{"id":479,"date":"2022-09-09T00:41:18","date_gmt":"2022-09-08T15:41:18","guid":{"rendered":"https:\/\/www.mgt.ous.ac.jp\/society\/?page_id=479"},"modified":"2023-01-18T16:54:37","modified_gmt":"2023-01-18T07:54:37","slug":"conf-009","status":"publish","type":"page","link":"https:\/\/www.mgt.ous.ac.jp\/society\/group\/conf-009\/","title":{"rendered":"\u5ca1\u5c71\u7406\u79d1\u5927\u5b66\u30de\u30cd\u30b8\u30e1\u30f3\u30c8\u5b66\u4f1a \u7b2c\uff19\u56de\u7814\u7a76\u4f1a"},"content":{"rendered":"<p><span>\u5ca1\u5c71\u7406\u79d1\u5927\u5b66\u30de\u30cd\u30b8\u30e1\u30f3\u30c8\u5b66\u4f1a\u3067\u306f\u3001\u5ca1\u5c71\u7d71\u8a08\u7814\u7a76\u4f1a\u3068\u306e\u5171\u50ac\u3067\u3001\u30b7\u30f3\u30ac\u30dd\u30fc\u30eb\u53ca\u3073\u30c9\u30a4\u30c4\u304b\u3089\u6765\u65e5\u3055\u308c\u308b<\/span><span>\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u5206\u91ce\u306e\u7814\u7a76\u8005\u306e\u65b9\u3092\u304a\u8fce\u3048\u3057\u3001\u6df1\u5c64\u5b66\u7fd2\u3084\u8a08\u7b97\u74b0\u5883\u3092\u30c6\u30fc\u30de\u3068\u3057\u3066\u3001\u7b2c\uff19\u56de\u7814\u7a76\u4f1a\u3092\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u65b9\u5f0f\u3067\u958b\u50ac\u3057\u307e\u3059\u3002<\/span><br \/><span>\u3054\u8208\u5473\u3042\u308b\u65b9\u3001\u305c\u3072\u3054\u53c2\u52a0\u304f\u3060\u3055\u3044\u307e\u3059\u3088\u3046\u3054\u6848\u5185\u7533\u3057\u4e0a\u3052\u307e\u3059\u3002<\/span><\/p><p><strong>\u7b2c\uff19\u56de\u7814\u7a76\u4f1a\u3000\u958b\u50ac\u6848\u5185<\/strong><\/p><p><strong>\u65e5\u3000\u6642\uff1a<\/strong>2022\u5e749\u670822\u65e5\uff08\u6728\uff0916:25\uff5e<\/p><p><strong><\/strong><strong>\u5834\u3000\u6240\uff1a<\/strong>\u5ca1\u5c71\u7406\u79d1\u5927\u5b66 \uff21\uff11\u53f7\u9928\uff11\u968e \u30d7\u30ec\u30bc\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\u30eb\u30fc\u30e0<\/p><p><strong><span>\u958b\u50ac\u65b9\u6cd5\uff1a<\/span><\/strong>Zoom\u4f75\u7528\u306e\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u65b9\u5f0f\uff08\u53c2\u52a0\u8cbb\u7121\u6599\uff09<\/p><ul><li>Zoom ID\u306f\u3001\u4e0b\u8a18\u7533\u8fbc\u3067\u30aa\u30f3\u30e9\u30a4\u30f3\u3092\u9078\u629e\u3055\u308c\u305f\u65b9\u306b\u304a\u77e5\u3089\u305b\u3057\u307e\u3059\u3002<\/li><li>\u5bfe\u9762\u53c2\u52a0\u3092\u3055\u308c\u308b\u65b9\u306f\u3001\u611f\u67d3\u62e1\u5927\u9632\u6b62\u306b\u3064\u3044\u3066\u3001\u3054\u5354\u529b\u3092\u304a\u9858\u3044\u3057\u307e\u3059\u3002\u4f1a\u5834\u3067\u306f\u3001\u6d88\u6bd2\u6db2\u306e\u914d\u7f6e\u3001\u63db\u6c17\u7b49\u306b\u7559\u610f\u3057\u307e\u3059\u304c\u3001\u500b\u4eba\u306b\u304a\u304b\u308c\u307e\u3057\u3066\u3082\u3001\u30de\u30b9\u30af\u306e\u7740\u7528\u3084\u624b\u6307\u6d88\u6bd2\u3001\u4f53\u8abf\u7ba1\u7406\u3001\u611f\u67d3\u30ea\u30b9\u30af\u306e\u3042\u308b\u884c\u52d5\u306e\u56de\u907f\u7b49\u3092\u3088\u308d\u3057\u304f\u304a\u9858\u3044\u3057\u307e\u3059\u3002<\/li><\/ul><p><strong><span>\u30c6\u30fc\u30de\uff1aDeep learning and Computational aspects<\/span><\/strong><\/p><p><strong>\u7533\u3057\u8fbc\u307f\uff1a<\/strong><a href=\"https:\/\/forms.gle\/U86syDTRbxERFbzX8\">\u3053\u3061\u3089\u304b\u3089\u304a\u7533\u3057\u8fbc\u307f\u304f\u3060\u3055\u3044\uff08Google Form\uff09\u3002<\/a><br \/>    \u3000\u306a\u304a\u3001\u7533\u8fbc\u306a\u3057\u3067\u3082\u5f53\u65e5\u3054\u53c2\u52a0\u3044\u305f\u3060\u3051\u307e\u3059\u304c\u3001\u30aa\u30f3\u30e9\u30a4\u30f3\u306e\u5834\u5408\u306f\u5fc5\u305a\u304a\u7533\u3057\u8fbc\u307f\u304f\u3060\u3055\u3044\u3002<\/p><p><strong>\u5171\u3000\u50ac\uff1a<\/strong>\u5ca1\u5c71\u7d71\u8a08\u7814\u7a76\u4f1a<\/p><p><strong>\u554f\u5408\u305b\u5148\uff1a<\/strong>\u5ca1\u5c71\u7406\u79d1\u5927\u5b66\u7d4c\u55b6\u5b66\u90e8\u3000\u68ee\u3000\u88d5\u4e00&lt;yuichi-mori\u3042\u3063\u3068ous.ac.jp&gt;<\/p><p><strong>\u30d7\u30ed\u30b0\u30e9\u30e0\uff1a<\/strong><br \/>\u300016:25\u3000<strong>\u958b\u4f1a<\/strong><br \/>\u300016:30\u3000<strong>\u8b1b\u6f141<\/strong><br \/>\u300017:30\u3000<strong>\u8b1b\u6f142<\/strong><br \/>\u300018:30\u3000<strong>\u7dcf\u5408\u8a0e\u8ad6<\/strong><\/p><p><strong>Lecture 1:<\/strong> <br \/><strong>Deep Switching State Space Model (DS3M) for Nonlinear Time Series Forecasting with Regime Switching<\/strong><br \/><strong>Xiuqin Xu, *Ying Chen\u00a0<\/strong> (National University of Singapore, Singapore)<br \/><strong>Abstract:<\/strong> We propose a deep switching state space model (DS3M) for efficient inference and forecasting of nonlinear time series with irregularly switching among various regimes. The switching among regimes is captured by both discrete and continuous latent variables with recurrent neural networks. The model is estimated with variational inference using a reparameterization trick. We test the approach on a variety of simulated and real datasets. In all cases, DS3M achieves competitive performance compared to several state-of-the-art methods (e.g. GRU, SRNN, DSARF, SNLDS), with superior forecasting accuracy, convincing interpretability of the discrete latent variables, and powerful representation of the continuous latent variables for different kinds of time series. Specifically, the MAPE values increase by 0.09% to 15.71% against the second-best performing alternative models.<\/p><p><strong>Lecture 2:<\/strong><br \/><strong>Progress in Mathematical Programming Solvers from 2001 to 2020<\/strong><br \/><strong>*Thorsten Koch<\/strong> (Zuse Institute Berlin &amp; Technische Universitaet Berlin, Germany)<br \/><strong>Abstract:<\/strong> We report on a study that investigates the progress made in LP and MILP solver performance during the last two decades by comparing the solver software from the beginning of the millennium with the codes available today. On average, we found out that for solving LP\/MILP, the total speed-up was about 180 and 1,000 times, respectively. However, these numbers have a very high variance and they considerably underestimate the progress made on the algorithmic side: many problem instances can nowadays be solved within seconds, which the old codes are not able to solve within any reasonable time. We will report on how we measure performance and why it is very difficult to come up with one reasonable number.<\/p><p><strong>Discussion on Analysis for Big Data and Complex data<\/strong><br \/><strong>Discussants:<\/strong> <br \/>Ying Chen, National University of Singapore, Singapore<br \/>Thorsten Koch, Zuse Institute Berlin &amp; Technische Universitaet Berlin, Germany<br \/>Ralf Bornd\u00f6rfer, Zuse Institute Berlin and Freie Universit\u00e4t Berlin, Germany<br \/>Yuji Shinano, Zuse Institute Berlin, Germany<br \/>Uwe Gotzes, Open Grid Europe (OGE) , Germany<br \/>Masaya Iizuka, Okayama University, Japan<br \/>Masahiro Kuroda, Okayama University of Science, Japan<br \/>Yuichi Mori, Okayama University of Science, Japan<\/p>","protected":false},"excerpt":{"rendered":"<p>\u5ca1\u5c71\u7406\u79d1\u5927\u5b66\u30de\u30cd\u30b8\u30e1\u30f3\u30c8\u5b66\u4f1a\u3067\u306f\u3001\u5ca1\u5c71\u7d71\u8a08\u7814\u7a76\u4f1a\u3068\u306e\u5171\u50ac\u3067\u3001\u30b7\u30f3\u30ac\u30dd\u30fc\u30eb\u53ca\u3073\u30c9\u30a4\u30c4\u304b\u3089\u6765\u65e5\u3055\u308c\u308b\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u5206\u91ce\u306e\u7814\u7a76\u8005\u306e\u65b9\u3092\u304a\u8fce\u3048\u3057\u3001\u6df1\u5c64\u5b66\u7fd2\u3084\u8a08\u7b97\u74b0\u5883\u3092\u30c6\u30fc\u30de\u3068\u3057\u3066\u3001\u7b2c\uff19\u56de\u7814\u7a76\u4f1a\u3092\u30cf\u30a4\u30d6\u30ea\u30c3\u30c9\u65b9\u5f0f\u3067\u958b\u50ac\u3057\u307e\u3059\u3002[\uff65\uff65\uff65\u7d9a\u304d\u3092\u8aad\u3080]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":50,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/pages\/479"}],"collection":[{"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/comments?post=479"}],"version-history":[{"count":12,"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/pages\/479\/revisions"}],"predecessor-version":[{"id":507,"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/pages\/479\/revisions\/507"}],"up":[{"embeddable":true,"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/pages\/50"}],"wp:attachment":[{"href":"https:\/\/www.mgt.ous.ac.jp\/society\/wp-json\/wp\/v2\/media?parent=479"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}