{"id":43795,"date":"2023-07-17T20:44:25","date_gmt":"2023-07-17T12:44:25","guid":{"rendered":"https:\/\/swarma.org\/?p=43795"},"modified":"2023-07-17T20:44:25","modified_gmt":"2023-07-17T12:44:25","slug":"%e6%b7%b1%e5%ba%a6%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c%e7%9a%84%e7%bb%9f%e8%ae%a1%e7%89%a9%e7%90%86%ef%bc%9a%e5%af%bb%e6%89%be%e6%9c%80%e4%bc%98%e5%88%9d%e5%a7%8b%e5%8c%96%e7%90%86%e8%ae%ba","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=43795","title":{"rendered":"\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u7684\u7edf\u8ba1\u7269\u7406\uff1a\u5bfb\u627e\u6700\u4f18\u521d\u59cb\u5316\u7406\u8bba"},"content":{"rendered":"
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Statistical physics of deep neural networks: Initialization toward optimal channels<\/span><\/section>\n
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3.\u795e\u7ecf\u7f51\u7edc\u4e2d\u95f4\u5c42\u7684\u4fe1\u53f7\u5728\u8ba1\u7b97\u76f8\u5173\u7cfb\u6570\u7684\u79ef\u5206\u516c\u5f0f\u4e2d\u53ef\u4ee5\u4f5c\u4e3a\u5b8c\u5168\u72ec\u7acb\u540c\u5206\u5e03\u7684\u6765\u5904\u7406\u3002<\/span><\/section>\n

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\u5728\u4e0a\u8ff0\u5047\u8bbe\u4e0b\uff0c\u901a\u8fc7\u5efa\u7acb\u4fe1\u53f7\u4f20\u64ad\u4e8c\u9636\u77e9\u7684\u8fed\u4ee3\u516c\u5f0f\uff0c\u5e76\u8fdb\u884c\u65b9\u7a0b\u6570\u503c\u5206\u6790\u4ee5\u53ca\u795e\u7ecf\u7f51\u7edc\u8ba1\u7b97\u673a\u5b9e\u9a8c\uff0c\u53ef\u4ee5\u7528\u4e0d\u540c\u4fe1\u53f7\u95f4\u76f8\u5173\u7cfb\u6570\u8d8b\u5411\u4e8e1\u6216\u8d8b\u5411\u4e8e\u5c0f\u91cf\u4e3a\u6807\u51c6\uff0c\u7ed9\u51fa\u65e0\u9650\u5bbd\u795e\u7ecf\u7f51\u7edc\u7cfb\u7efc\u5bf9\u4e8e\u8f93\u5165\u4fe1\u53f7\u8bb0\u5fc6\u7684\u6df7\u4e71\u76f8<\/strong>\u548c\u6709\u5e8f\u76f8<\/strong>\u3002\u4e24\u76f8\u76f8\u53d8\u7684\u4e34\u754c\u7ebf<\/span>\uff08EOC, Edge of chaos\uff09<\/span>\u5373\u662f\u795e\u7ecf\u7f51\u7edc\u8f93\u5165\u8f93\u51fa\u96c5\u5404\u6bd4\u77e9\u9635\u5947\u5f02\u503c\u7684\u6a21\u957f\u5747\u503c\u7b49\u4e8e1\u7684\u7ebf\uff0c\u5728\u6b64\u57fa\u7840\u4e0a\u53ef\u4ee5\u5b9a\u4e49\u52a8\u529b\u7b49\u8ddd\u70b9<\/span>\uff08DI, Dynamic isometry\uff09<\/span>\u2014\u2014\u96c5\u5404\u6bd4\u77e9\u9635\u5947\u5f02\u503c\u7684\u6a21\u957f\u5168\u90e8\u786e\u5b9e\u4e3a1\u7684\u70b9\u3002<\/span><\/section>\n

<\/section>\n
2. \u72ec\u7acb\u540c\u5206\u5e03\u5047\u8bbe\u7684\u56f0\u96be<\/span><\/strong><\/span><\/section>\n

<\/section>\n
\u5728\u8bba\u6587\u4e2d\uff0c\u4f5c\u8005\u7ecf\u8fc7\u7406\u8bba\u5206\u6790\u6307\u51fa\u5728\u8ba1\u7b97\u4e92\u4fe1\u606f\u65f6\uff0c\u4e09\u6761\u72ec\u7acb\u540c\u5206\u5e03\u5047\u8bbe\u4f1a\u4f7f\u6240\u5f97\u7684\u5747\u503c\u8d8b\u5411\u6b63\u65e0\u7a77\uff0c\u5f15\u51fa\u9519\u8bef\u3002\u5177\u4f53\u5730\uff0c\u5728\u72ec\u7acb\u540c\u5206\u5e03\u5047\u8bbe\u4e0b\u8f93\u5165\u4fe1\u53f7\u548c\u7b2cl\u5c42\u4fe1\u53f7\u95f4\u7684\u76f8\u5173\u7cfb\u6570\u7684\u8ba1\u7b97\u7ed3\u679c\u662f<\/span><\/section>\n

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  (3)<\/span><\/p>\n

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 <\/span><\/section>\n
\u7531\u7b2c\u4e00\u6761\u5047\u8bbe\u53ef\u77e5(3)\u4e2d\u52a0\u548c\u9879\u662f\u72ec\u7acb\u540c\u5206\u5e03\u7684\uff0c\u8fdb\u800c\u901a\u8fc7\u4e2d\u5fc3\u6781\u9650\u5b9a\u7406\u4ee5\u53ca\u8fdb\u4e00\u6b65\u7684\u7edf\u8ba1\u8ba1\u7b97\uff0c\u5f97\u5230\u76f8\u5173\u7cfb\u6570<\/sub><\/span>\u5bf9\u7edd\u5bf9\u503c\u5927\u4e8e1\u5177\u6709\u53ef\u6d4b\u7684\u6982\u7387\uff0c\u4f7f\u5f97\u4e92\u4fe1\u606f\u5bf9\u4e8e\u65e0\u7a77\u53d1\u6563\u4e5f\u5177\u6709\u53ef\u6d4b\u7684\u6982\u7387\u3002\u6839\u672c\u7684\u9519\u8bef\u5728\u4e8e\u5bf9\u4e8e\u65e0\u9650\u5bbd\u795e\u7ecf\u7f51\u7edc\uff0c\u7b2c\u4e09\u6761\u72ec\u7acb\u540c\u5206\u5e03\u5047\u8bbe\u8981\u6c42\u8f93\u5165\u4fe1\u53f7\u7684\u72ec\u7acb\u7ef4\u5ea6\u6709\u65e0\u7a77\u4e2a\uff0c\u800c\u65e0\u7a77\u7684\u72ec\u7acb\u7ef4\u5ea6\u81ea\u7136\u5f15\u51fa\u65e0\u7a77\u7684\u4fe1\u606f\u91cf\u3002<\/span><\/section>\n

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 <\/span><\/section>\n

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\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u56db\u3001\u65b0\u7684\u7406\u8bba\u65b9\u6cd5\uff0c<\/span><\/strong><\/strong><\/p>\n

\u4e92\u4fe1\u606f\u6700\u5927\u5316\u4e0e\u52a8\u529b\u7b49\u8ddd\u70b9\u7684\u540c\u4e00<\/span><\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

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

<\/section>\n
1.\u4e92\u4fe1\u606f\u7684\u4e0b\u754c<\/span><\/strong><\/span><\/section>\n

<\/section>\n
\u629b\u5f03\u72ec\u7acb\u540c\u5206\u5e03\u5047\u8bbe\u540e\uff0c\u4e3a\u4e86\u80fd\u4ece\u89e3\u6790\u7684\u89d2\u5ea6\u6709\u6240\u5206\u6790\uff0c\u4f5c\u8005\u63d0\u51fa\u8ba1\u7b97\u8f93\u5165\u8f93\u51fa\u4e92\u4fe1\u606f\u7684\u4e0b\u754c\u3002\u7ecf\u7531\u9ad8\u65af\u4fe1\u606f\u74f6\u9888\u7406\u8bba[12,13]\uff0c\u4f5c\u8005\u5c06\u7814\u7a76\u7684\u5bf9\u8c61\u8f6c\u5411\u5177\u6709\u8054\u5408\u9ad8\u65af\u5206\u5e03\u7684\u8f93\u5165\u4fe1\u53f7\u3002\u6b64\u65f6\u65e0\u8bba\u8f93\u51fa\u4fe1\u53f7\u7684\u5206\u5e03\uff0c\u5747\u53ef\u4ee5\u91c7\u7528\u9ad8\u65af\u4e92\u4fe1\u606f\u4f5c\u4e3a\u771f\u5b9e\u4e92\u4fe1\u606f\u7684\u4e0b\u754c[14]\uff0c\u8ba1\u7b97\u51fa\u7684\u4e0b\u754c\u503c\u662f\uff1a<\/span><\/section>\n

<\/span><\/section>\n

  (4)<\/span><\/p>\n

<\/span>
<\/section>\n
\u5728\u6b64\u516c\u5f0f\u4e2d\uff0c\u5bf9\u4e8e\u65e0\u9650\u5bbd\u795e\u7ecf\u7f51\u7edc\u7cfb\u7efc\u4ec5\u6709<\/span><\/sub><\/span>\uff08<\/span>\u03c3*\u662f<\/span>\u4fe1\u53f7\u4f20\u64ad\u8fc7\u7a0b\u4e2d\u65b9\u5dee\u7684\u6536\u655b\u503c\uff09<\/span>\u80fd\u4ee5\u53ef\u6d4b\u7684\u6982\u7387\u53d8\u5316\uff0c\u5e76\u4e14\uff084\uff09\u5f0f\u5173<\/span>\u4e8e\u03b2\u662f\u5355\u8c03\u9012\u589e\u7684\u3002\u81f3\u6b64\uff0c\u5bf9\u4e8e\u4e92\u4fe1\u606f\u4e0b\u754c\u6700\u5927\u503c\u7684\u5206\u6790\u8f6c\u5316\u4e3a\u5bf9\u79ef\u5206\u9879\u03b2\u6700\u5927\u503c\u7684\u5206\u6790<\/span>\u3002<\/span><\/section>\n

<\/section>\n
2. \u4e92\u4fe1\u606f\u6700\u5927\u5316\u7684\u7406\u8bba\u4e0e\u5b9e\u9a8c\u5206\u6790<\/span><\/strong><\/span><\/section>\n

<\/section>\n
\u8bba\u6587\u4f5c\u8005\u9996\u5148\u901a\u8fc7\u7ed9\u51fa<\/span>\u03c3w<\/sub><\/span><\/span>, \u03c3b<\/sub><\/span><\/span>\u548c \u03c3*<\/span>(\u03c3w<\/sub><\/span><\/span>, \u03c3b<\/sub><\/span><\/span><\/span>) <\/span>\u95f4\u7684\u9690\u5f0f\u65b9\u7a0b\uff0c\u8bc1\u660e\u4e86\u5bf9\u4e8e\u65e0\u9650\u5bbd\u795e\u7ecf\u7f51\u7edc\u7cfb\u7efc\uff0c\u03b2<\/span>\u53d6\u6700\u5927\u503c\u548c\u03c3*\u21920<\/span>\u5177\u6709\u540c\u4e00\u6027\u3002\u518d\u6839\u636e\u6587\u732e [15,16]\uff0c\u4f7f\u7528\u81ea\u7531\u6982\u7387\u8bba<\/span>\uff08free probability theory\uff09<\/span> [17]\u5bf9\u65e0\u9650\u5bbd\u795e\u7ecf\u7f51\u7edc\u7cfb\u7efc\u8f93\u5165\u8f93\u51fa\u96c5\u5404\u6bd4\u77e9\u9635\u7684\u5947\u5f02\u503c\u8fdb\u884c\u8ba1\u7b97\uff0c\u5f97\u5230\u4ee3\u8868\u5947\u5f02\u503c\u6a21\u957f\u5206\u5e03\u5747\u5300\u7684\u52a8\u529b\u7b49\u8ddd\u70b9\u4e0e\u03c3*<\/span>\u2192<\/span>0<\/span>\u4e5f\u662f\u540c\u4e00\u70b9\u3002\u4ece\u800c\u8bc1\u660e\u5728\u4f18\u5316\u7684\u5e73\u5747\u573a\u5047\u8bbe\u4e0b\uff0c\u52a8\u529b\u7b49\u8ddd\u70b9\u4e0e\u03b2<\/span>\u6700\u5927\u503c\u70b9\u7406\u8bba\u4e0a\u5177\u6709\u540c\u4e00\u6027\u3002\u540c\u65f6\u8bba\u6587\u4e2d\u8fd8\u5bf9\u03b2<\/span>\u5c55\u5f00\u6570\u503c\u8ba1\u7b97\uff0c\u7ed3\u679c\u5982\u56fe2(a)\uff0c\u5728\u6570\u503c\u7ed3\u679c\u4e0a\u8bf4\u660e\u4e86\u4e8c\u8005\u7684\u540c\u4e00\u6027\u3002\u81f3\u6b64\uff0c\u52a8\u529b\u7b49\u8ddd\u70b9\u4e0e\u4e92\u4fe1\u606f\u7684\u4e0b\u754c\u88ab\u8bc1\u660e\u662f\u7b49\u540c\u7684\u3002<\/span><\/section>\n
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\u56fe2.\u539f\u8bba\u6587\u4e2d\u7684\u8bc1\u660e\u903b\u8f91\u8be0\u91ca\u56fe\u3002(a)\u03b2<\/span>\u6700\u5927\u503c\u70b9\u548c\u52a8\u529b\u7b49\u8ddd\u70b9\u90fd\u662f\u03c3*\u21920<\/span>\u7684\u70b9\u3002(b)\u03b2<\/span>\u5728\u65e0\u9650\u5bbd\u795e\u7ecf\u7f51\u7edc\u7cfb\u7efc\u76f8\u56fe\u4e0a\u7684\u6027\u8d28\u4ee5\u53ca\u6570\u503c\u8ba1\u7b97\u7ed3\u679c\uff0c\u5176\u4e2d\u5728\u52a8\u529b\u7b49\u8ddd\u70b9\u4e0a\u6700\u5927\u5316\u3002<\/span><\/p>\n


<\/section>\n
\u7136\u800c\uff0c\u4e0a\u8ff0\u8bc1\u660e\u90fd\u9002\u7528\u4e8e\u65e0\u9650\u5bbd\u7684\u795e\u7ecf\u7f51\u7edc\u3002\u4e3a\u4e86\u63a2\u7d22\u771f\u5b9e\u7684\u6709\u9650\u5bbd\u795e\u7ecf\u7f51\u7edc\uff0c\u8bba\u6587\u4f5c\u8005\u90e8\u7f72\u4e86\u5927\u89c4\u6a21\u8ba1\u7b97\u5b9e\u9a8c\uff0c\u5bf9\u4e0d\u540c\u5bbd\u5ea6\u3001\u6df1\u5ea6\u4ee5\u53ca\u6743\u91cd\u548c\u504f\u7f6e\u4e0d\u540c\u65b9\u5dee\u7684\u795e\u7ecf\u7f51\u7edc\u8ba1\u7b97\u4e86\u9ad8\u65af\u4e92\u4fe1\u606f\u3002\u5b9e\u9a8c\u7ed3\u679c\u786e\u8bc1\u4e86\u5bf9\u4e8e\u6709\u9650\u5bbd\u7684\u795e\u7ecf\u7f51\u7edc\uff0c\u4e92\u4fe1\u606f\u540c\u6837\u5728\u52a8\u529b\u7b49\u8ddd\u70b9\u9644\u8fd1\u6700\u5927\u5316\uff0c\u4ece\u800c\u6269\u5c55\u4e86\u7406\u8bba\u7684\u7ed3\u679c\u3002<\/span><\/section>\n

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\u56fe3. \u539f\u8bba\u6587\u4e2d\u7684\u5b9e\u9a8c\u6570\u636e\u56fe\u4e00\u3002\u5c55\u73b0\u5728\u4e0d\u540c\u6df1\u5ea6\u3001\u5bbd\u5ea6\u548c\u521d\u59cb\u5316\u53c2\u6570\u4e0b\u6709\u9650\u795e\u7ecf\u7f51\u7edc\u4e2d\u8f93\u5165\u8f93\u51fa\u4e92\u4fe1\u606f\u7684\u503c\u3002\u4ece\u56fe\u4e2d\u53ef\u770b\u51fa\u4e34\u754c\u7ebf\uff08EOC\uff09\u9644\u8fd1\u7684\u4e92\u4fe1\u606f\u8f83\u5927\uff0c\u8fdb\u4e00\u6b65\u7cbe\u7ec6\u8ba1\u7b97\u53ef\u5f97\u6700\u5927\u503c\u70b9\u5728\u52a8\u529b\u7b49\u8ddd\u70b9\uff08DI\uff09\u9644\u8fd1\u3002<\/span><\/p>\n


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\u4e94\u3001\u603b\u7ed3<\/span><\/strong><\/strong><\/p>\n<\/section>\n

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

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\u603b\u800c\u8a00\u4e4b\uff0c\u8be5\u8bba\u6587\u9996\u5148\u5bf9\u6709\u5173\u795e\u7ecf\u7f51\u7edc\u5e73\u5747\u573a\u8fd1\u4f3c\u7684\u7406\u8bba\u5de5\u4f5c\u8fdb\u884c\u4e86\u603b\u7ed3\uff0c\u63d0\u51fa\u4e86\u4e00\u4e2a\u7edf\u4e00\u7684\u6846\u67b6\uff1b\u5e76\u4e14\u76f8\u5bf9\u9886\u57df\u5185\u7684\u5176\u4ed6\u7814\u7a76\uff0c\u63ed\u793a\u4e86\u72ec\u7acb\u540c\u5206\u5e03\u5047\u8bbe\u7684\u95ee\u9898\uff0c\u91cd\u65b0\u63d0\u51fa\u66f4\u4e3a\u4e25\u8c28\u7684\u795e\u7ecf\u7f51\u7edc\u5e73\u5747\u573a\u8fd1\u4f3c\u65b9\u6cd5\u3002\u5229\u7528\u65b0\u7684\u7406\u8bba\u65b9\u6cd5\uff0c\u8be5\u8bba\u6587\u5728\u89e3\u6790\u7406\u8bba\u548c\u5b9e\u9a8c\u4e24\u65b9\u9762\u8bc1\u660e\u52a8\u529b\u7b49\u8ddd\u70b9\u4e0a\u4e92\u4fe1\u606f\u4e0b\u754c\u7684\u6700\u5927\u5316\u3002\u5728\u6b64\u57fa\u7840\u4e0a\uff0c\u7814\u7a76\u8005\u5206\u6790\u4e86\u52a8\u529b\u5b66\u7b49\u8ddd\u70b9\u6761\u4ef6\u4e0e\u795e\u7ecf\u7f51\u7edc\u6784\u6210\u6700\u4f18\u4fe1\u9053\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/span><\/section>\n

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[1] Aaron van den Oord, Y. Li, and O. Vinyals, Representation learning with contrastive predictive coding, arXiv:1807.03748 (2018).<\/span><\/section>\n
[2] O. Henaff, Data-efficient image recognition with contrastive predictive coding, in Proceedings of the International Conference on Machine Learning (PMLR, 2020), pp. 4182\u20134192.<\/span><\/section>\n
[3] Y. Tian, D. Krishnan, and P. Isola, Contrastive multiview coding, in Proceedings of the European Conference on Computer Vision (Springer, Berlin, 2020), pp. 776\u2013794.<\/span><\/section>\n
[4] R. D. Hjelm, A. Fedorov, S. Lavoie-Marchildon, K. Grewal, P. Bachman, A. Trischler, and Y. Bengio, Learning deep representations by mutual information estimation and maximization, International Conference on Learning Representations (OpenReview.net, 2019).<\/span><\/section>\n
[5] B. Poole, S. Lahiri, M. Raghu, J. Sohl-Dickstein, and S. Ganguli, Exponential expressivity in deep neural networks through transient chaos, in Proceedings of the 30th Conference on Neural Information Processing Systems, Barcelona, Spain, edited by D. Lee, M. Sugiyama, U. Luxburg, I. Guyon, and R. Garnett, Vol. 29 (Curran Associates, Inc., 2016).<\/span><\/section>\n
[6] Schoenholz, S. S., Gilmer, J., Ganguli, S. & Sohl-Dickstein, J. Deep Information Propagation. arXiv:1611.01232 [cs, stat]<\/em> (2017).<\/span><\/section>\n
[7] T. M. Cover, Elements of Information Theory (John Wiley & Sons, New York, NY, 1999).<\/span><\/section>\n
[8] W. Kang and S. Ulukus, A new data processing inequality and its applications in distributed source and channel coding, IEEE Trans. Inf. Theory 57, 56 (2010).<\/span><\/section>\n
[9] C. Zhou, Q. Zhuang, M. Mattina, and P. N. Whatmough, Strong data processing inequality in neural networks with noisy neurons and its implications, in Proceedings of the IEEE International Symposium on Information.<\/span><\/section>\n
[10] S. Mei, T. Misiakiewicz, and A. Montanari, Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit, in Proceedings of the Conference on Learning Theory (PMLR, 2019), pp. 2388\u20132464.<\/span><\/section>\n
[11] P.-M. Nguyen, Mean field limit of the learning dynamics of multilayer neural networks, arXiv:1902.02880 (2019).<\/span><\/section>\n
[12] A. Painsky and N. Tishby, Gaussian lower bound for the information bottleneck limit, J. Mach. Learn. Res. 18, 1 (2018).<\/span><\/section>\n
[13] G. Chechik, A. Globerson, N. Tishby, and Y. Weiss, Information bottleneck for Gaussian variables, in Advances in Neural Information Processing Systems, edited by S. Thrun, L. Saul, and B. Sch\u00f6lkopf, Vol. 16 (MIT Press, 2003).<\/span><\/section>\n
[14] G. Ughi, Studies on neural networks: Information propagation at initialisation and robustness to adversarial examples, Ph.D. thesis, University of Oxford (2022).<\/span><\/section>\n
[15] J. Pennington, S. Schoenholz, and S. Ganguli, Resurrecting the sigmoid in deep learning through dynamical isometry: Theory and practice, in Proceedings of the 31st Conferenceon Neural Information Processing Systems, Long Beach, CA, USA, edited by I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Vol. 30 (Curran Associates, Inc., 2017).<\/span><\/section>\n
[16] A. M. Saxe, J. L. McClelland, and S. Ganguli, Exact solutions to the nonlinear dynamics of learning in deep linear neural networks, International Conference on Learning Representations (OpenReview.net, 2014).<\/span><\/section>\n

[17] J. A. Mingo and R. Speicher, Free Probability and Random Matrices (Springer, Berlin, 2017), Vol. 35.<\/span><\/p>\n


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\uff08\u53c2\u8003\u6587\u732e\u53ef\u4e0a\u4e0b\u6ed1\u52a8<\/strong>\u67e5\u770b\uff09<\/p>\n<\/section>\n<\/section>\n


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\u56e0\u679c\u6d8c\u73b0\u8bfb\u4e66\u4f1a\u7b2c\u4e09\u5b63\u542f\u52a8<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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\u6d8c\u73b0\u65e0\u7591\u662f\u590d\u6742\u7cfb\u7edf\u8bf8\u591a\u73b0\u8c61\u4e2d\u6700\u795e\u79d8\u83ab\u6d4b\u7684\u4e00\u4e2a\u3002\u4ece\u9e1f\u7fa4\u805a\u96c6\u3001\u8424\u706b\u866b\u540c\u6b65\u3001\u871c\u8702\u821e\u8e48\uff0c\u5230\u5b87\u5b99\u8d77\u6e90\u3001\u751f\u547d\u6f14\u5316\u3001\u610f\u8bc6\u4ea7\u751f\uff0c\u6211\u4eec\u751f\u6d3b\u5728\u4e00\u4e2a\u201c\u6d8c\u73b0\u201d\u7684\u4e16\u754c\u4e2d\u3002\u6240\u8c13\u7684\u6d8c\u73b0\uff0c\u662f\u6307\u590d\u6742\u7cfb\u7edf\u5728\u5b8f\u89c2\u6240\u5c55\u73b0\u51fa\u6765\u7684\uff0c\u65e0\u6cd5\u5f52\u7ea6\u5230\u5fae\u89c2\u7684\u7279\u6027\u6216\u89c4\u5f8b\u3002\u65b0\u5174\u7684\u56e0\u679c\u6d8c\u73b0\u7406\u8bba\u6709\u671b\u4e3a\u91cf\u5316\u591a\u5c3a\u5ea6\u590d\u6742\u7cfb\u7edf\u4e2d\u7684\u6d8c\u73b0\u73b0\u8c61\u63d0\u4f9b\u5f3a\u5927\u5de5\u5177\u3002<\/span><\/section>\n


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\u7531\u5317\u4eac\u5e08\u8303\u5927\u5b66\u6559\u6388\u3001\u96c6\u667a\u4ff1\u4e50\u90e8\u521b\u59cb\u4eba\u5f20\u6c5f\u7b49\u4eba\u53d1\u8d77\u7684\u300c\u56e0\u679c\u6d8c\u73b0\u300d\u7cfb\u5217\u8bfb\u4e66\u4f1a\u7b2c\u4e09\u5b63\uff0c\u5c06\u7ec4\u7ec7\u5bf9\u672c\u8bdd\u9898\u611f\u5174\u8da3\u7684\u670b\u53cb\uff0c\u6df1\u5165\u63a2\u8ba8\u56e0\u679c\u6d8c\u73b0\u7684\u6838\u5fc3\u7406\u8bba\uff0c\u8be6\u7ec6\u68b3\u7406\u9886\u57df\u53d1\u5c55\u8109\u7edc\uff0c\u5e76\u53d1\u6398\u56e0\u679c\u6d8c\u73b0\u5728\u751f\u7269\u7f51\u7edc\u548c\u8111\u7f51\u7edc\u3001\u6d8c\u73b0\u63a2\u6d4b\u7b49\u65b9\u9762\u7684\u5e94\u7528\u3002\u8bfb\u4e66\u4f1a\u81ea7\u670811\u65e5\u5f00\u59cb\uff0c\u6bcf\u5468\u4e8c\u665a19:00-21:00\uff0c\u9884\u8ba1\u6301\u7eed\u65f6\u95f48\uff5e10\u5468\u3002\u6b22\u8fce\u611f\u5174\u8da3\u7684\u670b\u53cb\u62a5\u540d\u53c2\u4e0e\u3002<\/span><\/p>\n


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1. <\/strong>\u4f5c\u4e3a\u56e0\u679c\u79d1\u5b66\u5bb6\u7684\u795e\u7ecf\u7cfb\u7edf\uff1a\u56e0\u679c\u7f16\u7801<\/a><\/strong><\/span><\/section>\n
2. <\/strong>\u590d\u6742\u7cfb\u7edf\u7684\u5185\u90e8\u7ed3\u6784\u5982\u4f55\u5f71\u54cd\u4fe1\u606f\u70ed\u529b\u5b66\uff1f<\/a><\/strong><\/span><\/section>\n
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4. \u300a\u5f20\u6c5f\u00b7\u590d\u6742\u79d1\u5b66\u524d\u6cbf27\u8bb2\u300b\u5b8c\u6574\u4e0a\u7ebf\uff01<\/strong><\/a><\/strong><\/strong><\/strong><\/section>\n
5. <\/strong><\/strong><\/strong><\/strong>\u52a0\u5165\u96c6\u667a\u5b66\u56edVIP\uff0c\u83b7\u5f9720\u5468\u5e74\u201c\u6d8c\u73b0\u201d\u5b66\u672f\u5e74\u4f1a\u5165\u573a\u5238\uff01<\/a><\/strong><\/strong><\/strong><\/strong><\/span><\/section>\n
6. <\/strong><\/strong><\/strong>\u52a0\u5165\u96c6\u667a\uff0c\u4e00\u8d77\u590d\u6742\uff01<\/strong><\/strong><\/strong><\/span><\/a><\/section>\n


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\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u62a5\u540d\u8bfb\u4e66\u4f1a<\/strong><\/strong><\/span><\/strong><\/span><\/strong><\/section>\n

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