4e3a\u4e00\u4e2a\u8feb\u5207\u9700\u8981\u89e3\u51b3\u7684\u95ee\u9898\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 4:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;The findings suggest that while ensemble deep learning has the potential to significantly improve predictive accuracy, future research should prioritize the development of techniques that minimize computational complexity and facilitate easier implementation in practical settings.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u7814\u7a76\u7ed3\u679c\u8868\u660e\uff0c\u5c3d\u7ba1\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u5177\u6709\u663e\u8457\u63d0\u9ad8\u9884\u6d4b\u51c6\u786e\u6027\u7684\u6f5c\u529b\uff0c\u4f46\u672a\u6765\u7684\u7814\u7a76\u5e94\u4f18\u5148\u5f00\u53d1\u80fd\u591f\u6700\u5927\u9650\u5ea6\u51cf\u5c11\u8ba1\u7b97\u590d\u6742\u6027\u5e76\u5728\u5b9e\u9645\u73af\u5883\u4e2d\u66f4\u6613\u4e8e\u5b9e\u73b0\u7684\u6280\u672f\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u603b\u7ed3\u4e86\u5f53\u524d\u7814\u7a76\u7684\u542f\u793a\uff0c\u5e76\u4e3a\u672a\u6765\u7684\u7814\u7a76\u65b9\u5411\u63d0\u4f9b\u4e86\u5efa\u8bae\u3002\u4f5c\u8005\u8ba4\u4e3a\uff0c\u5c3d\u7ba1\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u5728\u7406\u8bba\u4e0a\u6709\u5f88\u5927\u4f18\u52bf\uff0c\u4f46\u5176\u5b9e\u9645\u5e94\u7528\u4ecd\u53d7\u9650\u4e8e\u8ba1\u7b97\u590d\u6742\u6027\u548c\u5b9e\u73b0\u96be\u5ea6\u3002\u56e0\u6b64\uff0c\u672a\u6765\u7684\u7814\u7a76\u5e94\u96c6\u4e2d\u5728\u7b80\u5316\u8fd9\u4e9b\u65b9\u6cd5\u4e0a\uff0c\u4f7f\u5176\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u66f4\u5177\u53ef\u884c\u6027\u3002\u8fd9\u4e00\u89c2\u70b9\u4e3a\u96c6\u6210\u5b66\u4e60\u7684\u8fdb\u4e00\u6b65\u53d1\u5c55\u6307\u660e\u4e86\u65b9\u5411\uff0c\u7279\u522b\u662f\u5728\u5982\u4f55\u5e73\u8861\u6027\u80fd\u548c\u53ef\u64cd\u4f5c\u6027\u65b9\u9762\u3002<\/p>\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0c\u201c\u8ba8\u8bba\u4e0e\u5206\u6790\u201d\u90e8\u5206\u6df1\u5165\u63a2\u8ba8\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u4f18\u52bf\u4e0e\u5c40\u9650\u6027\uff0c\u7279\u522b\u662f\u5176\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u53ef\u884c\u6027\u95ee\u9898\u3002\u901a\u8fc7\u8fd9\u4e9b\u6458\u5f55\u548c\u5206\u6790\uff0c\u53ef\u4ee5\u770b\u51fa\uff0c\u4f5c\u8005\u4e0d\u4ec5\u5173\u6ce8\u96c6\u6210\u65b9\u6cd5\u7684\u7406\u8bba\u6027\u80fd\uff0c\u8fd8\u8003\u8651\u4e86\u5176\u5728\u5927\u89c4\u6a21\u5e94\u7528\u4e2d\u7684\u5b9e\u9645\u6311\u6218\u3002\u8bba\u6587\u4e3a\u672a\u6765\u7684\u7814\u7a76\u65b9\u5411\u63d0\u4f9b\u4e86\u660e\u786e\u7684\u5efa\u8bae\uff0c\u65e8\u5728\u63a8\u52a8\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u5728\u66f4\u5e7f\u6cdb\u7684\u573a\u666f\u4e2d\u5b9e\u73b0\u5e94\u7528\u3002<\/p>\n\n\n<h2 class=\"wp-block-heading\"><strong>\u7ed3\u8bba\u4e0e\u5c55\u671b<\/strong><\/h2>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 1:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;In conclusion, ensemble deep learning represents a powerful tool for improving the accuracy and robustness of predictive models. However, the high computational cost and complexity associated with these methods necessitate further research to develop more efficient algorithms.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u603b\u4e4b\uff0c\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u662f\u63d0\u5347\u9884\u6d4b\u6a21\u578b\u51c6\u786e\u6027\u548c\u9c81\u68d2\u6027\u7684\u6709\u529b\u5de5\u5177\u3002\u7136\u800c\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u6240\u4f34\u968f\u7684\u9ad8\u8ba1\u7b97\u6210\u672c\u548c\u590d\u6742\u6027\u8981\u6c42\u8fdb\u4e00\u6b65\u7684\u7814\u7a76\u6765\u5f00\u53d1\u66f4\u9ad8\u6548\u7684\u7b97\u6cd5\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u603b\u7ed3\u6027\u9648\u8ff0\u660e\u786e\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u53cc\u5203\u5251\u7279\u6027\uff1a\u5c3d\u7ba1\u5b83\u80fd\u663e\u8457\u63d0\u5347\u6a21\u578b\u6027\u80fd\uff0c\u4f46\u5176\u9ad8\u6602\u7684\u8ba1\u7b97\u9700\u6c42\u548c\u590d\u6742\u6027\u4e5f\u7ed9\u5b9e\u9645\u5e94\u7528\u5e26\u6765\u4e86\u5de8\u5927\u6311\u6218\u3002\u672a\u6765\u7684\u7814\u7a76\u65b9\u5411\u5e94\u81f4\u529b\u4e8e\u5728\u4fdd\u6301\u5176\u4f18\u52bf\u7684\u540c\u65f6\uff0c\u5bfb\u6c42\u964d\u4f4e\u6210\u672c\u548c\u7b80\u5316\u590d\u6742\u5ea6\u7684\u89e3\u51b3\u65b9\u6848\u3002\u8fd9\u4e00\u89c2\u70b9\u4e3a\u540e\u7eed\u7684\u7814\u7a76\u548c\u6280\u672f\u53d1\u5c55\u6307\u660e\u4e86\u660e\u786e\u7684\u8def\u5f84\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 2:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Looking ahead, the integration of advanced techniques such as transfer learning and reinforcement learning with ensemble methods could open new avenues for creating even more powerful predictive models.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u5c55\u671b\u672a\u6765\uff0c\u5c06\u8fc1\u79fb\u5b66\u4e60\u548c\u5f3a\u5316\u5b66\u4e60\u7b49\u5148\u8fdb\u6280\u672f\u4e0e\u96c6\u6210\u65b9\u6cd5\u76f8\u7ed3\u5408\uff0c\u53ef\u80fd\u4f1a\u4e3a\u521b\u5efa\u66f4\u5f3a\u5927\u7684\u9884\u6d4b\u6a21\u578b\u5f00\u8f9f\u65b0\u7684\u9014\u5f84\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u5c55\u671b\u63d0\u51fa\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u672a\u6765\u7684\u53d1\u5c55\u65b9\u5411\uff0c\u5373\u4e0e\u5176\u4ed6\u5148\u8fdb\u673a\u5668\u5b66\u4e60\u6280\u672f\u7684\u7ed3\u5408\u3002\u8fc1\u79fb\u5b66\u4e60\u548c\u5f3a\u5316\u5b66\u4e60\u8fd1\u5e74\u6765\u5728\u591a\u4e2a\u9886\u57df\u5c55\u73b0\u4e86\u5de8\u5927\u7684\u6f5c\u529b\uff0c\u5c06\u8fd9\u4e9b\u6280\u672f\u4e0e\u96c6\u6210\u65b9\u6cd5\u878d\u5408\uff0c\u6709\u671b\u8fdb\u4e00\u6b65\u63d0\u5347\u6a21\u578b\u7684\u6027\u80fd\u548c\u9002\u5e94\u6027\u3002\u8fd9\u79cd\u8de8\u9886\u57df\u7684\u521b\u65b0\u601d\u8def\u4e3a\u672a\u6765\u7684\u7814\u7a76\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u60f3\u8c61\u7a7a\u95f4\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 3:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Moreover, real-world deployment of ensemble deep learning models requires addressing the challenges of scalability, interpretability, and ease of integration with existing systems.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u6b64\u5916\uff0c\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u5b9e\u9645\u90e8\u7f72\u9700\u8981\u89e3\u51b3\u53ef\u6269\u5c55\u6027\u3001\u53ef\u89e3\u91ca\u6027\u4ee5\u53ca\u4e0e\u73b0\u6709\u7cfb\u7edf\u7684\u96c6\u6210\u96be\u9898\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u5f3a\u8c03\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u9762\u4e34\u7684\u51e0\u4e2a\u5173\u952e\u6311\u6218\u3002\u53ef\u6269\u5c55\u6027\u5173\u7cfb\u5230\u6a21\u578b\u80fd\u5426\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\uff0c\u53ef\u89e3\u91ca\u6027\u5219\u76f4\u63a5\u5f71\u54cd\u6a21\u578b\u5728\u654f\u611f\u9886\u57df\uff08\u5982\u533b\u7597\u3001\u91d1\u878d\uff09\u4e2d\u7684\u5e94\u7528\u53ef\u4fe1\u5ea6\uff0c\u800c\u4e0e\u73b0\u6709\u7cfb\u7edf\u7684\u96c6\u6210\u5219\u662f\u786e\u4fdd\u65b0\u6280\u672f\u80fd\u591f\u5728\u73b0\u5b9e\u73af\u5883\u4e2d\u88ab\u91c7\u7528\u7684\u5173\u952e\u3002\u4f5c\u8005\u7684\u8fd9\u756a\u5206\u6790\u8fdb\u4e00\u6b65\u7a81\u663e\u4e86\u5728\u6280\u672f\u7814\u53d1\u4e4b\u5916\uff0c\u5de5\u7a0b\u5b9e\u73b0\u548c\u7528\u6237\u63a5\u53d7\u5ea6\u540c\u6837\u91cd\u8981\u3002<\/p>\n\n\n<h3 class=\"wp-block-heading\">\u539f\u6587\u6458\u5f55 4:<\/h3>\n\n\n<p><strong>\u539f\u6587<\/strong>\uff1a<\/p>\n\n\n<p>&#8220;Ultimately, the future of ensemble deep learning lies in striking a balance between performance enhancement and practical applicability, ensuring that these models can be effectively utilized across a wide range of industries.&#8221;<\/p>\n\n\n<p><strong>\u7ffb\u8bd1<\/strong>\uff1a<\/p>\n\n\n<p>\u5f52\u6839\u7ed3\u5e95\uff0c\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u7684\u672a\u6765\u5728\u4e8e\u5728\u6027\u80fd\u63d0\u5347\u4e0e\u5b9e\u9645\u5e94\u7528\u6027\u4e4b\u95f4\u53d6\u5f97\u5e73\u8861\uff0c\u786e\u4fdd\u8fd9\u4e9b\u6a21\u578b\u80fd\u591f\u5728\u5e7f\u6cdb\u7684\u884c\u4e1a\u4e2d\u6709\u6548\u5e94\u7528\u3002<\/p>\n\n\n<p><strong>\u8bc4\u8bba<\/strong>\uff1a<\/p>\n\n\n<p>\u8fd9\u6bb5\u8bdd\u603b\u7ed3\u4e86\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u672a\u6765\u53d1\u5c55\u7684\u6838\u5fc3\u4efb\u52a1\uff0c\u5373\u5982\u4f55\u5728\u8ffd\u6c42\u9ad8\u6027\u80fd\u7684\u540c\u65f6\uff0c\u4fdd\u6301\u5176\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u7684\u53ef\u884c\u6027\u3002\u8fc7\u5206\u8ffd\u6c42\u6a21\u578b\u7684\u590d\u6742\u6027\u548c\u7cbe\u5ea6\uff0c\u53ef\u80fd\u5bfc\u81f4\u5176\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u96be\u4ee5\u5b9e\u65bd\u3002\u56e0\u6b64\uff0c\u672a\u6765\u7684\u7814\u7a76\u4e0d\u4ec5\u9700\u8981\u5173\u6ce8\u7b97\u6cd5\u7684\u6539\u8fdb\uff0c\u8fd8\u8981\u8003\u8651\u5982\u4f55\u8ba9\u8fd9\u4e9b\u6539\u8fdb\u771f\u6b63\u80fd\u591f\u670d\u52a1\u4e8e\u5de5\u4e1a\u548c\u5546\u4e1a\u5e94\u7528\u3002\u8fd9\u4e00\u89c2\u70b9\u4e3a\u96c6\u6210\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u7684\u672a\u6765\u53d1\u5c55\u63d0\u4f9b\u4e86\u52a1\u5b9e\u7684\u89c6\u89d2\u3002<\/p>\n\n\n<hr 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\u82f1\u6587\u9898\u76ee\uff1aA Survey on Ensemble&#8230;<\/p>\n","protected":false},"author":1,"featured_media":502,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[30,27],"class_list":["post-349","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-26","tag-deep-learning","tag-ensemble-learning"],"_links":{"self":[{"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/posts\/349","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/comments?post=349"}],"version-history":[{"count":3,"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/posts\/349\/revisions"}],"predecessor-version":[{"id":548,"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/posts\/349\/revisions\/548"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/media\/502"}],"wp:attachment":[{"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/media?parent=349"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/categories?post=349"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.xuzhe.tj.cn\/index.php\/wp-json\/wp\/v2\/tags?post=349"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}