{"id":26954,"date":"2021-06-12T21:41:46","date_gmt":"2021-06-12T13:41:46","guid":{"rendered":"https:\/\/swarma.org\/?p=26954"},"modified":"2021-06-12T21:41:46","modified_gmt":"2021-06-12T13:41:46","slug":"pcic-2021%e5%8d%8e%e4%b8%ba%e5%9b%a0%e6%9e%9c%e6%8e%a8%e7%90%86%e6%8c%91%e6%88%98%e8%b5%9b%e5%bc%80%e6%94%be%e7%bb%84%e9%98%9f%e6%8a%a5%e5%90%8d","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=26954","title":{"rendered":"PCIC 2021\u534e\u4e3a\u56e0\u679c\u63a8\u7406\u6311\u6218\u8d5b\u5f00\u653e\u7ec4\u961f\u62a5\u540d"},"content":{"rendered":"
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PCIC 2021\u534e\u4e3a\u56e0\u679c\u63a8\u7406\u6311\u6218\u8d5b<\/strong><\/span><\/h2>\n

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PCIC<\/span>\uff08the Pacific Causal Inference Conference\uff0c\u6cdb\u592a\u5e73\u6d0b\u56e0\u679c\u63a8\u65ad\u5927\u4f1a\uff09<\/span>\u7531\u5317\u4eac\u5927\u5b66\u8bb2\u5e2d\u6559\u6388\u3001\u5317\u4eac\u5927\u5b66\u516c\u5171\u536b\u751f\u5b66\u9662\u751f\u7269\u7edf\u8ba1\u7cfb\u7cfb\u4e3b\u4efb\u3001\u5317\u4eac\u5927\u5b66\u5317\u4eac\u56fd\u9645\u6570\u5b66\u7814\u7a76\u4e2d\u5fc3\u751f\u7269\u7edf\u8ba1\u548c\u4fe1\u606f\u7814\u7a76\u4e8b\u5ba4\u4e3b\u4efb\u5468\u6653\u534e\u7ec4\u7ec7\u53d1\u8d77\uff0c\u7531\u5317\u4eac\u5927\u5b66\u3001\u56fd\u9645\u751f\u7269\u7edf\u8ba1\u5b66\u4f1a\u4e2d\u56fd\u5206\u4f1a\u7b49\u673a\u6784\u4e3b\u529e\u3001\u534e\u4e3a\u8bfa\u4e9a\u65b9\u821f\u5b9e\u9a8c\u5ba4\u3001\u96c6\u667a\u4ff1\u4e50\u90e8\u7b49\u673a\u6784\u534f\u529e\u3002<\/span><\/section>\n

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PCIC\u662f\u56e0\u679c\u79d1\u5b66\u9886\u57df\u4e00\u5e74\u4e00\u5ea6\u7684\u76db\u4f1a\uff0cPCIC 2021\u5c06\u4e8e2021\u5e749\u670811\u65e5\u81f312\u65e5\u5728\u5317\u4eac\u4ee5\u7ebf\u4e0a+\u7ebf\u4e0b\u76f8\u7ed3\u5408\u7684\u65b9\u5f0f\u4e3e\u884c\u3002\u672c\u5927\u4f1a\u805a\u96c6\u4e86\u6d77\u5185\u5916\u4e00\u5927\u6279\u56e0\u679c\u79d1\u5b66\u76f8\u5173\u9886\u57df\u7684\u5b66\u672f\u5927\u62ff\u6c47\u805a\u4e00\u5802\uff0c\u5171\u540c\u63a2\u8ba8\u56e0\u679c\u79d1\u5b66\u7684\u65b0\u8fdb\u5c55\uff0c\u63a2\u7d22\u65b0\u7684\u79d1\u7814\u65b9\u5411\uff0c\u5438\u5f15\u4e86\u975e\u5e38\u591a\u4f18\u79c0\u7684\u79d1\u7814\u5de5\u4f5c\u8005\u6295\u8eab\u4e8e\u8be5\u9886\u57df\uff0c\u63a8\u52a8\u4e86\u56e0\u679c\u79d1\u5b66\u7684\u7814\u7a76\u8fdb\u7a0b\u3002<\/span><\/section>\n

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\u4f1a\u8bae\u671f\u95f4\u4f1a\u8bae\u7ec4\u59d4\u4f1a\uff0c\u5317\u4eac\u5927\u5b66\u548c\u534e\u4e3a\u8bfa\u4e9a\u65b9\u821f\u5b9e\u9a8c\u5ba4\u5171\u540c\u7ec4\u7ec7\u4e86\u6b64\u6b21\u56e0\u679c\u7ade\u8d5b\u3002\u6b64\u6b21\u7ade\u8d5b\u5206\u4e3a\u4e24\u4e2a\u8d5b\u9053\u3002\u8d5b\u90531\u7684\u76ee\u6807\u662f\u4ece\u8fde\u7eed\u65f6\u95f4\u4e8b\u4ef6\u578b\u6570\u636e\u4e2d\u53d1\u73b0\u56e0\u679c\u5173\u7cfb\u3002\u4e8b\u4ef6\u578b\u6570\u636e\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u4f1a\u7ecf\u5e38\u9047\u5230\uff0c\u4f8b\u5982\u76d1\u6d4b\u7535\u4fe1\u7cfb\u7edf\u662f\u5426\u6b63\u5e38\u8fd0\u884c\u7684\u62a5\u8b66\u8bb0\u5f55\u3002\u5b66\u4e60\u62a5\u8b66\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\u53ef\u4ee5\u7528\u6765\u8bc6\u522b\u6839\u56e0\u62a5\u8b66\uff0c\u4ece\u800c\u5e2e\u52a9\u5feb\u901f\u5b9a\u4f4d\u7cfb\u7edf\u7684\u5b9e\u9645\u6545\u969c\u3002\u8d5b\u90532\u5219\u5173\u6ce8\u7528\u6237\u7684\u504f\u597d\u9884\u6d4b\u3002\u5b9e\u9645\u4e2d\uff0c\u6bcf\u90e8\u7535\u5f71\u901a\u5e38\u90fd\u4f1a\u6709\u4e00\u5b9a\u7684\u63cf\u8ff0\u6027\u6807\u7b7e\u3002\u53c2\u8d5b\u8005\u57fa\u4e8e\u5173\u8054\u6570\u636e<\/span>\uff08\u7535\u5f71\u7684\u6807\u7b7e\uff09<\/span>\u548c\u56e0\u679c\u6570\u636e<\/span>\uff08\u7528\u6237\u6807\u660e\u4ed6\u559c\u6b22\u67d0\u90e8\u7535\u5f71\u7684\u539f\u56e0\u6807\u7b7e\uff09<\/span>\u5efa\u6a21\uff0c\u5e76\u7ea0\u504f\u6709\u504f\u7684\u63a8\u8350\u6570\u636e<\/span>\uff08\u7528\u6237\u9009\u62e9\u504f\u7f6e\u3001\u524d\u5e8f\u6a21\u578b\u504f\u7f6e\u7b49\uff09<\/span>\uff0c\u5b66\u4e60\u7528\u6237\u7684\u5174\u8da3\u6807\u7b7e\u3002<\/span><\/section>\n

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2021\u5e7406\u670808\u65e5\uff1a\u7ade\u8d5b\u5f00\u653e\u3002<\/span><\/p>\n

2021\u5e7406\u670815\u65e5\uff1a\u5317\u4eac\u65f6\u95f4\u665a\u4e0a11:59\uff0c\u521d\u8d5b\u63d0\u4ea4\u5f00\u653e\u3002<\/span><\/p>\n

2021\u5e7407\u670815\u65e5\uff1a\u5317\u4eac\u65f6\u95f4\u665a\u4e0a11:59\uff0c\u62a5\u540d\u548c\u7ec4\u961f\u622a\u6b62\u3002<\/span><\/p>\n

2021\u5e7408\u670810\u65e5: \u5317\u4eac\u65f6\u95f4\u665a\u4e0a11:59\uff0c\u521d\u8d5b\u7ed3\u675f\uff0c\u590d\u8d5b\u5f00\u59cb\u3002<\/span><\/p>\n

2021\u5e7408\u670822\u65e5\uff1a\u5317\u4eac\u65f6\u95f4\u665a\u4e0a11:59\uff0c\u7ade\u8d5b\u7ed3\u675f\u3002<\/span><\/p>\n

2021\u5e7409\u670801\u65e5\uff1a\u5ba3\u5e03\u83b7\u80dc\u961f\u4f0d\u3002<\/span><\/p>\n

2021\u5e7409\u670811\u65e5\uff1aPCIC 2021\u5c06\u9080\u8bf7\u83b7\u5956\u56e2\u961f\u8fdb\u884c\u6280\u672f\u62a5\u544a\u3002<\/span><\/p>\n

\u6700\u7ec8\u7684\u83b7\u5956\u961f\u4f0d\u6392\u540d\u5c06\u7531\u7ade\u8d5b\u59d4\u5458\u4f1a\u6839\u636e\u7ade\u8d5b\u6210\u7ee9\u548c\u63d0\u4ea4\u65b9\u6848\u7684\u6709\u6548\u6027\u8bc4\u5224\u3002<\/span><\/section>\n

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\u6bcf\u4e2a\u8d5b\u9053\u7684\u5956\u91d1\u603b\u989d\u5747\u4e3a\uff1a$10,000\uff08USD\uff09\uff0c\u5176\u4e2d<\/span><\/p>\n

\u2022 Gold Prize: $5,000<\/span><\/p>\n

\u2022 Silver Prize: $3,000<\/span><\/p>\n

\u2022 Bronze Prize: $2,000<\/span><\/section>\n

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https:\/\/competition.huaweicloud.com\/information\/1000041487\/introduction<\/span><\/section>\n
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PCIC 2021 Huawei Causal Inference Competition<\/span><\/strong><\/span><\/h2>\n


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The goal of causal inference is to combine external knowledge and study design to draw a causal conclusion between variables. It has gained popularity in fields including statistics, biostatistics, biomedical science, computer science, economics, epidemiology, and various social sciences. To promote both research and application on real-world problems, Huawei Noah’s Ark Lab and Peking University jointly organize the competition focusing on causal inference and discovery at the 2021 Pacific Causal Inference Conference (PCIC 2021). The datasets used in the competition are either directly collected from or generated according to real scenarios.<\/span><\/p>\n


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The competition consists of two tracks. Track 1 aims to discover the causal graphs from event sequence data, which often occur in real applications such as social interactions amongst users or alarm records indicating whether a system operates properly. Obtaining such information is meaningful to better understand the relations among entities or to find root causes that can be more informative about the actual system fault. Track 2 focuses on the user preference prediction problem. In real-world movie recommendation systems, each movie is usually associated with descriptive tags, either by users or professionals. Instead of predicting the rating of a particular user-movie pair, participants are asked to estimate a user’s preference to a particular tag. The challenge comes from the existence of many biases, including user selection bias, popularity bias, etc.<\/span><\/p>\n


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The winners will be awarded cash prizes and winner certificates, as well as invited to give talks at PCIC 2021. This conference will focus on the latest development in causal inference and will take place between Sept. 11 and Sept. 12, 2021.<\/span><\/p>\n

We look forward to your participation!<\/span><\/p>\n


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