{"id":1069443,"date":"2022-04-26T21:00:00","date_gmt":"2022-04-27T04:00:00","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/?post_type=msr-blog-post&#038;p=1069443"},"modified":"2024-09-25T01:27:03","modified_gmt":"2024-09-25T08:27:03","slug":"iclr-2022","status":"publish","type":"msr-blog-post","link":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/articles\/iclr-2022\/","title":{"rendered":"ICLR 2022 | \u5fae\u8f6f\u4e9a\u6d32\u7814\u7a76\u9662\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u6700\u65b0\u7814\u7a76\u6210\u679c\u4e00\u89c8"},"content":{"rendered":"\n<p>\u7f16\u8005\u6309\uff1aICLR\uff08International Conference on Learning Representations\uff09\u662f\u56fd\u9645\u516c\u8ba4\u7684\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u9876\u7ea7\u4f1a\u8bae\u4e4b\u4e00\uff0c\u4f17\u591a\u5728\u4eba\u5de5\u667a\u80fd\u3001\u7edf\u8ba1\u548c\u6570\u636e\u79d1\u5b66\u9886\u57df\u4ee5\u53ca\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u8bed\u97f3\u8bc6\u522b\u3001\u6587\u672c\u7406\u89e3\u7b49\u91cd\u8981\u5e94\u7528\u9886\u57df\u6781\u5176\u6709\u5f71\u54cd\u529b\u7684\u8bba\u6587\u90fd\u53d1\u8868\u5728\u8be5\u5927\u4f1a\u4e0a\u3002\u4eca\u5e74\u7684 ICLR \u5927\u4f1a\u4e8e4\u670825\u65e5\u81f329\u65e5\u5728\u7ebf\u4e0a\u4e3e\u529e\u3002\u672c\u5c4a\u5927\u4f1a\u5171\u63a5\u6536\u8bba\u65871095\u7bc7\uff0c\u8bba\u6587\u63a5\u6536\u738732.3%\u3002\u4eca\u5929\uff0c\u6211\u4eec\u7cbe\u9009\u4e86\u5176\u4e2d\u7684\u516d\u7bc7\u6765\u4e3a\u5927\u5bb6\u8fdb\u884c\u7b80\u8981\u4ecb\u7ecd\uff0c\u5176\u4e2d\u7814\u7a76\u4e3b\u9898\u7684\u5173\u952e\u8bcd\u5305\u62ec\u65f6\u95f4\u5e8f\u5217\u3001\u7b56\u7565\u4f18\u5316\u3001\u89e3\u8026\u8868\u793a\u5b66\u4e60\u3001\u91c7\u6837\u65b9\u6cd5\u3001\u5f3a\u5316\u5b66\u4e60\u7b49\u3002\u6b22\u8fce\u611f\u5174\u8da3\u7684\u8bfb\u8005\u9605\u8bfb\u8bba\u6587\u539f\u6587\uff0c\u4e00\u8d77\u4e86\u89e3\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u7684\u524d\u6cbf\u8fdb\u5c55\uff01<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"\u5468\u671f\u6027\u65f6\u95f4\u5e8f\u5217\u7684\u6df1\u5ea6\u5c55\u5f00\u5b66\u4e60\">\u5468\u671f\u6027\u65f6\u95f4\u5e8f\u5217\u7684\u6df1\u5ea6\u5c55\u5f00\u5b66\u4e60<\/h3>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"210\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-1-1024x210.png\" alt=\"paper screenshot\" class=\"wp-image-1069452\" style=\"width:748px;height:auto\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-1-1024x210.png 1024w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-1-300x62.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-1-768x158.png 768w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-1-1536x315.png 1536w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-1-240x49.png 240w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-1.png 1802w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/depts-deep-expansion-learning-for-periodic-time-series-forecasting\/<\/p>\n\n\n\n<p>\u5468\u671f\u6027\u65f6\u95f4\u5e8f\u5217\u5728\u7535\u529b\u3001\u4ea4\u901a\u3001\u73af\u5883\u3001\u533b\u7597\u7b49\u9886\u57df\u4e2d\u666e\u904d\u5b58\u5728\uff0c\u4f46\u662f\u51c6\u786e\u5730\u6355\u6349\u8fd9\u4e9b\u65f6\u5e8f\u4fe1\u53f7\u7684\u6f14\u5316\u89c4\u5f8b\u5374\u5f88\u56f0\u96be\u3002\u4e00\u65b9\u9762\u662f\u56e0\u4e3a\u89c2\u6d4b\u5230\u7684\u65f6\u5e8f\u4fe1\u53f7\u5f80\u5f80\u5bf9\u9690\u5f0f\u7684\u5468\u671f\u89c4\u5f8b\u6709\u7740\u5404\u79cd\u5404\u6837\u590d\u6742\u7684\u4f9d\u8d56\u5173\u7cfb\uff0c\u53e6\u4e00\u65b9\u9762\u662f\u7531\u4e8e\u8fd9\u4e9b\u9690\u5f0f\u7684\u5468\u671f\u89c4\u5f8b\u901a\u5e38\u4e5f\u7531\u4e0d\u540c\u9891\u7387\u3001\u5e45\u5ea6\u7684\u5468\u671f\u6a21\u5f0f\u590d\u5408\u800c\u6210\u3002\u7136\u800c\uff0c\u73b0\u6709\u7684\u6df1\u5ea6\u65f6\u95f4\u5e8f\u5217\u9884\u6d4b\u6a21\u578b\u8981\u4e48\u5ffd\u89c6\u4e86\u5bf9\u5468\u671f\u6027\u7684\u5efa\u6a21\uff0c\u8981\u4e48\u4f9d\u8d56\u4e00\u4e9b\u7b80\u5355\u7684\u5047\u8bbe\uff08\u52a0\u6027\u5468\u671f\u3001\u4e58\u6027\u5468\u671f\u7b49\uff09\uff0c\u4ece\u800c\u5bfc\u81f4\u5728\u76f8\u5e94\u9884\u6d4b\u4efb\u52a1\u4e2d\u7684\u8868\u73b0\u4e0d\u5982\u4eba\u610f\u3002<\/p>\n\n\n\n<p>\u5728\u6df1\u5165\u601d\u8003\u8fd9\u4e9b\u7814\u7a76\u96be\u70b9\u540e\uff0c\u5fae\u8f6f\u4e9a\u6d32\u7814\u7a76\u9662\u7684\u7814\u7a76\u5458\u4eec\u4e3a\u5468\u671f\u6027\u65f6\u95f4\u5e8f\u5217\u7684\u9884\u6d4b\u95ee\u9898\u63d0\u51fa\u4e86\u4e00\u5957\u65b0\u578b\u7684\u6df1\u5ea6\u5c55\u5f00\u5b66\u4e60\u6846\u67b6 DEPTS\u3002\u8be5\u6846\u67b6\u65e2\u53ef\u4ee5\u523b\u753b\u591a\u6837\u5316\u7684\u5468\u671f\u6027\u6210\u5206\uff0c\u4e5f\u80fd\u6355\u6349\u590d\u6742\u7684\u5468\u671f\u6027\u4f9d\u8d56\u5173\u7cfb\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"307\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-2-1024x307.png\" alt=\"\u56fe1\uff1aDEPTS \u6846\u67b6\u56fe\" class=\"wp-image-1069455\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-2-1024x307.png 1024w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-2-300x90.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-2-768x230.png 768w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-2-1536x460.png 1536w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-2-2048x613.png 2048w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-2-240x72.png 240w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>\u56fe1\uff1aDEPTS \u6846\u67b6\u56fe<\/em><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>\u5982\u56fe1\u6240\u793a\uff0cDEPTS \u4e3b\u8981\u5305\u542b\u4e24\u5927\u6a21\u5757\uff1a\u5468\u671f\u6a21\u5757\uff08The Periodicity Module\uff09\u548c\u5c55\u5f00\u6a21\u5757\uff08The Expansion Module\uff09\u3002\u9996\u5148\uff0c\u5468\u671f\u6a21\u5757\u8d1f\u8d23\u5bf9\u6574\u6761\u65f6\u95f4\u5e8f\u5217\u7684\u5168\u5c40\u5468\u671f\u8fdb\u884c\u5efa\u6a21\uff0c\u63a5\u53d7\u5168\u5c40\u65f6\u95f4\u4f5c\u4e3a\u8f93\u5165\uff0c\u63a8\u65ad\u9690\u5f0f\u7684\u5468\u671f\u72b6\u6001\u4f5c\u4e3a\u8f93\u51fa\u3002\u4e3a\u4e86\u6709\u6548\u523b\u753b\u591a\u79cd\u4e0d\u540c\u6a21\u5f0f\u7684\u590d\u5408\u5468\u671f\uff0c\u8fd9\u91cc\u4f7f\u7528\u4e86\u4e00\u7ec4\u53c2\u6570\u5316\u7684\u5468\u671f\u51fd\u6570\uff08\u5982\u4f59\u5f26\u7ea7\u6570\uff09\u6765\u6784\u5efa\u5468\u671f\u6a21\u5757\u5e76\u4f7f\u7528\u76f8\u5e94\u53d8\u6362\uff08\u5982\u79bb\u6563\u4f59\u5f26\u53d8\u6362\uff09\u6765\u8fdb\u884c\u9ad8\u6548\u7684\u53c2\u6570\u521d\u59cb\u5316\u3002<\/p>\n\n\n\n<p>\u7136\u540e\uff0c\u57fa\u4e8e\u4e00\u6bb5\u89c2\u6d4b\u7684\u65f6\u95f4\u5e8f\u5217\u4fe1\u53f7\u53ca\u5176\u76f8\u5e94\u7684\u9690\u5f0f\u5468\u671f\u72b6\u6001\uff0c\u5c55\u5f00\u6a21\u5757\u8d1f\u8d23\u6355\u6349\u89c2\u6d4b\u4fe1\u53f7\u4e0e\u9690\u5f0f\u5468\u671f\u4e4b\u95f4\u590d\u6742\u7684\u4f9d\u8d56\u5173\u7cfb\u5e76\u505a\u51fa\u9884\u6d4b\u3002\u5728\u8fd9\u91cc\uff0c\u7814\u7a76\u5458\u4eec\u62d3\u5c55\u4e86\u7ecf\u5178\u7684\u6df1\u5ea6\u6b8b\u5dee\u5b66\u4e60\u601d\u60f3\u5f00\u53d1\u4e86\u4e00\u79cd\u6df1\u5ea6\u5c55\u5f00\u5b66\u4e60\u67b6\u6784\u3002\u5728\u8fd9\u4e2a\u67b6\u6784\u4e2d\uff0c\u7814\u7a76\u5458\u4eec\u4f1a\u5bf9\u8f93\u5165\u7684\u65f6\u95f4\u5e8f\u5217\u53ca\u5176\u9690\u5f0f\u5468\u671f\u505a\u9010\u5c42\u7684\u4f9d\u8d56\u5173\u7cfb\u5c55\u5f00\u5e76\u5f97\u51fa\u76f8\u5e94\u9884\u6d4b\u5206\u91cf\u3002\u5728\u6bcf\u4e00\u5c42\u4e2d\uff0c\u7531\u53c2\u6570\u5316\u7684\u5468\u671f\u795e\u7ecf\u7f51\u7edc\u6765\u51b3\u5b9a\u672c\u5c42\u805a\u7126\u7684\u5468\u671f\u5206\u91cf\uff0c\u5e76\u5c55\u5f00\u89c2\u6d4b\u4fe1\u53f7\u7684\u56de\u770b\u548c\u9884\u6d4b\u5206\u91cf\u3002\u5728\u8fdb\u5165\u4e0b\u4e00\u5c42\u524d\uff0c\u7814\u7a76\u5458\u4eec\u4f1a\u51cf\u53bb\u672c\u5c42\u4e2d\u4ea7\u751f\u7684\u5468\u671f\u5206\u91cf\u548c\u56de\u770b\u5206\u91cf\uff0c\u4ece\u800c\u9f13\u52b1\u540e\u7eed\u7684\u795e\u7ecf\u7f51\u7edc\u5c42\u805a\u7126\u4e8e\u5c1a\u672a\u5c55\u5f00\u7684\u5468\u671f\u6027\u4f9d\u8d56\u3002\u6309\u7167\u8fd9\u6837\u7684\u6a21\u5f0f\u5806\u53e0 N \u5c42\u5c31\u6784\u6210\u4e86\uff08\u6df1\u5ea6\uff09\u5c55\u5f00\u6a21\u5757\u3002<\/p>\n\n\n\n<p>\u7814\u7a76\u5458\u4eec\u5728\u751f\u6210\u6570\u636e\u548c\u5e7f\u6cdb\u7684\u771f\u5b9e\u6570\u636e\u4e0a\u90fd\u8fdb\u884c\u4e86\u5b9e\u9a8c\u9a8c\u8bc1\uff0c\u660e\u786e\u5730\u63ed\u793a\u4e86\u73b0\u6709\u65b9\u6cd5\u5728\u5468\u671f\u6027\u65f6\u95f4\u5e8f\u5217\u9884\u6d4b\u65b9\u9762\u7684\u77ed\u677f\uff0c\u5e76\u6709\u529b\u5730\u8bc1\u5b9e\u4e86 DEPTS \u6846\u67b6\u7684\u4f18\u8d8a\u6027\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u5728\u4e00\u4e9b\u5468\u671f\u6a21\u5f0f\u5f88\u5f3a\u7684\u6570\u636e\u4e0a\uff0cDEPTS 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src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-3.jpg\" alt=\"paper screenshot\" class=\"wp-image-1069458\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-3.jpg 540w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-3-300x101.jpg 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-3-240x80.jpg 240w\" sizes=\"auto, (max-width: 540px) 100vw, 540px\" \/><\/figure>\n\n\n\n<p>\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/gradient-information-matters-in-policy-optimization-by-back-propagating-through-model\/<\/p>\n\n\n\n<p>\u57fa\u4e8e\u6a21\u578b\u7684\u5f3a\u5316\u5b66\u4e60\u65b9\u6cd5\u63d0\u4f9b\u4e86\u4e00\u79cd\u901a\u8fc7\u4e0e\u5b66\u5230\u7684\u73af\u5883\u8fdb\u884c\u4ea4\u4e92\u4ece\u800c\u83b7\u5f97\u6700\u4f18\u7b56\u7565\u7684\u9ad8\u6548\u673a\u5236\u3002\u5728\u8fd9\u7bc7\u8bba\u6587\u4e2d\uff0c\u7814\u7a76\u5458\u4eec\u7814\u7a76\u4e86\u5176\u4e2d\u6a21\u578b\u5b66\u4e60\u4e0e\u6a21\u578b\u4f7f\u7528\u4e0d\u5339\u914d\u7684\u95ee\u9898\u3002\u5177\u4f53\u6765\u8bf4\uff0c\u4e3a\u4e86\u83b7\u5f97\u5f53\u524d\u7b56\u7565\u7684\u66f4\u65b0\u65b9\u5411\uff0c\u4e00\u4e2a\u6709\u6548\u7684\u65b9\u6cd5\u5c31\u662f\u5229\u7528\u6a21\u578b\u7684\u53ef\u5fae\u6027\u53bb\u8ba1\u7b97\u6a21\u578b\u7684\u5bfc\u6570\u3002 \u7136\u800c\uff0c\u73b0\u5728\u5e38\u7528\u7684\u65b9\u6cd5\u90fd\u53ea\u662f\u7b80\u5355\u5730\u5c06\u6a21\u578b\u7684\u5b66\u4e60\u770b\u6210\u662f\u4e00\u4e2a\u76d1\u7763\u5b66\u4e60\u7684\u4efb\u52a1\uff0c\u5229\u7528\u6a21\u578b\u7684\u9884\u6d4b\u8bef\u5dee\u53bb\u6307\u5bfc\u6a21\u578b\u7684\u5b66\u4e60\uff0c\u4f46\u662f\u5ffd\u7565\u4e86\u6a21\u578b\u7684\u68af\u5ea6\u8bef\u5dee\u3002\u7b80\u800c\u8a00\u4e4b\uff0c\u57fa\u4e8e\u6a21\u578b\u7684\u5f3a\u5316\u5b66\u4e60\u7b97\u6cd5\u5f80\u5f80\u9700\u8981\u51c6\u786e\u7684\u6a21\u578b\u68af\u5ea6\uff0c\u4f46\u662f\u5728\u5b66\u4e60\u9636\u6bb5\u53ea\u51cf\u5c0f\u4e86\u9884\u6d4b\u8bef\u5dee\uff0c\u56e0\u6b64\u5c31\u5b58\u5728\u76ee\u6807\u4e0d\u4e00\u81f4\u7684\u95ee\u9898\u3002<\/p>\n\n\n\n<p>\u672c\u7bc7\u8bba\u6587\u4e2d\uff0c\u7814\u7a76\u5458\u4eec\u9996\u5148\u5728\u7406\u8bba\u4e0a\u8bc1\u660e\u4e86\u6a21\u578b\u7684\u68af\u5ea6\u8bef\u5dee\u5bf9\u4e8e\u7b56\u7565\u4f18\u5316\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002\u7531\u4e8e\u7b56\u7565\u68af\u5ea6\u7684\u504f\u5dee\u4e0d\u4ec5\u53d7\u5230\u6a21\u578b\u9884\u6d4b\u8bef\u5dee\u7684\u5f71\u54cd\u800c\u4e14\u4e5f\u53d7\u5230\u6a21\u578b\u68af\u5ea6\u8bef\u5dee\u7684\u5f71\u54cd\uff0c\u56e0\u6b64\u8fd9\u4e9b\u8bef\u5dee\u4f1a\u6700\u7ec8\u5f71\u54cd\u5230\u7b56\u7565\u4f18\u5316\u8fc7\u7a0b\u7684\u6536\u655b\u901f\u7387\u3002<\/p>\n\n\n\n<p>\u63a5\u4e0b\u6765\uff0c\u8bba\u6587\u63d0\u51fa\u4e86\u4e00\u4e2a\u53cc\u6a21\u578b\u7684\u65b9\u6cd5\u53bb\u540c\u65f6\u63a7\u5236\u6a21\u578b\u7684\u9884\u6d4b\u548c\u68af\u5ea6\u8bef\u5dee\u3002\u7814\u7a76\u5458\u4eec\u8bbe\u8ba1\u4e86\u4e24\u4e2a\u4e0d\u540c\u7684\u6a21\u578b\uff0c\u5e76\u4e14\u5728\u6a21\u578b\u7684\u5b66\u4e60\u548c\u4f7f\u7528\u9636\u6bb5\u5206\u522b\u8ba9\u8fd9\u4e24\u4e2a\u6a21\u578b\u627f\u62c5\u4e86\u4e0d\u540c\u7684\u89d2\u8272\u3002\u5728\u6a21\u578b\u5b66\u4e60\u9636\u6bb5\uff0c\u7814\u7a76\u5458\u4eec\u8bbe\u8ba1\u4e86\u4e00\u4e2a\u53ef\u884c\u7684\u65b9\u6cd5\u53bb\u8ba1\u7b97\u68af\u5ea6\u8bef\u5dee\u5e76\u4e14\u7528\u5176\u53bb\u6307\u5bfc\u68af\u5ea6\u6a21\u578b\u7684\u5b66\u4e60\u3002\u5728\u6a21\u578b\u4f7f\u7528\u9636\u6bb5\uff0c\u7814\u7a76\u5458\u4eec\u5148\u5229\u7528\u9884\u6d4b\u6a21\u578b\u53bb\u83b7\u5f97\u9884\u6d4b\u8f68\u8ff9\uff0c\u518d\u5229\u7528\u68af\u5ea6\u6a21\u578b\u53bb\u8ba1\u7b97\u6a21\u578b\u68af\u5ea6\u3002\u7ed3\u5408\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u672c\u7bc7\u8bba\u6587\u63d0\u51fa\u4e86\u57fa\u4e8e\u65b9\u5411\u5bfc\u6570\u6295\u5f71\u7684\u7b56\u7565\u4f18\u5316\u7b97\u6cd5\uff08DDPPO\uff09\u3002 \u6700\u540e\uff0c\u5728\u4e00\u7cfb\u5217\u8fde\u7eed\u63a7\u5236\u57fa\u51c6\u4efb\u52a1\u4e0a\u7684\u5b9e\u9a8c\u7ed3\u679c\u8bc1\u660e\u4e86\u8bba\u6587\u4e2d\u63d0\u51fa\u7684\u7b97\u6cd5\u786e\u5b9e\u6709\u7740\u66f4\u9ad8\u7684\u6837\u672c\u6548\u7387\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"204\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-4-1024x204.png\" alt=\"\u56fe2\uff1a (a)\u6a21\u578b\u5b66\u4e60\u548c\u4f7f\u7528\u4e2d\u7684\u4e0d\u4e00\u81f4\u3002 (b)DDPPO \u7b97\u6cd5\u7684\u793a\u610f\u56fe\u3002DDPPO \u7b97\u6cd5\u5206\u522b\u6784\u9020\u4e86\u9884\u6d4b\u6a21\u578b\u548c\u68af\u5ea6\u6a21\u578b\u3002DDPPO \u7b97\u6cd5\u4f7f\u7528\u4e0d\u540c\u7684\u635f\u5931\u51fd\u6570\u53bb\u5206\u522b\u8bad\u7ec3\u8fd9\u4e24\u4e2a\u6a21\u578b\uff0c\u5e76\u4e14\u5728\u7b56\u7565\u4f18\u5316\u4e2d\u5206\u522b\u6070\u5f53\u5730\u4f7f\u7528\u4ed6\u4eec\u3002\" class=\"wp-image-1069461\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-4-1024x204.png 1024w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-4-300x60.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-4-768x153.png 768w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-4-240x48.png 240w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-4.png 1466w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>\u56fe2\uff1a (a)\u6a21\u578b\u5b66\u4e60\u548c\u4f7f\u7528\u4e2d\u7684\u4e0d\u4e00\u81f4\u3002 (b)DDPPO \u7b97\u6cd5\u7684\u793a\u610f\u56fe\u3002DDPPO \u7b97\u6cd5\u5206\u522b\u6784\u9020\u4e86\u9884\u6d4b\u6a21\u578b\u548c\u68af\u5ea6\u6a21\u578b\u3002DDPPO \u7b97\u6cd5\u4f7f\u7528\u4e0d\u540c\u7684\u635f\u5931\u51fd\u6570\u53bb\u5206\u522b\u8bad\u7ec3\u8fd9\u4e24\u4e2a\u6a21\u578b\uff0c\u5e76\u4e14\u5728\u7b56\u7565\u4f18\u5316\u4e2d\u5206\u522b\u6070\u5f53\u5730\u4f7f\u7528\u4ed6\u4eec\u3002<\/em><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"recurd\u9012\u5f52\u89e3\u8026\u7f51\u7edc\">RecurD\u9012\u5f52\u89e3\u8026\u7f51\u7edc<\/h3>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"550\" height=\"250\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-5.jpg\" alt=\"paper screenshot\" class=\"wp-image-1069464\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-5.jpg 550w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-5-300x136.jpg 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-5-240x109.jpg 240w\" sizes=\"auto, (max-width: 550px) 100vw, 550px\" \/><\/figure>\n\n\n\n<p>\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/recursive-disentanglement-network\/<\/p>\n\n\n\n<p>\u673a\u5668\u5b66\u4e60\u7684\u6700\u65b0\u8fdb\u5c55\u8868\u660e\uff0c\u89e3\u8026\u8868\u793a\u7684\u5b66\u4e60\u80fd\u529b\u6709\u5229\u4e8e\u6a21\u578b\u5b9e\u73b0\u9ad8\u6548\u7684\u6570\u636e\u5229\u7528\u3002\u5176\u4e2d BETA-VAE \u53ca\u5176\u53d8\u4f53\u662f\u89e3\u8026\u8868\u793a\u5b66\u4e60\u4e2d\u5e94\u7528\u6700\u4e3a\u5e7f\u6cdb\u7684\u4e00\u7c7b\u65b9\u6cd5\u3002\u8fd9\u7c7b\u5de5\u4f5c\u5f15\u5165\u4e86\u591a\u79cd\u4e0d\u540c\u7684\u5f52\u7eb3\u504f\u5dee\u4f5c\u4e3a\u6b63\u5219\u5316\u9879\uff0c\u5e76\u5c06\u5b83\u4eec\u76f4\u63a5\u5e94\u7528\u4e8e\u9690\u53d8\u91cf\u7a7a\u95f4\uff0c\u65e8\u5728\u5e73\u8861\u89e3\u8026\u8868\u793a\u7684\u4fe1\u606f\u91cf\u53ca\u5176\u72ec\u7acb\u6027\u7ea6\u675f\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u7136\u800c\uff0c\u6df1\u5ea6\u6a21\u578b\u7684\u7279\u5f81\u7a7a\u95f4\u5177\u6709\u5929\u7136\u7684\u7ec4\u5408\u7ed3\u6784\uff0c\u5373\u6bcf\u4e2a\u590d\u6742\u7279\u5f81\u90fd\u662f\u539f\u59cb\u7279\u5f81\u7684\u7ec4\u5408\u3002\u4ec5\u5c06\u89e3\u8026\u6b63\u5219\u5316\u9879\u5e94\u7528\u4e8e\u9690\u53d8\u91cf\u7a7a\u95f4\u65e0\u6cd5\u6709\u6548\u5730\u5728\u7ec4\u5408\u7279\u5f81\u7a7a\u95f4\u4e2d\u4f20\u64ad\u89e3\u8026\u8868\u793a\u7684\u7ea6\u675f\u3002<\/p>\n\n\n\n<p>\u672c\u7bc7\u8bba\u6587\u65e8\u5728\u7ed3\u5408\u7ec4\u5408\u7279\u5f81\u7a7a\u95f4\u7684\u7279\u70b9\u6765\u89e3\u51b3\u89e3\u8026\u8868\u793a\u5b66\u4e60\u95ee\u9898\u3002\u9996\u5148\uff0c\u8bba\u6587\u4ece\u4fe1\u606f\u8bba\u7684\u89d2\u5ea6\u5b9a\u4e49\u4e86\u89e3\u8026\u8868\u793a\u7684\u5c5e\u6027\uff0c\u4ece\u800c\u5f15\u5165\u4e86\u4e00\u4e2a\u65b0\u7684\u5b66\u4e60\u76ee\u6807\uff0c\u5305\u62ec\u4e09\u4e2a\u57fa\u672c\u5c5e\u6027\uff1a\u5145\u5206\u6027\u3001\u6700\u5c0f\u5145\u5206\u6027\u548c\u89e3\u8026\u6027\u3002\u4ece\u7406\u8bba\u5206\u6790\u8868\u660e\uff0c\u672c\u7bc7\u8bba\u6587\u6240\u63d0\u51fa\u7684\u5b66\u4e60\u76ee\u6807\u662f BETA-VAE \u53ca\u5176\u51e0\u4e2a\u53d8\u79cd\u7684\u4e00\u822c\u5f62\u5f0f\u3002\u63a5\u4e0b\u6765\uff0c\u7814\u7a76\u5458\u4eec\u5c06\u6240\u63d0\u51fa\u7684\u5b66\u4e60\u76ee\u6807\u6269\u5c55\u5230\u4e86\u7ec4\u5408\u7279\u5f81\u7a7a\u95f4\uff0c\u4ee5\u6db5\u76d6\u7ec4\u5408\u7279\u5f81\u7a7a\u95f4\u4e2d\u7684\u89e3\u7f20\u7ed3\u8868\u793a\u5b66\u4e60\u95ee\u9898\uff0c\u5305\u62ec\u7ec4\u5408\u6700\u5c0f\u5145\u5206\u6027\u548c\u7ec4\u5408\u89e3\u8026\u6027\u3002<\/p>\n\n\n\n<p>\u57fa\u4e8e\u7ec4\u5408\u89e3\u8026\u5b66\u4e60\u76ee\u6807\uff0c\u672c\u7bc7\u8bba\u6587\u63d0\u51fa\u4e86\u5bf9\u5e94\u7684\u9012\u5f52\u89e3\u7f20\u7ed3\u7f51\u7edc\uff08Recursive disentanglement network, RecurD\uff09\uff0c\u5728\u6a21\u578b\u7f51\u7edc\u4e2d\u7684\u7ec4\u5408\u7279\u5f81\u7a7a\u95f4\u5185\uff0c\u9012\u5f52\u5730\u4f20\u64ad\u89e3\u8026\u5f52\u7eb3\u504f\u7f6e\u6765\u6307\u5bfc\u89e3\u7f20\u7ed3\u5b66\u4e60\u8fc7\u7a0b\u3002\u901a\u8fc7\u524d\u9988\u7f51\u7edc\uff0c\u9012\u5f52\u7684\u4f20\u64ad\u5f3a\u5f52\u7eb3\u504f\u5dee\u662f\u89e3\u8026\u8868\u793a\u5b66\u4e60\u7684\u5145\u5206\u6761\u4ef6\u3002\u5b9e\u9a8c\u8868\u660e\uff0c\u76f8\u8f83\u4e8e BETA-VAE \u53ca\u5176\u53d8\u79cd\u6a21\u578b\uff0cRecurD \u5b9e\u73b0\u4e86\u66f4\u597d\u7684\u89e3\u8026\u8868\u793a\u5b66\u4e60\u3002\u5e76\u4e14\uff0c\u5728\u4e0b\u6e38\u5206\u7c7b\u4efb\u52a1\u4e2d\uff0cRecurD \u4e5f\u8868\u73b0\u51fa\u4e86\u4e00\u5b9a\u7684\u6709\u6548\u5229\u7528\u6570\u636e\u7684\u80fd\u529b\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"308\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-6-1024x308.png\" alt=\"\u56fe3\uff1aRecurD \u7f51\u7edc\u7ed3\u6784\" class=\"wp-image-1069467\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-6-1024x308.png 1024w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-6-300x90.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-6-768x231.png 768w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-6-240x72.png 240w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-6.png 1268w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>\u56fe3\uff1aRecurD \u7f51\u7edc\u7ed3\u6784<\/em><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"\u57fa\u4e8e\u955c\u50cf\u65af\u5766\u56e0\u7b97\u7b26\u7684\u91c7\u6837\u65b9\u6cd5\">\u57fa\u4e8e\u955c\u50cf\u65af\u5766\u56e0\u7b97\u7b26\u7684\u91c7\u6837\u65b9\u6cd5<\/h3>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"482\" height=\"98\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-7.png\" alt=\"paper screenshot\" class=\"wp-image-1069470\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-7.png 482w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-7-300x61.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-7-480x98.png 480w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-7-240x49.png 240w\" sizes=\"auto, (max-width: 482px) 100vw, 482px\" \/><\/figure>\n\n\n\n<p>\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/sampling-with-mirrored-stein-operators\/<\/p>\n\n\n\n<p>\u8d1d\u53f6\u65af\u63a8\u7406\uff08Bayesian inference\uff09\u7b49\u4e00\u4e9b\u673a\u5668\u5b66\u4e60\u53ca\u79d1\u5b66\u8ba1\u7b97\u95ee\u9898\u90fd\u53ef\u5f52\u7ed3\u4e3a\u7528\u4e00\u7ec4\u6837\u672c\u6765\u4ee3\u8868\u4e00\u4e2a\u53ea\u77e5\u9053\u672a\u5f52\u4e00\u5316\u5bc6\u5ea6\u51fd\u6570\u7684\u5206\u5e03\u3002\u4e0d\u540c\u4e8e\u7ecf\u5178\u7684\u9a6c\u5c14\u53ef\u592b\u94fe\u8499\u7279\u5361\u7f57\uff08Markov chain Monte Carlo\uff09\u65b9\u6cd5\uff0c\u8fd1\u5e74\u6765\u53d1\u5c55\u8d77\u6765\u7684\u65af\u5766\u56e0\u53d8\u5206\u68af\u5ea6\u4e0b\u964d\u65b9\u6cd5\uff08Stein variational gradient descent\uff0c\u7b80\u8bb0\u4e3a SVGD\uff09\u5177\u6709\u66f4\u597d\u7684\u6837\u672c\u9ad8\u6548\u6027\uff0c\u4f46\u5bf9\u5728\u53d7\u9650\u7a7a\u95f4\uff08\u56fe\u4e2d\u0398\uff09\u4e0a\u5206\u5e03\u7684\u91c7\u6837\u6216\u5bf9\u5f62\u72b6\u626d\u66f2\u7684\u5206\u5e03\u7684\u91c7\u6837\u4ecd\u663e\u5403\u529b\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"361\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-8-1024x361.png\" alt=\"\u56fe4\uff1a\u539f\u6837\u672c\u7a7a\u95f4\\Theta\u53ca\u5176\u955c\u50cf\u7a7a\u95f4\u793a\u610f\" class=\"wp-image-1069473\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-8-1024x361.png 1024w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-8-300x106.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-8-768x270.png 768w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-8-240x85.png 240w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-8.png 1474w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>\u56fe4\uff1a\u539f\u6837\u672c\u7a7a\u95f4\\Theta\u53ca\u5176\u955c\u50cf\u7a7a\u95f4\u793a\u610f<\/em><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>\u672c\u7bc7\u8bba\u6587\u4e2d\uff0c\u7814\u7a76\u5458\u4eec\u501f\u9274\u4f18\u5316\u9886\u57df\u4e2d\u955c\u50cf\u4e0b\u964d\u65b9\u6cd5\uff08mirrored descent\uff09\u7684\u601d\u60f3\uff0c\u63a8\u5bfc\u8bbe\u8ba1\u51fa\u4e86\u4e00\u7cfb\u5217\u955c\u50cf\u65af\u5766\u56e0\u7b97\u7b26\uff08mirrored Stein operators\uff09\u53ca\u5176\u5bf9\u5e94\u7684\u955c\u50cf SVGD \u65b9\u6cd5\u3002\u539f\u7a7a\u95f4\u7ecf\u955c\u50cf\u6620\u5c04\uff08\u56fe\u4e2d\u2207\u03c8\uff09\u6240\u5f97\u7684\u955c\u50cf\u7a7a\u95f4\u662f\u4e0d\u53d7\u9650\u7684\u5e76\u53ef\u4f53\u73b0\u5206\u5e03\u7684\u51e0\u4f55\u4fe1\u606f\uff0c\u56e0\u800c\u8fd9\u4e9b\u65b9\u6cd5\u7cfb\u7edf\u6027\u5730\u89e3\u51b3\u4e86\u4e0a\u8ff0\u95ee\u9898\u3002<\/p>\n\n\n\n<p>\u5177\u4f53\u6765\u8bf4\uff0cSVGD \u7684\u539f\u7406\u662f\u4f7f\u7528\u80fd\u6700\u5927\u5316\u6837\u672c\u5206\u5e03\u4e0e\u76ee\u6807\u5206\u5e03\u4e4b\u95f4 KL \u6563\u5ea6\u51cf\u5c0f\u7387\u7684\u66f4\u65b0\u65b9\u5411\u6765\u66f4\u65b0\u6837\u672c\uff0c\u4ece\u800c\u4f7f\u6837\u672c\u5206\u5e03\u4e0d\u65ad\u903c\u8fd1\u76ee\u6807\u5206\u5e03\uff0c\u800c\u8fd9\u4e2a\u51cf\u5c0f\u7387\u548c\u66f4\u65b0\u65b9\u5411\u90fd\u662f\u7531\u65af\u5766\u56e0\u7b97\u7b26\u7ed9\u51fa\u7684\u3002\u56e0\u800c\u8bba\u6587\u9996\u5148\u63a8\u5bfc\u51fa\u4e86\u955c\u50cf\u7a7a\u95f4\u4e2d\u7684\u65af\u5766\u56e0\u7b97\u7b26\uff08\u56fe\u4e2d M_(p,\u03c8)\uff09\u548c\u6837\u672c\u7684\u66f4\u65b0\u65b9\u5411\uff08\u56fe\u4e2d E_(\u03b8\u223cq_t ) [M_(p,\u03c8) K(\u03b8_t,\u03b8)]\uff09\u3002<\/p>\n\n\n\n<p>\u7814\u7a76\u5458\u4eec\u8fdb\u800c\u8bbe\u8ba1\u4e86\u4e09\u79cd\u8ba1\u7b97\u66f4\u65b0\u65b9\u5411\u6240\u9700\u7684\u6838\u51fd\u6570\uff08kernel function\uff0c\u56fe\u4e2d K\uff09\uff0c\u5206\u522b\u53ef\u5728\u5355\u6837\u672c\u60c5\u51b5\u4e0b\u5212\u5f52\u4e3a\u9488\u5bf9\u955c\u50cf\u7a7a\u95f4\u53ca\u539f\u7a7a\u95f4\u4e0a\u76ee\u6807\u5206\u5e03\u5cf0\u503c\u7684\u68af\u5ea6\u4e0b\u964d\uff0c\u4ee5\u53ca\u539f\u7a7a\u95f4\u4e0a\u7684\u81ea\u7136\u68af\u5ea6\u4e0b\u964d\u3002\u8be5\u8bba\u6587\u8fd8\u63a8\u5bfc\u4e86\u6240\u63d0\u65b9\u6cd5\u7684\u6536\u655b\u6027\u4fdd\u8bc1\u3002\u5b9e\u9a8c\u53d1\u73b0\u6240\u63d0\u65b9\u6cd5\u6bd4\u539f\u672c\u7684 SVGD \u6709\u66f4\u597d\u7684\u6536\u655b\u901f\u5ea6\u548c\u7cbe\u5ea6\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"\u90e8\u7f72\u9ad8\u6548\u7684\u5f3a\u5316\u5b66\u4e60-\u7406\u8bba\u4e0b\u754c\u4e0e\u6700\u4f18\u7b97\u6cd5\">\u90e8\u7f72\u9ad8\u6548\u7684\u5f3a\u5316\u5b66\u4e60\uff1a\u7406\u8bba\u4e0b\u754c\u4e0e\u6700\u4f18\u7b97\u6cd5<\/h3>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"601\" height=\"154\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-9.png\" alt=\"paper screenshot\" class=\"wp-image-1069476\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-9.png 601w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-9-300x77.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-9-240x61.png 240w\" sizes=\"auto, (max-width: 601px) 100vw, 601px\" \/><\/figure>\n\n\n\n<p>\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/towards-deployment-efficient-reinforcement-learning-lower-bound-and-optimality\/<\/p>\n\n\n\n<p>\u4f20\u7edf\u7684\uff08\u5728\u7ebf\uff09\u5f3a\u5316\u5b66\u4e60\uff08RL\uff09\u7684\u5b66\u4e60\u8fc7\u7a0b\u53ef\u4ee5\u6982\u62ec\u4e3a\u4e24\u90e8\u5206\u7684\u5faa\u73af\uff1a\u5176\u4e00\u662f\u6839\u636e\u6536\u96c6\u7684\u6570\u636e\u5b66\u4e60\u4e00\u4e2a\u7b56\u7565\uff08policy\uff09\uff1b\u5176\u4e8c\u662f\u5c06\u7b56\u7565\u90e8\u7f72\u5230\u73af\u5883\u4e2d\u8fdb\u884c\u4ea4\u4e92\uff0c\u83b7\u5f97\u65b0\u7684\u6570\u636e\u7528\u4e8e\u63a5\u4e0b\u6765\u7684\u5b66\u4e60\u3002\u5f3a\u5316\u5b66\u4e60\u7684\u76ee\u6807\u5c31\u662f\u5728\u8fd9\u6837\u7684\u5faa\u73af\u4e2d\u5b8c\u6210\u5bf9\u73af\u5883\u7684\u63a2\u7d22\uff0c\u63d0\u5347\u7b56\u7565\u76f4\u81f3\u6700\u4f18\u3002<\/p>\n\n\n\n<p>\u7136\u800c\u5728\u4e00\u4e9b\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u90e8\u7f72\u7b56\u7565\u7684\u8fc7\u7a0b\u4f1a\u5341\u5206\u7e41\u7410\uff0c\u800c\u76f8\u5bf9\u6765\u8bb2\uff0c\u5f53\u90e8\u7f72\u5b8c\u65b0\u7684\u7b56\u7565\u4e4b\u540e\uff0c\u6570\u636e\u7684\u6536\u96c6\u8fc7\u7a0b\u662f\u5f88\u5feb\u7684\u3002\u6bd4\u5982\u5728\u63a8\u8350\u7cfb\u7edf\u4e2d\uff0c\u7b56\u7565\u5c31\u662f\u63a8\u8350\u65b9\u6848\uff0c\u597d\u7684\u7b56\u7565\u53ef\u4ee5\u7cbe\u51c6\u5730\u63a8\u9001\u7528\u6237\u6240\u9700\u8981\u7684\u5185\u5bb9\u3002\u8003\u8651\u5230\u7528\u6237\u4f53\u9a8c\uff0c\u901a\u5e38\u4e00\u5bb6\u516c\u53f8\u5728\u4e0a\u7ebf\u65b0\u7684\u63a8\u8350\u7b56\u7565\u4e4b\u524d\u4f1a\u8fdb\u884c\u5f88\u957f\u65f6\u95f4\u7684\u5185\u90e8\u6d4b\u8bd5\u6765\u68c0\u9a8c\u6027\u80fd\uff0c\u7531\u4e8e\u5e9e\u5927\u7684\u7528\u6237\u57fa\u6570\uff0c\u5f80\u5f80\u90e8\u7f72\u4e4b\u540e\u77ed\u65f6\u95f4\u5185\u5c31\u53ef\u4ee5\u6536\u96c6\u5230\u6d77\u91cf\u7684\u7528\u6237\u53cd\u9988\u6570\u636e\u6765\u8fdb\u884c\u540e\u7eed\u7684\u7b56\u7565\u5b66\u4e60\u3002\u5728\u8fd9\u6837\u7684\u5e94\u7528\u4e2d\uff0c\u7814\u7a76\u5458\u4eec\u66f4\u503e\u5411\u4e8e\u9009\u62e9\u53ea\u9700\u8981\u5f88\u5c11\u90e8\u7f72\u6b21\u6570\uff08deployment complexity\uff09\u5c31\u80fd\u5b66\u5230\u597d\u7b56\u7565\u7684\u7b97\u6cd5\u3002<\/p>\n\n\n\n<p>\u4f46\u662f\u73b0\u6709\u7684\u5f3a\u5316\u5b66\u4e60\u7b97\u6cd5\u4ee5\u53ca\u7406\u8bba\u548c\u4e0a\u8ff0\u771f\u5b9e\u9700\u6c42\u4e4b\u95f4\u8fd8\u6709\u8ddd\u79bb\u3002\u5728\u8fd9\u7bc7\u8bba\u6587\u4e2d\uff0c\u7814\u7a76\u5458\u4eec\u5c1d\u8bd5\u53bb\u586b\u8865\u8fd9\u4e2a\u7a7a\u767d\u3002\u7814\u7a76\u5458\u4eec\u9996\u5148\u4ece\u7406\u8bba\u7684\u89d2\u5ea6\u4e0a\uff0c\u5bf9 deployment-efficient RL \u8fd9\u4e2a\u95ee\u9898\u63d0\u4f9b\u4e86\u4e00\u4e2a\u6bd4\u8f83\u4e25\u8c28\u7684\u5b9a\u4e49\u3002\u4e4b\u540e\u4ee5 episodic linear MDP \u4f5c\u4e3a\u4e00\u4e2a\u5177\u4f53\u7684\u8bbe\u5b9a\uff0c\u7814\u7a76\u5458\u4eec\u5206\u522b\u7814\u7a76\u4e86\u6700\u4f18\u7684\u7b97\u6cd5\u80fd\u8868\u73b0\u7684\u600e\u6837\uff08lower bound\uff09\uff0c\u4ee5\u53ca\u63d0\u51fa\u4e86\u53ef\u4ee5\u8fbe\u5230\u6700\u4f18\u7684\u90e8\u7f72\u590d\u6742\u5ea6\u7684\u7b97\u6cd5\u8bbe\u8ba1\u65b9\u6848\uff08optimality\uff09\u3002<\/p>\n\n\n\n<p>\u5176\u4e2d\uff0c\u5728 lower bound \u90e8\u5206\uff0c\u7814\u7a76\u5458\u4eec\u8d21\u732e\u4e86\u7406\u8bba\u4e0b\u754c\u7684\u6784\u9020\u4e0e\u76f8\u5173\u8bc1\u660e\uff1b\u5728 upper bound \u90e8\u5206\uff0c\u7814\u7a76\u5458\u4eec\u63d0\u51fa\u4e86\u201c\u9010\u5c42\u63a8\u8fdb\u201d\u7684\u63a2\u7d22\u7b56\u7565\uff08\u5982\u56fe5\u6240\u793a\uff09\uff0c\u5e76\u8d21\u732e\u4e86\u57fa\u4e8e\u534f\u65b9\u5dee\u77e9\u9635\u4f30\u8ba1\u7684\u65b0\u7684\u7b97\u6cd5\u6846\u67b6\uff0c\u4ee5\u53ca\u4e00\u4e9b\u6280\u672f\u5c42\u9762\u7684\u521b\u65b0\u3002\u7814\u7a76\u5458\u4eec\u7684\u7ed3\u8bba\u4e5f\u63ed\u793a\u4e86\u90e8\u7f72\u5e26\u6709\u968f\u673a\u6027\u7684\u7b56\u7565\u5bf9\u4e8e\u964d\u4f4e\u90e8\u7f72\u590d\u6742\u5ea6\u7684\u663e\u8457\u4f5c\u7528\uff0c\u8fd9\u4e00\u70b9\u5728\u4e4b\u524d\u7684\u5de5\u4f5c\u5f53\u4e2d\u5f80\u5f80\u88ab\u5ffd\u7565\u4e86\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"291\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-10-1024x291.gif\" alt=\"\u56fe5\uff1a\u201c\u9010\u5c42\u63a8\u8fdb\u201d\u7684\u63a2\u7d22\u7b56\u7565\uff08\u4ee53\u5c42\u7684\u79bb\u6563\u9a6c\u5c14\u79d1\u592b\u51b3\u7b56\u8fc7\u7a0b\u4e3a\u4f8b\uff09\" class=\"wp-image-1069479\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-10-1024x291.gif 1024w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-10-300x85.gif 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-10-768x218.gif 768w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-10-1536x437.gif 1536w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-10-240x68.gif 240w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>\u56fe5\uff1a\u201c\u9010\u5c42\u63a8\u8fdb\u201d\u7684\u63a2\u7d22\u7b56\u7565\uff08\u4ee53\u5c42\u7684\u79bb\u6563\u9a6c\u5c14\u79d1\u592b\u51b3\u7b56\u8fc7\u7a0b\u4e3a\u4f8b\uff09<\/em><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"\u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u53d8\u5206\u5148\u77e5\u5f15\u5bfc\">\u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u53d8\u5206\u5148\u77e5\u5f15\u5bfc<\/h3>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"537\" height=\"188\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-11.png\" alt=\"paper screenshot\" class=\"wp-image-1069482\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-11.png 537w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-11-300x105.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-11-240x84.png 240w\" sizes=\"auto, (max-width: 537px) 100vw, 537px\" \/><\/figure>\n\n\n\n<p>\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/variational-oracle-guiding-for-reinforcement-learning\/<\/p>\n\n\n\n<p>GitHub\u94fe\u63a5\uff1ahttps:\/\/github.com\/Agony5757\/mahjong<\/p>\n\n\n\n<p>\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\uff08DRL\uff09\u6700\u8fd1\u5728\u5404\u79cd\u51b3\u7b56\u95ee\u9898\u4e0a\u90fd\u53d6\u5f97\u4e86\u6210\u529f\uff0c\u7136\u800c\u6709\u4e00\u4e2a\u91cd\u8981\u7684\u65b9\u9762\u8fd8\u6ca1\u6709\u88ab\u5145\u5206\u63a2\u7d22\u2014\u2014\u5982\u4f55\u5229\u7528 oracle observation\uff08\u51b3\u7b56\u65f6\u4e0d\u53ef\u89c1\uff0c\u4f46\u4e8b\u540e\u53ef\u77e5\u7684\u4fe1\u606f\uff09\u6765\u5e2e\u52a9\u8bad\u7ec3\u3002\u4f8b\u5982\uff0c\u4eba\u7c7b\u6251\u514b\u9ad8\u624b\u4f1a\u5728\u8d5b\u540e\u67e5\u770b\u6bd4\u8d5b\u7684\u56de\u653e\uff0c\u5728\u56de\u653e\u4e2d\uff0c\u4ed6\u4eec\u53ef\u4ee5\u5206\u6790\u5bf9\u624b\u7684\u624b\u724c\uff0c\u4ece\u800c\u5e2e\u52a9\u4ed6\u4eec\u66f4\u597d\u5730\u53cd\u601d\u6bd4\u8d5b\u4e2d\u81ea\u5df1\u6839\u636e\u53ef\u89c1\u4fe1\u606f\uff08executor observation\uff09\u6765\u505a\u7684\u51b3\u7b56\u662f\u5426\u53ef\u4ee5\u6539\u8fdb\u3002\u8fd9\u6837\u7684\u95ee\u9898\u88ab\u79f0\u4e3a oracle guiding\u3002<\/p>\n\n\n\n<p>\u5728\u8fd9\u9879\u5de5\u4f5c\u4e2d\uff0c\u7814\u7a76\u5458\u4eec\u57fa\u4e8e\u8d1d\u53f6\u65af\u7406\u8bba\u5bf9 oracle guiding \u7684\u95ee\u9898\u8fdb\u884c\u4e86\u7814\u7a76\u3002\u672c\u7bc7\u8bba\u6587\u63d0\u51fa\u4e86\u4e00\u79cd\u65b0\u7684\u57fa\u4e8e\u53d8\u5206\u8d1d\u53f6\u65af\u65b9\u6cd5\uff08variational Bayes\uff09\u7684\u5f3a\u5316\u5b66\u4e60\u7684\u76ee\u6807\u51fd\u6570\uff0c\u6765\u5229\u7528 oracle observation \u5e2e\u52a9\u8bad\u7ec3\u3002\u8fd9\u9879\u5de5\u4f5c\u7684\u4e3b\u8981\u8d21\u732e\u662f\u63d0\u51fa\u4e86\u4e00\u4e2a\u901a\u7528\u7684\u5f3a\u5316\u5b66\u4e60\u6846\u67b6\uff0c\u79f0\u4e3a Variational Latent Oracle Guiding (VLOG)\u3002VLOG \u5177\u6709\u8bb8\u591a\u4f18\u5f02\u7684\u6027\u8d28\uff0c\u6bd4\u5982\u5728\u5404\u79cd\u4efb\u52a1\u4e0a\u90fd\u6709\u7740\u826f\u597d\u4e14\u9c81\u68d2\u7684\u8868\u73b0\uff0c\u800c\u4e14 VLOG \u53ef\u4ee5\u4e0e\u4efb\u4f55 value-based \u7684 DRL \u7b97\u6cd5\u76f8\u7ed3\u5408\u4f7f\u7528\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"545\" src=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-12-1024x545.png\" alt=\"\u56fe6\uff1aVLOG \u5728\u8bad\u7ec3\u65f6\u548c\u4f7f\u7528\u65f6\u7684\u6a21\u578b\u56fe\u8868\uff08\u4ee5 Q-learning \u4e3a\u4f8b\uff09\u3002\u5de6\uff1a\u8bad\u7ec3\u65f6\uff08\u77e5\u9053 oracle observation\uff09\uff0c\u5206\u522b\u7528 executor observation \u548c oracle observation \u6765\u4f30\u8ba1\u4e00\u4e2a\u8d1d\u53f6\u65af\u9690\u53d8\u91cfz\u7684\u5148\u9a8c\uff08prior\uff09\u548c\u540e\u9a8c\uff08posterior\uff09\u5206\u5e03\u3002\u901a\u8fc7\u4f18\u5316 VLOG \u53d8\u5206\u4e0b\u754c\uff08variational lower bound\uff0c\u540e\u9a8c\u6a21\u578b\u7684\u5f3a\u5316\u5b66\u4e60\u76ee\u6807\u51fd\u6570\u51cf\u53bbz\u7684\u540e\u9a8c\u548c\u5148\u9a8c\u5206\u5e03\u4e4b\u95f4\u7684KL\u6563\u5ea6\uff09\u6765\u8bad\u7ec3\u6574\u4e2a\u6a21\u578b\u3002\u53f3\uff1a\u4f7f\u7528\u65f6\uff0c\u57fa\u4e8e\u53ef\u89c1\u4fe1\u606f\u6765\u505a\u51fa\u51b3\u7b56\u3002\" class=\"wp-image-1069485\" srcset=\"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-12-1024x545.png 1024w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-12-300x160.png 300w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-12-768x409.png 768w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-12-240x128.png 240w, https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-content\/uploads\/2024\/08\/iclr-2022-12.png 1338w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>\u56fe6\uff1aVLOG \u5728\u8bad\u7ec3\u65f6\u548c\u4f7f\u7528\u65f6\u7684\u6a21\u578b\u56fe\u8868\uff08\u4ee5 Q-learning \u4e3a\u4f8b\uff09\u3002\u5de6\uff1a\u8bad\u7ec3\u65f6\uff08\u77e5\u9053 oracle observation\uff09\uff0c\u5206\u522b\u7528 executor observation \u548c oracle observation \u6765\u4f30\u8ba1\u4e00\u4e2a\u8d1d\u53f6\u65af\u9690\u53d8\u91cfz\u7684\u5148\u9a8c\uff08prior\uff09\u548c\u540e\u9a8c\uff08posterior\uff09\u5206\u5e03\u3002\u901a\u8fc7\u4f18\u5316 VLOG \u53d8\u5206\u4e0b\u754c\uff08variational lower bound\uff0c\u540e\u9a8c\u6a21\u578b\u7684\u5f3a\u5316\u5b66\u4e60\u76ee\u6807\u51fd\u6570\u51cf\u53bbz\u7684\u540e\u9a8c\u548c\u5148\u9a8c\u5206\u5e03\u4e4b\u95f4\u7684KL\u6563\u5ea6\uff09\u6765\u8bad\u7ec3\u6574\u4e2a\u6a21\u578b\u3002\u53f3\uff1a\u4f7f\u7528\u65f6\uff0c\u57fa\u4e8e\u53ef\u89c1\u4fe1\u606f\u6765\u505a\u51fa\u51b3\u7b56\u3002<\/em><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>\u7814\u7a76\u5458\u4eec\u5bf9 VLOG \u8fdb\u884c\u4e86\u5404\u79cd\u4efb\u52a1\u7684\u5b9e\u9a8c\uff0c\u5305\u62ec\u4e00\u4e2a\u8ff7\u5bab\uff0c\u7b80\u660e\u7248\u7684 Atari Games\uff0c\u4ee5\u53ca\u9ebb\u5c06\u3002\u5b9e\u9a8c\u6db5\u76d6\u4e86\u5728\u7ebf\u4ee5\u53ca\u79bb\u7ebf\u5f3a\u5316\u5b66\u4e60\u7684\u4e0d\u540c\u60c5\u51b5\uff0c\u5747\u9a8c\u8bc1\u4e86 VLOG \u7684\u826f\u597d\u8868\u73b0\u3002 \u6b64\u5916\uff0c\u7814\u7a76\u5458\u4eec\u8fd8\u5f00\u6e90\u4e86\u6587\u4e2d\u4f7f\u7528\u7684\u9ebb\u5c06\u5f3a\u5316\u5b66\u4e60\u73af\u5883\u548c\u5bf9\u5e94\u7684\u79bb\u7ebf\u5f3a\u5316\u5b66\u4e60\u6570\u636e\u96c6\uff0c\u6765\u4f5c\u4e3a\u672a\u6765 oracle guiding \u95ee\u9898\u548c\u590d\u6742\u51b3\u7b56\u73af\u5883\u7814\u7a76\u7684\u6807\u51c6\u5316\u6d4b\u8bd5\u73af\u5883 \u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7f16\u8005\u6309\uff1aICLR\uff08International Conference on Learning Representations\uff09\u662f\u56fd\u9645\u516c\u8ba4\u7684\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u9876\u7ea7\u4f1a\u8bae\u4e4b\u4e00\uff0c\u4f17\u591a\u5728\u4eba\u5de5\u667a\u80fd\u3001\u7edf\u8ba1\u548c\u6570\u636e\u79d1\u5b66\u9886\u57df\u4ee5\u53ca\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u8bed\u97f3\u8bc6\u522b\u3001\u6587\u672c\u7406\u89e3\u7b49\u91cd\u8981\u5e94\u7528\u9886\u57df\u6781\u5176\u6709\u5f71\u54cd\u529b\u7684\u8bba\u6587\u90fd\u53d1\u8868\u5728\u8be5\u5927\u4f1a\u4e0a\u3002\u4eca\u5e74\u7684 ICLR \u5927\u4f1a\u4e8e4\u670825\u65e5\u81f329\u65e5\u5728\u7ebf\u4e0a\u4e3e\u529e\u3002\u672c\u5c4a\u5927\u4f1a\u5171\u63a5\u6536\u8bba\u65871095\u7bc7\uff0c\u8bba\u6587\u63a5\u6536\u738732.3%\u3002\u4eca\u5929\uff0c\u6211\u4eec\u7cbe\u9009\u4e86\u5176\u4e2d\u7684\u516d\u7bc7\u6765\u4e3a\u5927\u5bb6\u8fdb\u884c\u7b80\u8981\u4ecb\u7ecd\uff0c\u5176\u4e2d\u7814\u7a76\u4e3b\u9898\u7684\u5173\u952e\u8bcd\u5305\u62ec\u65f6\u95f4\u5e8f\u5217\u3001\u7b56\u7565\u4f18\u5316\u3001\u89e3\u8026\u8868\u793a\u5b66\u4e60\u3001\u91c7\u6837\u65b9\u6cd5\u3001\u5f3a\u5316\u5b66\u4e60\u7b49\u3002\u6b22\u8fce\u611f\u5174\u8da3\u7684\u8bfb\u8005\u9605\u8bfb\u8bba\u6587\u539f\u6587\uff0c\u4e00\u8d77\u4e86\u89e3\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u7684\u524d\u6cbf\u8fdb\u5c55\uff01 \u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/depts-deep-expansion-learning-for-periodic-time-series-forecasting\/ 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\u5728\u6df1\u5165\u601d\u8003\u8fd9\u4e9b\u7814\u7a76\u96be\u70b9\u540e\uff0c\u5fae\u8f6f\u4e9a\u6d32\u7814\u7a76\u9662\u7684\u7814\u7a76\u5458\u4eec\u4e3a\u5468\u671f\u6027\u65f6\u95f4\u5e8f\u5217\u7684\u9884\u6d4b\u95ee\u9898\u63d0\u51fa\u4e86\u4e00\u5957\u65b0\u578b\u7684\u6df1\u5ea6\u5c55\u5f00\u5b66\u4e60\u6846\u67b6 DEPTS\u3002\u8be5\u6846\u67b6\u65e2\u53ef\u4ee5\u523b\u753b\u591a\u6837\u5316\u7684\u5468\u671f\u6027\u6210\u5206\uff0c\u4e5f\u80fd\u6355\u6349\u590d\u6742\u7684\u5468\u671f\u6027\u4f9d\u8d56\u5173\u7cfb\u3002 \u5982\u56fe1\u6240\u793a\uff0cDEPTS \u4e3b\u8981\u5305\u542b\u4e24\u5927\u6a21\u5757\uff1a\u5468\u671f\u6a21\u5757\uff08The Periodicity Module\uff09\u548c\u5c55\u5f00\u6a21\u5757\uff08The Expansion 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