{"id":10054,"date":"2016-07-16T01:00:00","date_gmt":"2016-07-15T17:00:00","guid":{"rendered":"http:\/\/swarma.org\/%swarma-paper%\/"},"modified":"2018-12-12T00:32:50","modified_gmt":"2018-12-11T16:32:50","slug":"%e8%87%aa%e7%84%b6%e8%af%ad%e8%a8%80%e5%a4%84%e7%90%86%e4%b8%8e%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%e8%af%bb%e4%b9%a6%e4%bc%9a%e5%bc%80%e5%a7%8b%e6%8a%a5%e5%90%8d%e4%ba%86%ef%bc%81","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=10054","title":{"rendered":"\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e0e\u6df1\u5ea6\u5b66\u4e60\u8bfb\u4e66\u4f1a\u5f00\u59cb\u62a5\u540d\u4e86\uff01"},"content":{"rendered":"
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\u4e3b\u8bb2\u4eba\uff1a<\/span><\/strong>\u674e\u5ae3\u7136<\/span><\/p>\n


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\u5317\u4eac\u5927\u5b66\u667a\u80fd\u79d1\u5b66\u4e13\u4e1a\u672c\u79d1\uff0c\u73b0\u4e3a\u9999\u6e2f\u7406\u5de5\u5927\u5b66\u5728\u8bfb\u535a\u58eb\u751f\u3002\u7814\u7a76\u65b9\u5411\u4e3a\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u7684\u8bed\u4e49\u8868\u8fbe\u548c\u8bed\u8a00\u751f\u6210\u3002\u66fe\u4e8e\u81ea\u7136\u8bed\u8a00\u9886\u57df\u7684\u9876\u7ea7\u4f1a\u8bae\u4e0a\u53d1\u8868\u591a\u7bc7\u8bba\u6587\uff0c\u5408\u8457\u6709\u300a\u79d1\u5b66\u7684\u6781\u81f4\u2014\u2014\u6f2b\u8c08\u4eba\u5de5\u667a\u80fd\u300b\u4e00\u4e66\u3002\u96c6\u667a\u4ff1\u4e50\u90e8\u6210\u5458\uff0c<\/span>\u540c\u65f6\u662f\u5fae\u4fe1\u516c\u4f17\u53f7\uff3b\u7a0b\u5e8f\u5a9b\u7684\u65e5\u5e38\uff3d\u7684\u7ef4\u62a4\u8005\u4e4b\u4e00\u5c0f\uff33\u3002<\/span><\/p>\n


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\u5730\u70b9\uff1a<\/span><\/strong>\u7f51\u7edc<\/span><\/p>\n


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\u65f6\u95f4\uff1a<\/span><\/strong>7\u6708\u5e95\u81f311\u6708\u521d\uff08\u665a\u4e0a\u6216\u5468\u672b\uff09\uff0c\u6bcf\u5468\u4e3e\u529e\u4e00\u671f\uff0c\u5171\u5341\u671f\u3002<\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


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(1)\u5b66\u5458\u62a5\u540d\u65f6\u9884\u4ea4\u4fdd\u8bc1\u91d1200\u5143\u3002<\/span><\/p>\n

(2)\u5b66\u5458\u9700\u8981\u575a\u6301\u4e0a\u5b8c\u6240\u6709\u8bbe\u5b9a\u7684\u8bfe\u7a0b\uff0c\u5e76\u4e14\u4efb\u53d6\u5176\u4e2d\u4e00\u671f\u8bfb\u4e66\u4f1a\u5199\u6210\u4e0d\u5c11\u4e8e1000\u5b57\u7684\u542c\u8bfe\u7b14\u8bb0\uff0c\u6216\u8005\u9009\u62e9\u5176\u4e2d\u4e00\u671f\uff0c\u4f5c\u4e3a\u4e3b\u8bb2\u4eba\u8fdb\u884c\u5185\u5bb9\u5206\u4eab\u3002<\/span><\/p>\n

(3)\u6ee1\u8db3\u4e0a\u8ff0\u6761\u4ef6\u7684\u5b66\u5458\uff0c\u900080%\u7684\u5b66\u8d39\uff0c\u5269\u4f59\u768420%\u8bf7\u4e3b\u8bb2\u4eba\u548c\u96c6\u667a\u5fd7\u613f\u8005\u559d\u5496\u5561\uff1b\u6ca1\u6709\u6ee1\u8db3\u4e0a\u8ff0\u6761\u4ef6\u7684\uff0c\u4e0d\u9000\u8d39\u3002<\/span><\/p>\n

(4)\u4e3b\u8bb2\u4eba\u4ece\u6240\u6536\u5230\u7684\u4f5c\u4e1a\u4e2d\u9009\u51fa\u81f3\u5c11\u4e24\u7bc7\u4f18\u79c0\u7684\u8bfb\u4e66\u7b14\u8bb0\uff0c\u5728\u96c6\u667a\u4ff1\u4e50\u90e8\u516c\u4f17\u53f7\u516c\u5f00\u53d1\u8868\u3002<\/span><\/p>\n

(5)\u6700\u7ec8\u89e3\u91ca\u6743\u5f52\u96c6\u667a\u4ff1\u4e50\u90e8\u6240\u6709\u3002<\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n


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Word Representations<\/strong><\/section>\n

Distributional vs. Distributed<\/p>\n


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Word2Vec<\/strong><\/section>\n
1.paper (model, negative sampling…)<\/section>\n
2.code<\/section>\n
3.further reading and related issues (polysemy, multilingual…)<\/section>\n
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RNN<\/strong><\/section>\n
1.neural network basics (back propagation, gradient, regularization, activations)<\/section>\n
2.RNN (model, calculation, language modeling)<\/section>\n
3.further reading and related issues (gradient vanishing, GRU, LSTM)<\/section>\n
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CNN<\/strong><\/section>\n
1.convolutional operation basics<\/section>\n
2.paper (model, pooling, sentence modeling, variable-length…)<\/section>\n
3.further reading and related issues (character-level CNN…)<\/section>\n
 <\/section>\n
Sentiment Analysis<\/strong><\/section>\n
1.Sentiment Analysis tasks and benchmarks (Stanford TreeBank…)<\/section>\n
2.papers (GAN, duyu-tang)<\/section>\n
 <\/section>\n
Machine Translation<\/strong><\/section>\n
1.Seq2Seq and encoder-decoder framework<\/section>\n
2.papers (attention, code)<\/section>\n
3.further reading and related issues (http:\/\/www.statmt.org\/ued\/? n=Public.WeeklyMeeting)<\/section>\n

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\u968f\u7740\u4eba\u5de5\u667a\u80fd\u7a0b\u5e8fAlphaGo\u4ee54:1\u7684\u5927\u6bd4\u5206\u6218\u80dc\u4eba\u7c7b\u56f4\u68cb\u4e16\u754c\u51a0\u519b\u674e\u4e16\u77f3\uff0c\u673a\u5668\u5c06\u5f81\u670d\u4eba\u7c7b\u7684\u62c5\u5fe7\u6b63\u5728\u751a\u56a3\u5c18\u4e0a\u3002\u300a\u8d70\u8fd12050\uff1a\u6ce8\u610f\u529b\u3001\u4e92\u8054\u7f51\u4e0e\u4eba\u5de5\u667a\u80fd\u300b\u5219\u4e3a\u6211\u4eec\u63cf\u7ed8\u4e86\u4e00\u5e45\u4eba\u673a\u548c\u8c10\u5171\u751f\u3001\u534f\u540c\u6f14\u5316\u7684\u5168\u65b0\u573a\u666f\u3002\u5728\u770b\u5f97\u89c1\u7684\u672a\u6765\uff0c\u4eba\u7c7b\u5c06\u8d8a\u6765\u8d8a\u591a\u5730\u6c89\u6d78\u4e8e\u4e94\u82b1\u516b\u95e8\u7684\u865a\u62df\u4e16\u754c\u4ee5\u83b7\u53d6\u5404\u5f0f\u4f53\u9a8c\uff0c\u4e0e\u6b64\u540c\u65f6\uff0c\u6211\u4eec\u5c06\u5fc3\u7518\u60c5\u613f\u5730\u5c06\u81ea\u5df1\u7684\u6ce8\u610f\u529b\u6e90\u6e90\u4e0d\u65ad\u5730\u8f93\u5165\u7ed9\u673a\u5668\u4e16\u754c\u4ee5\u4fc3\u4f7f\u5b83\u4eec\u8fdb\u5316\u3002<\/span><\/p>\n


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\"\u96c6\u667a\"<\/p>\n

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

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\u957f\u6309\u8bc6\u522b\u4e8c\u7ef4\u7801\uff0c\u5173\u6ce8\u96c6\u667aClub\uff0c<\/span><\/p>\n

\u8ba9\u6211\u4eec\u79bb\u79d1\u5b66\u63a2\u7d22\u66f4\u8fd1\u4e00\u6b65\u3002<\/span><\/p>\n

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\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u67e5\u770b\u4e0a\u4e00\u671f\u8bfb\u4e66\u4f1a\u7b14\u8bb0\u3002<\/span><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
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\u59cb\u53d1\u4e8e\u5fae\u4fe1\u516c\u4f17\u53f7\uff1a \u96c6\u667a\u4ff1\u4e50\u90e8 <\/p>\n<\/blockquote>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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