{"id":21833,"date":"2020-11-08T18:25:41","date_gmt":"2020-11-08T10:25:41","guid":{"rendered":"https:\/\/swarma.org\/?p=21833"},"modified":"2020-11-08T18:25:41","modified_gmt":"2020-11-08T10:25:41","slug":"%e4%bb%8a%e6%99%9a8%e7%82%b9%e7%9b%b4%e6%92%ad%ef%bc%9a%e5%9b%a0%e6%9e%9c%e6%8e%a8%e7%90%86%e4%b8%8e%e7%a8%b3%e5%ae%9a%e5%ad%a6%e4%b9%a0-%e5%9b%a0%e6%9e%9c%e7%a7%91%e5%ad%a6%e4%b8%8ecasual-ai","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=21833","title":{"rendered":"\u4eca\u665a8\u70b9\u76f4\u64ad\uff1a\u56e0\u679c\u63a8\u7406\u4e0e\u7a33\u5b9a\u5b66\u4e60 | \u56e0\u679c\u79d1\u5b66\u4e0eCasual AI\u8bfb\u4e66\u4f1a"},"content":{"rendered":"
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\u4eca\u665a8\u70b9\uff0c\u201c\u56e0\u679c\u79d1\u5b66\u4e0eCasual A<\/span>I\u201d\u8bfb\u4e66\u4f1a\u5c06\u8fdb\u884c\u7b2c\u4e03\u671f\u7684\u7ebf\u4e0a\u8bba\u6587\u5206\u4eab\uff0c\u4e3b\u9898\u662f\u201c\u56e0\u679c\u63a8\u7406\u4e0e\u7a33\u5b9a\u5b66\u4e60\u201d\uff0c\u5c06\u7531\u6e05\u534e\u5927\u5b66\u8ba1\u7b97\u673a\u7cfb\u5728\u8bfb\u535a\u58eb\u751f\u6c88\u54f2\u8a00\u548c\u6e05\u534e\u5927\u5b66\u8ba1\u7b97\u673a\u7cfb\u5728\u8bfb\u535a\u58eb\u751f\u5218\u5bb6\u7855\u6765\u8fdb\u884c\u5206\u4eab\uff0c\u672c\u6b21\u5185\u5bb9\u5c06\u5728\u96c6\u667a\u4ff1\u4e50\u90e8B\u7ad9\u76f4\u64ad\uff0c\u6b22\u8fce\u5927\u5bb6\u5728\u6587\u672b\u626b\u7801\u62a5\u540d\uff0c\u83b7\u53d6\u76f4\u64ad\u94fe\u63a5\u548c\u63d0\u9192\u3002<\/span><\/section>\n

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Part 1: <\/span><\/strong><\/strong><\/span><\/p>\n

Causal Inference and Stable Learning<\/span><\/strong><\/strong><\/span><\/p>\n

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\u5206\u4eab\u8005\uff1a<\/span><\/span><\/strong><\/span>\u6c88\u54f2\u8a00 \u6e05\u534e\u5927\u5b66\u8ba1\u7b97\u673a\u7cfb\u5728\u8bfb\u535a\u58eb\u751f<\/span><\/span><\/p>\n


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\u5206\u4eab\u5927\u7eb2\uff1a<\/span><\/strong><\/span><\/p>\n

1. Causal Inference and Its Implication for Learning<\/span><\/p>\n

2. Learning Stability and Robustness<\/span><\/p>\n

3. Theory and Algorithms for Stable Learning<\/span><\/p>\n

4. Applications and Benchmarks<\/span><\/p>\n


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\u5728\u5e38\u89c1\u7684\u673a\u5668\u5b66\u4e60\u95ee\u9898\u4e2d\uff0c\u6211\u4eec\u4f1a\u4f7f\u7528\u4e00\u4e2a\u57fa\u4e8e\u8bad\u7ec3\u6570\u636e\u96c6\u4f30\u8ba1\u7684\u6a21\u578b\u6765\u9884\u6d4b\u672a\u6765\u7684\u7ed3\u679c\u503c\u3002\u5f53\u6d4b\u8bd5\u6570\u636e\u548c\u8bad\u7ec3\u6570\u636e\u6765\u81ea\u540c\u4e00\u5206\u5e03\u65f6\uff0c\u8bb8\u591a\u5b66\u4e60\u7b97\u6cd5\u90fd\u88ab\u8bc1\u660e\u662f\u6709\u6548\u7684\u3002\u7136\u800c\uff0c\u5728\u7ed9\u5b9a\u7684\u8bad\u7ec3\u6570\u636e\u5206\u5e03\u4e0a\u6027\u80fd\u6700\u597d\u7684\u6a21\u578b\u901a\u5e38\u4f1a\u5438\u6536\u548c\u62df\u5408\u4e00\u4e9b\u7279\u5f81\u4e4b\u95f4\u5fae\u5999\u7684\u7edf\u8ba1\u5173\u7cfb\u2014\u2014\u865a\u5047\u5173\u8054\uff0c\u5f53\u6a21\u578b\u88ab\u5e94\u7528\u4e8e\u5206\u5e03\u4e0d\u540c\u4e8e\u8bad\u7ec3\u6570\u636e\u7684\u6d4b\u8bd5\u6570\u636e\u65f6\uff0c\u8fd9\u4e9b\u5229\u7528\u865a\u5047\u5173\u8054\u7684\u6a21\u578b\u53ef\u80fd\u66f4\u5bb9\u6613\u51fa\u73b0\u9884\u6d4b\u9519\u8bef\u3002\u5982\u4f55\u5f00\u53d1\u51fa\u5bf9\u6570\u636e\u53d8\u5316\u5177\u6709\u7a33\u5b9a\u6027\u548c\u9c81\u68d2\u6027\u7684\u5b66\u4e60\u6a21\u578b\u5bf9\u4e8e\u5b66\u672f\u7814\u7a76\u4ee5\u53ca\u90a3\u4e9b\u5bf9\u4e8e\u98ce\u9669\u6bd4\u8f83\u654f\u611f\u7684\u5b9e\u9645\u5e94\u7528\u90fd\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002<\/span><\/p>\n


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\u5728\u8fd9\u6b21\u5206\u4eab\u4e2d\uff0c\u6211\u4eec\u4f1a\u628a\u56e0\u679c\u5206\u6790\u7684\u601d\u60f3\u5f15\u5165\u5230\u4f20\u7edf\u7684\u673a\u5668\u5b66\u4e60\u8bbe\u5b9a\u5f53\u4e2d\uff0c\u63a2\u8ba8\u5982\u4f55\u5229\u7528\u597d\u8fd9\u4e00\u7ecf\u5178\u7684\u7edf\u8ba1\u5206\u6790\u5de5\u5177\u6765\u89e3\u51b3\u66f4\u4e3a\u590d\u6742\u7684\u673a\u5668\u5b66\u4e60\u5b9e\u9645\u95ee\u9898\uff1b\u540c\u65f6\uff0c\u6211\u4eec\u4e5f\u4f1a\u62d3\u5bbd\u4f20\u7edf\u673a\u5668\u5b66\u4e60\u7684\u8bc4\u4ef7\u6807\u51c6\uff0c\u5f15\u5165\u7a33\u5b9a\u5b66\u4e60\u8fd9\u4e00\u6982\u5ff5\u6765\u523b\u753b\u4e00\u4e2a\u6a21\u578b\u7684\u7efc\u5408\u6027\u80fd\uff0c\u5e76\u7ed3\u5408\u56e0\u679c\u7684\u6280\u672f\u63d0\u51fa\u4e00\u4e9b\u6709\u6548\u7684\u7b97\u6cd5\u3002<\/span><\/p>\n

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Part2:<\/span><\/strong><\/strong><\/span><\/p>\n

Causality and Its Connection to Robust Machine Learning (\u8bba\u6587\u89e3\u8bfb)<\/span><\/strong><\/strong><\/span><\/p>\n

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\u5206\u4eab\u8005\uff1a<\/span><\/strong><\/span>\u5218\u5bb6\u7855 \u6e05\u534e\u5927\u5b66\u8ba1\u7b97\u673a\u7cfb\u5728\u8bfb\u535a\u58eb\u751f<\/span><\/p>\n

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\u672c\u6b21\u5206\u4eab\u4e3b\u8981\u5305\u542b\u5bf9\u4e8e\u56e0\u679c\u7a33\u5b9a\u9884\u6d4b\u548c\u5206\u5e03\u9c81\u68d2\u4f18\u5316\u4e24\u4e2a\u65b9\u9762\u7ecf\u5178\u8bba\u6587\u7684\u5206\u4eab\u548c\u89e3\u8bfb\uff0c\u5e76\u901a\u8fc7\u4e00\u5b9a\u7684\u5f62\u5f0f\u5316\u5efa\u7acb\u8d77\u56e0\u679c\u53d1\u73b0\u548c\u9c81\u68d2\u673a\u5668\u5b66\u4e60\u4e4b\u95f4\u7684\u6865\u6881\uff0c\u63d0\u4f9b\u4e00\u4e2a\u66f4\u52a0\u7edf\u4e00\u7684\u89c6\u89d2\u6765\u770b\u5f85\u56e0\u679c\u548c\u673a\u5668\u5b66\u4e60\u3002<\/span><\/p>\n


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\u4e3b\u8981\u5206\u4eab\u8bba\u6587\u5217\u8868\uff1a<\/span><\/strong><\/span><\/section>\n
J.Peters et al. Causal inference by using invariant prediction: identification and confidence intervals<\/span><\/section>\n
H.Namkoong et al. Stochastic Gradient Methods for Distributionally Robust Optimization with f-Divergences<\/span><\/section>\n

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\u76f4\u64ad\u65f6\u95f4\uff1a\u4eca\u665a<\/span><\/strong>\uff0811\u67088\u65e5\uff09 20:00-23:00<\/span><\/p>\n


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\u53c2\u4e0e\u65b9\u5f0f 1\uff1a\u817e\u8baf\u4f1a\u8bae\uff08\u9700\u62a5\u540d\u53c2\u52a0\u7cfb\u5217\u8bfb\u4e66\u4f1a\uff09<\/strong><\/p>\n

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\u53c2\u4e0e\u65b9\u5f0f 2\uff1a\u96c6\u667a\u4ff1\u4e50\u90e8B\u7ad9\u76f4\u64ad<\/strong><\/p>\n


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\u626b\u63cf\u4e0b\u65b9\u4e8c\u7ef4\u7801\uff0c\u70b9\u51fb\u300c\u6211\u8981\u542c\u300d\u62a5\u540d\uff0c\u5185\u9644B\u7ad9\u76f4\u64ad\u5730\u5740\u3002<\/strong><\/span><\/p>\n

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\u7cfb\u5217\u8bfb\u4e66\u4f1a\u62a5\u540d<\/strong><\/span><\/p>\n

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\u5927\u6570\u636e\u65f6\u4ee3\u7684\u4e0b\u4e00\u573a\u53d8\u9769\u2014\u2014\u56e0\u679c\u9769\u547d\u6b63\u5728\u915d\u917f\u4e4b\u4e2d\uff0c\u901a\u8fc7\u878d\u5408\u56e0\u679c\u63a8\u7406\u548c\u673a\u5668\u5b66\u4e60\u800c\u6784\u5efa\u51fa\u6765\u7684Causal AI\u7cfb\u7edf\uff0c\u6709\u671b\u5960\u5b9a\u5f3a\u4eba\u5de5\u667a\u80fd\u7684\u57fa\u77f3\u3002<\/span><\/p>\n


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\u96c6\u667a\u4ff1\u4e50\u90e8\u8054\u5408\u5317\u4eac\u667a\u6e90\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u9662\uff0c\u9080\u8bf7\u4e86\u4e00\u6279\u5bf9\u56e0\u679c\u79d1\u5b66\u4e0eCasual AI\u611f\u5174\u8da3\u7684\u7814\u7a76\u8005\uff0c\u5f00\u5c55\u4e3a\u671f2-3\u4e2a\u6708\u7684\u7cfb\u5217\u7ebf\u4e0a\u8bfb\u4e66\u4f1a\uff0c\u7814\u8bfb\u7ecf\u5178\u548c\u524d\u6cbf\u8bba\u6587\uff0c\u5e76\u5c1d\u8bd5\u96c6\u4f53\u64b0\u5199\u4e00\u90e8\u4e66\u7c4d\u3002\u5982\u679c\u4f60\u4e5f\u4ece\u4e8b\u76f8\u5173\u7684\u7814\u7a76\u3001\u5e94\u7528\u5de5\u4f5c\uff0c\u6b22\u8fce\u62a5\u540d\uff0c\u53c2\u4e0e\u8bfb\u4e66\u4f1a\u7684\u8ba8\u8bba\uff01<\/span><\/p>\n

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\u65f6\u95f4\uff1a<\/span><\/strong>9\u670820\u65e5\u8d77\uff0c\u6bcf\u5468\u65e5\u665a19:00-21:00\uff0c\u6301\u7eed\u7ea62-3\u4e2a\u6708<\/span><\/section>\n
\u6a21\u5f0f\uff1a<\/span><\/strong>\u7ebf\u4e0a\u95ed\u95e8\u8bfb\u4e66\u4f1a\uff1b\u6536\u8d39-\u9000\u6b3e\u7684\u4fdd\u8bc1\u91d1\u6a21\u5f0f\uff1b\u8bfb\u4e66\u4f1a\u6210\u5458\u8ba4\u9886\u89e3\u8bfb\u8bba\u6587<\/span><\/section>\n
\u8d39\u7528\uff1a<\/span><\/strong>299\/\u4eba<\/span><\/section>\n

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\u4e86\u89e3\u8bfb\u4e66\u4f1a\u5177\u4f53\u89c4\u5219\u3001\u62a5\u540d\u8bfb\u4e66\u4f1a\u8bf7\u70b9\u51fb\u4e0b\u65b9\u6587\u7ae0\uff1a<\/span><\/p>\n

\u56e0\u679c\u79d1\u5b66\u4e0e Causal AI \u7cfb\u5217\u8bfb\u4e66\u4f1a | \u4f17\u5305\u51fa\u4e66<\/span><\/a><\/section>\n


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\u76ee\u524d\u8bfb\u4e66\u4f1a\u5df2\u7ecf\u6709\u8d85\u8fc7130\u4f59\u4eba\u7684\u6d77\u5185\u5916\u9ad8\u6821\u79d1\u7814\u9662\u6240\u7684\u4e00\u7ebf\u79d1\u7814\u5de5\u4f5c\u8005\u4ee5\u53ca\u4e92\u8054\u7f51\u4e00\u7ebf\u4ece\u4e1a\u4eba\u5458\u53c2\u4e0e\uff0c\u5982\u679c\u4f60\u4e5f\u5bf9\u8fd9\u4e2a\u4e3b\u9898\u611f\u5174\u8da3\uff0c\u5c31\u5feb\u52a0\u5165\u6211\u4eec\u5427\uff01<\/span><\/p>\n


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\u9488\u5bf9\u8bfb\u4e66\u4f1a\u7684\u4e3b\u9898\uff0c\u7531\u53d1\u8d77\u4eba\u9f9a\u9e64\u626c\u8bbe\u7f6e\u597d\u4e86\u5185\u5bb9\u6846\u67b6\uff0c\u6bcf\u4e2a\u4e3b\u9898\u4e0b\u6709\u4e00\u4e2a\u8d1f\u8d23\u4eba\u6765\u8d1f\u8d23\u7ef4\u62a4\u7ec4\u7ec7\u76f8\u5173\u5185\u5bb9\uff0c\u76ee\u524d\u5df2\u7ecf\u5b9a\u597d\u7684\u5982\u56fe\u6240\u793a\uff0c\u6b22\u8fce\u5bf9\u4e3b\u9898\u611f\u5174\u8da3\u7684\u8054\u7cfb\u76f8\u5173\u8d1f\u8d23\u4eba\uff0c\u4ee5\u53ca\u6765\u8ba4\u9886\u76f8\u5173\u4e3b\u9898~<\/span><\/p>\n


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\u56fe\u7075\u5956\u5f97\u4e3bJudea Pearl \u667a\u6e90\u5927\u4f1a\u6f14\u8bb2\uff1a\u4ece\u201c\u5927\u6570\u636e\u9769\u547d\u201d\u5230\u201c\u56e0\u679c\u9769\u547d\u201d<\/strong><\/a>
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\u56e0\u679c\u53d1\u73b0\uff1a\u5982\u4f55\u8ba9\u7b97\u6cd5\u6210\u4e3a\u590d\u6742\u7cfb\u7edf\u4e2d\u7684\u201c\u798f\u5c14\u6469\u65af\u201d\uff1f<\/strong><\/a>
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\u56e0\u679c\u79d1\u5b66\uff1a\u8fde\u63a5\u7edf\u8ba1\u5b66\u3001\u673a\u5668\u5b66\u4e60\u4e0e\u81ea\u52a8\u63a8\u7406\u7684\u65b0\u5174\u4ea4\u53c9\u9886\u57df<\/strong><\/a>
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\u52a0\u5165\u96c6\u667a\uff0c\u4e00\u8d77\u590d\u6742\uff01<\/strong><\/span><\/a><\/section>\n


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\u5546\u52a1\u5408\u4f5c\u53ca\u6295\u7a3f\u8f6c\u8f7d\uff5cswarma@swarma.org
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\u52a0\u5165\u201c\u6ca1\u6709\u56f4\u5899\u7684\u7814\u7a76\u6240\u201d<\/span><\/strong><\/span><\/p>\n

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\u8ba9\u82f9\u679c\u7838\u5f97\u66f4\u731b\u70c8\u4e9b\u5427\uff01<\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


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\u4eca\u665a8\u70b9\uff0c\u201c\u56e0\u679c\u79d1\u5b66\u4e0eCasual AI\u201d\u8bfb\u4e66\u4f1a\u5c06\u8fdb\u884c\u7b2c\u4e03\u671f\u7684\u7ebf\u4e0a\u8bba\u6587\u5206\u4eab\uff0c\u4e3b\u9898\u662f\u201c\u56e0\u679c\u63a8\u7406\u4e0e\u7a33\u5b9a\u5b66\u4e60\u201d\uff0c\u5c06\u7531\u6e05\u534e\u5927\u5b66\u8ba1\u7b97\u673a\u7cfb\u5728\u8bfb\u535a\u58eb\u751f\u6c88\u54f2\u8a00\u548c\u6e05\u534e\u5927\u5b66\u8ba1\u7b97\u673a\u7cfb\u5728\u8bfb\u535a\u58eb\u751f\u5218\u5bb6\u7855\u6765\u8fdb\u884c\u5206\u4eab\uff0c\u672c\u6b21\u5185\u5bb9\u5c06\u5728\u96c6\u667a\u4ff1\u4e50\u90e8B\u7ad9\u76f4\u64ad\uff0c\u6b22\u8fce\u5927\u5bb6\u5728\u6587\u672b\u626b\u7801\u62a5\u540d\uff0c\u83b7\u53d6\u76f4\u64ad\u94fe\u63a5\u548c\u63d0\u9192\u3002 Part 1:  Cau…<\/p>\n","protected":false},"author":1,"featured_media":21828,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"special":[],"_links":{"self":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/21833"}],"collection":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=21833"}],"version-history":[{"count":0,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/21833\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/media\/21828"}],"wp:attachment":[{"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=21833"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=21833"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=21833"},{"taxonomy":"special","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fspecial&post=21833"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}