{"id":1007,"date":"2018-01-02T13:18:34","date_gmt":"2018-01-02T13:18:34","guid":{"rendered":"http:\/\/www.marekrei.com\/blog\/?p=1007"},"modified":"2019-09-27T23:20:36","modified_gmt":"2019-09-27T23:20:36","slug":"ml-nlp-publications-in-2017","status":"publish","type":"post","link":"https:\/\/www.marekrei.com\/blog\/ml-nlp-publications-in-2017\/","title":{"rendered":"ML\/NLP Publications in 2017"},"content":{"rendered":"<p>It has been a very productive year for NLP and ML research. Both areas continued to grow, with conferences reaching record numbers of publications. In this post I will break these numbers down a bit more, by individual authors and organisations. The statistics cover the following venues: ACL, EMNLP, NAACL, EACL, COLING, TACL, CL, CoNLL, *Sem+SemEval, NIPS, ICML, ICLR. Compared to last year, I&#8217;ve now included ICLR which has grown very rapidly in the last two years and become a highly competitive conference.<\/p>\n<p>The analysis is done automatically, by crawling publication information from the conference websites and ACL Anthology. Author names are usually listed in the proceedings and easily extractable, however the organisation names are more tricky and need to be extracted straight from the PDFs. I&#8217;ve created a number of rules to map together alternative names and misspellings, but let me know if you notice any errors. <\/p>\n<p><strong>Venues<\/strong><\/p>\n<p>First, let&#8217;s look at different publication venues between 2012-2017. NIPS is clearly heading off the charts, with 677 publications this year. Most other venues are also growing rapidly, with 2017 being the biggest year ever for ICML, ICLR, EMNLP, EACL and CoNLL. In contrast, TACL and CL seem to be keeping a constant number of publications per year. NAACL and COLING were notably missing from 2017, but we can look forward to both of them in 2018.<\/p>\n<div id=\"myplot_graph2017allsource_year\" style=\"width: 700px; height: 700px;\"><\/div>\n<p><script>\nvar trace_graph2017allsource_year_0 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [222, 394, 328, 358, 378, 352, ],\n  text: 'ACL',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_1 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [139, 205, 226, 312, 264, 344, ],\n  text: 'EMNLP',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_2 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [126, 168, 0, 239, 224, 0, ],\n  text: 'NAACL',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_3 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [116, 0, 163, 0, 0, 280, ],\n  text: 'EACL',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_4 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [399, 0, 255, 0, 408, 0, ],\n  text: 'COLING',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_5 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [0, 35, 43, 42, 39, 37, ],\n  text: 'TACL',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_6 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [39, 37, 37, 33, 31, 28, ],\n  text: 'CL',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_7 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [0, 42, 33, 53, 53, 86, ],\n  text: 'CoNLL',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_8 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [109, 158, 171, 198, 239, 211, ],\n  text: 'StarSem',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_9 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [368, 360, 411, 403, 568, 677, ],\n  text: 'NIPS',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_10 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [243, 283, 310, 270, 322, 434, ],\n  text: 'ICML',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017allsource_year_11 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [0, 23, 34, 42, 80, 198, ],\n  text: 'ICLR',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar data_graph2017allsource_year = [trace_graph2017allsource_year_0, trace_graph2017allsource_year_1, trace_graph2017allsource_year_2, trace_graph2017allsource_year_3, trace_graph2017allsource_year_4, trace_graph2017allsource_year_5, trace_graph2017allsource_year_6, trace_graph2017allsource_year_7, trace_graph2017allsource_year_8, trace_graph2017allsource_year_9, trace_graph2017allsource_year_10, trace_graph2017allsource_year_11];\nPlotly.newPlot('myplot_graph2017allsource_year', data_graph2017allsource_year, {margin: { l: 30, r: 0, b: 100, t: 0, pad: 4 }, showlegend: false, showticklabels: true, xaxis:{autotick: false}});\n<\/script><\/p>\n<p><!--more--><\/p>\n<p><strong>Authors<\/strong><\/p>\n<p>The most prolific author of 2017 is <a href=\"https:\/\/www.ukp.tu-darmstadt.de\/people\/group-heads\/prof-dr-iryna-gurevych\/\">Iryna Gurevych<\/a> (TU Darmstadt) with 18 papers. <a href=\"http:\/\/people.ee.duke.edu\/~lcarin\/\">Lawrence Carin<\/a> (Duke University) has 16 publications, with an impressive 10 papers at NIPS. Following them closely are <a href=\"http:\/\/people.sutd.edu.sg\/~yue_zhang\/\">Yue Zhang<\/a> (Singapore), <a href=\"http:\/\/www.iro.umontreal.ca\/~bengioy\/yoshua_en\/\">Yoshua Bengio<\/a> (Montreal), and <a href=\"http:\/\/www.cis.uni-muenchen.de\/personen\/professoren\/schuetze\/\">Hinrich Sch\u00fctze<\/a> (Munich).<\/p>\n<div id=\"myplot_graph2017last_author_source\" style=\"width: 700px; height: 700px;\"><\/div>\n<p><script>\nvar trace_graph2017last_author_source_0 = {  x: [\"Iryna Gurevych\", \"Lawrence Carin\", \"Yue Zhang\", \"Yoshua Bengio\", \"Hinrich Sch\u00fctze\", \"Graham Neubig\", \"Pieter Abbeel\", \"Chris Dyer\", \"Timothy Baldwin\", \"Ryan Cotterell\", \"Qun Liu\", \"Ming Zhou\", \"Anders S\u00f8gaard\", \"Trevor Cohn\", \"Yang Liu\", \"Sergey Levine\", \"Pushmeet Kohli\", \"Le Song\", \"Andreas Krause\", \"Mirella Lapata\", \"Dan Klein\", \"Percy Liang\", \"Eduard Hovy\", \"Alessandro Moschitti\", \"Benjamin Van Durme\", \"Yoav Goldberg\", \"Man Lan\", \"Yuanbin 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Lan\", \"Yuanbin Wu\"],\n  y: [6, 1, 5, 0, 2, 3, 0, 1, 3, 2, 3, 3, 2, 4, 3, 0, 0, 0, 0, 5, 3, 3, 4, 1, 0, 0, 1, 1, 2, 1, 1, 2, 3, 3, 0, 0, 0, 2, 4, 2, 1, 3, 2, 1, 2, ],\n  name: 'EMNLP',\n  type: 'bar'\n};\nvar trace_graph2017last_author_source_9 = {  x: [\"Iryna Gurevych\", \"Lawrence Carin\", \"Yue Zhang\", \"Yoshua Bengio\", \"Hinrich Sch\u00fctze\", \"Graham Neubig\", \"Pieter Abbeel\", \"Chris Dyer\", \"Timothy Baldwin\", \"Ryan Cotterell\", \"Qun Liu\", \"Ming Zhou\", \"Anders S\u00f8gaard\", \"Trevor Cohn\", \"Yang Liu\", \"Sergey Levine\", \"Pushmeet Kohli\", \"Le Song\", \"Andreas Krause\", \"Mirella Lapata\", \"Dan Klein\", \"Percy Liang\", \"Eduard Hovy\", \"Alessandro Moschitti\", \"Benjamin Van Durme\", \"Yoav Goldberg\", \"Man Lan\", \"Yuanbin Wu\"],\n  y: [4, 1, 3, 1, 1, 4, 0, 4, 2, 2, 4, 6, 3, 3, 4, 0, 0, 0, 0, 2, 5, 3, 2, 3, 3, 2, 0, 0, 6, 1, 3, 1, 5, 2, 0, 0, 0, 4, 3, 1, 1, 3, 3, 1, 2, ],\n  name: 'ACL',\n  type: 'bar'\n};\nvar data_graph2017last_author_source = [trace_graph2017last_author_source_0, trace_graph2017last_author_source_1, trace_graph2017last_author_source_2, trace_graph2017last_author_source_3, trace_graph2017last_author_source_4, trace_graph2017last_author_source_5, trace_graph2017last_author_source_6, trace_graph2017last_author_source_7, trace_graph2017last_author_source_8, trace_graph2017last_author_source_9];\nPlotly.newPlot('myplot_graph2017last_author_source', data_graph2017last_author_source, {barmode: 'stack', margin: { l: 30, r: 0, b: 200, t: 20, pad: 4 }});\n<\/script><\/p>\n<p>Looking at cumulative statistics from 2012-2017, <a href=\"http:\/\/www.cs.cmu.edu\/~cdyer\/\">Chris Dyer<\/a> (DeepMind) is at the top with an impressive lead, followed by <a href=\"https:\/\/www.ukp.tu-darmstadt.de\/people\/group-heads\/prof-dr-iryna-gurevych\/\">Iryna Gurevych<\/a> (TU Darmstadt) and <a href=\"https:\/\/homes.cs.washington.edu\/~nasmith\/\">Noah A. Smith<\/a> (Washington). <a href=\"http:\/\/people.ee.duke.edu\/~lcarin\/\">Lawrence Carin<\/a> (Duke), <a href=\"http:\/\/mlg.eng.cam.ac.uk\/zoubin\/\">Zoubin Ghahramani<\/a> (Cambridge) and <a href=\"https:\/\/www.cs.cmu.edu\/~pradeepr\/\">Pradeep K. Ravikumar<\/a> (CMU) are publishing mainly in the general ML venues, while the others are balanced between NLP and ML.<\/p>\n<div id=\"myplot_graph2017all_author_source\" style=\"width: 700px; height: 700px;\"><\/div>\n<p><script>\nvar trace_graph2017all_author_source_0 = {  x: [\"Chris Dyer\", \"Iryna Gurevych\", \"Noah A. Smith\", \"Yoshua Bengio\", \"Yang Liu\", \"Christopher D. Manning\", \"Yue Zhang\", \"Ting Liu\", \"Hinrich Sch\u00fctze\", \"Ming Zhou\", \"Timothy Baldwin\", \"Qun Liu\", \"Anders S\u00f8gaard\", \"Dan Roth\", \"Trevor Cohn\", \"Alessandro Moschitti\", \"Lawrence Carin\", \"Dan Klein\", \"Heng Ji\", \"Pushpak Bhattacharyya\", \"Benjamin Van Durme\", \"Zoubin Ghahramani\", \"Jordan Boyd-Graber\", \"Pradeep K. 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Manning\", \"Yue Zhang\", \"Ting Liu\", \"Hinrich Sch\u00fctze\", \"Ming Zhou\", \"Timothy Baldwin\", \"Qun Liu\", \"Anders S\u00f8gaard\", \"Dan Roth\", \"Trevor Cohn\", \"Alessandro Moschitti\", \"Lawrence Carin\", \"Dan Klein\", \"Heng Ji\", \"Pushpak Bhattacharyya\", \"Benjamin Van Durme\", \"Zoubin Ghahramani\", \"Jordan Boyd-Graber\", \"Pradeep K. Ravikumar\"],\n  y: [20, 14, 17, 1, 13, 18, 20, 15, 13, 12, 8, 13, 6, 16, 16, 6, 1, 15, 12, 7, 7, 0, 10, 0, 5, ],\n  name: 'EMNLP',\n  type: 'bar'\n};\nvar trace_graph2017all_author_source_11 = {  x: [\"Chris Dyer\", \"Iryna Gurevych\", \"Noah A. Smith\", \"Yoshua Bengio\", \"Yang Liu\", \"Christopher D. Manning\", \"Yue Zhang\", \"Ting Liu\", \"Hinrich Sch\u00fctze\", \"Ming Zhou\", \"Timothy Baldwin\", \"Qun Liu\", \"Anders S\u00f8gaard\", \"Dan Roth\", \"Trevor Cohn\", \"Alessandro Moschitti\", \"Lawrence Carin\", \"Dan Klein\", \"Heng Ji\", \"Pushpak Bhattacharyya\", \"Benjamin Van Durme\", \"Zoubin Ghahramani\", \"Jordan Boyd-Graber\", \"Pradeep K. Ravikumar\"],\n  y: [23, 21, 18, 6, 25, 22, 18, 16, 12, 30, 11, 18, 17, 8, 18, 14, 1, 19, 24, 11, 18, 0, 13, 0, 18, ],\n  name: 'ACL',\n  type: 'bar'\n};\nvar data_graph2017all_author_source = [trace_graph2017all_author_source_0, trace_graph2017all_author_source_1, trace_graph2017all_author_source_2, trace_graph2017all_author_source_3, trace_graph2017all_author_source_4, trace_graph2017all_author_source_5, trace_graph2017all_author_source_6, trace_graph2017all_author_source_7, trace_graph2017all_author_source_8, trace_graph2017all_author_source_9, trace_graph2017all_author_source_10, trace_graph2017all_author_source_11];\nPlotly.newPlot('myplot_graph2017all_author_source', data_graph2017all_author_source, {barmode: 'stack', margin: { l: 30, r: 0, b: 200, t: 20, pad: 4 }});\n<\/script><\/p>\n<p>Separating the publications by year shows that Chris Dyer has scaled down the publication count to a more manageable level this year, and Iryna Gurevych is developing an impressive upward trajectory.<\/p>\n<div id=\"myplot_graph2017all_author_year\" style=\"width: 700px; height: 700px;\"><\/div>\n<p><script>\nvar trace_graph2017all_author_year_0 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [4, 10, 17, 21, 25, 12, ],\n  text: 'Chris Dyer',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_1 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 11, 12, 6, 13, 18, ],\n  text: 'Iryna Gurevych',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_2 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 10, 16, 14, 11, 7, ],\n  text: 'Noah A. Smith',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_3 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [4, 9, 14, 8, 14, 14, ],\n  text: 'Yoshua Bengio',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_4 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 8, 7, 14, 11, 11, ],\n  text: 'Yang Liu',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_5 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [8, 13, 14, 11, 8, 8, ],\n  text: 'Christopher D. Manning',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_6 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [3, 4, 13, 9, 18, 14, ],\n  text: 'Yue Zhang',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_7 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 5, 17, 6, 13, 8, ],\n  text: 'Ting Liu',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_8 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [5, 4, 9, 13, 15, 14, ],\n  text: 'Hinrich Sch\u00fctze',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_9 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 8, 12, 8, 9, 11, ],\n  text: 'Ming Zhou',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_10 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 5, 10, 7, 14, 12, ],\n  text: 'Timothy Baldwin',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_11 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 8, 8, 6, 12, 11, ],\n  text: 'Qun Liu',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_12 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [3, 7, 9, 11, 12, 11, ],\n  text: 'Anders S\u00f8gaard',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_13 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 8, 5, 7, 13, 7, ],\n  text: 'Dan Roth',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_14 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [2, 7, 6, 11, 14, 11, ],\n  text: 'Trevor Cohn',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_15 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [4, 7, 7, 11, 11, 10, ],\n  text: 'Alessandro Moschitti',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_16 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [7, 5, 8, 9, 6, 15, ],\n  text: 'Lawrence Carin',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_17 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [10, 9, 8, 8, 4, 10, ],\n  text: 'Dan Klein',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_18 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [2, 4, 11, 13, 11, 6, ],\n  text: 'Heng Ji',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_19 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [10, 10, 2, 7, 9, 9, ],\n  text: 'Pushpak Bhattacharyya',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_20 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [5, 9, 7, 12, 2, 10, ],\n  text: 'Benjamin Van Durme',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_21 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [9, 1, 11, 10, 5, 8, ],\n  text: 'Zoubin Ghahramani',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_22 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [6, 4, 8, 11, 9, 5, ],\n  text: 'Jordan Boyd-Graber',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_author_year_23 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [2, 7, 14, 10, 5, 5, ],\n  text: 'Pradeep K. Ravikumar',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar data_graph2017all_author_year = [trace_graph2017all_author_year_0, trace_graph2017all_author_year_1, trace_graph2017all_author_year_2, trace_graph2017all_author_year_3, trace_graph2017all_author_year_4, trace_graph2017all_author_year_5, trace_graph2017all_author_year_6, trace_graph2017all_author_year_7, trace_graph2017all_author_year_8, trace_graph2017all_author_year_9, trace_graph2017all_author_year_10, trace_graph2017all_author_year_11, trace_graph2017all_author_year_12, trace_graph2017all_author_year_13, trace_graph2017all_author_year_14, trace_graph2017all_author_year_15];\nPlotly.newPlot('myplot_graph2017all_author_year', data_graph2017all_author_year, {margin: { l: 30, r: 0, b: 100, t: 0, pad: 4 }, showlegend: false, showticklabels: true, xaxis:{autotick: false}});\n<\/script><\/p>\n<p><strong>First Authors<\/strong><\/p>\n<p>Now let&#8217;s look at first authors, as these are usually the people implementing the code and running the experiments. <a href=\"http:\/\/people.ds.cam.ac.uk\/iv250\/\">Ivan Vuli\u0107<\/a> (Cambridge), <a href=\"https:\/\/ryancotterell.github.io\/\">Ryan Cotterell<\/a> (Johns Hopkins) and <a href=\"http:\/\/people.csail.mit.edu\/zeyuan\/\">Zeyuan Allen-Zhu <\/a> (Microsoft Research) have all produced an impressive 6 first-author publications in 2017. They are followed by <a href=\"https:\/\/www.uni-weimar.de\/en\/media\/chairs\/computer-science-and-media\/webis\/people\/henning-wachsmuth\/\">Henning Wachsmuth<\/a> (Weimar), <a href=\"http:\/\/www.tsendeemts.com\/\">Tsendsuren Munkhdalai<\/a> (Microsoft Maluuba), <a href=\"https:\/\/web.stanford.edu\/~jiweil\/\">Jiwei Li<\/a> (Stanford) and <a href=\"http:\/\/www.cs.cmu.edu\/~ssdu\/\">Simon S. Du<\/a> (CMU).<\/p>\n<div id=\"myplot_graph2017last_firstauthor_source\" style=\"width: 700px; height: 700px;\"><\/div>\n<p><script>\nvar trace_graph2017last_firstauthor_source_0 = {  x: [\"Ivan Vuli\u0107\", \"Ryan Cotterell\", \"Zeyuan Allen-Zhu\", \"Henning Wachsmuth\", \"Tsendsuren Munkhdalai\", \"Jiwei Li\", \"Simon S. 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Universities that publish proportionally more in the general ML area compared to NLP include MIT, Columbia, Oxford, Harvard, Toronto, Princeton and Z\u00fcrich. In contrast, universities and organisations that focus more on the NLP venues include Edinburgh, IBM, Peking, Washington, Johns Hopkins, Pennsylvania, CAS, Darmstadt, and Qatar.<\/p>\n<div id=\"myplot_graph2017_org_source\" style=\"width: 700px; height: 700px;\"><\/div>\n<p><script>\nvar trace_graph2017_org_source_0 = {  x: [\"Carnegie Mellon University\", \"Google\", \"Microsoft\", \"Stanford University\", \"Massachusetts Institute of Technology\", \"UC Berkeley\", \"University of Cambridge\", \"Facebook\", \"University of Edinburgh\", \"IBM\", \"Tsinghua University\", \"Peking University\", \"University of Washington\", \"Johns Hopkins University\", \"University of Pennsylvania\", \"New York University\", \"Cornell University\", \"Columbia University\", \"University of Oxford\", \"University of Michigan\", \"Georgia Institute of Technology\", \"Universit\u00e9 Paris-Saclay\", \"University of Illinois at Urbana-Champaign\", \"University of Melbourne\", \"Harvard University\", 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700px;\"><\/div>\n<p><script>\nvar trace_graph2017allorg_source_0 = {  x: [\"Carnegie Mellon University\", \"Microsoft\", \"Google\", \"Stanford University\", \"University of Cambridge\", \"IBM\", \"Massachusetts Institute of Technology\", \"UC Berkeley\", \"Columbia University\", \"University of Edinburgh\", \"University of Washington\", \"Johns Hopkins University\", \"Peking University\", \"UT Austin\", \"University of Pennsylvania\", \"Tsinghua University\", \"Princeton University\", \"University of Toronto\", \"Facebook\", \"Chinese Academy of Sciences\", \"University of Maryland\", \"Cornell University\", \"University College London\", \"Harbin Institute of Technology\", \"INRIA\", ],\n  y: [11, 18, 48, 17, 7, 2, 12, 21, 7, 5, 6, 1, 1, 1, 0, 3, 5, 16, 34, 1, 2, 4, 4, 0, 0, ],\n  name: 'ICLR',\n  type: 'bar'\n};\nvar trace_graph2017allorg_source_1 = {  x: [\"Carnegie Mellon University\", \"Microsoft\", \"Google\", \"Stanford University\", \"University of Cambridge\", \"IBM\", 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University\", \"University of Cambridge\", \"IBM\", \"Massachusetts Institute of Technology\", \"UC Berkeley\", \"Columbia University\", \"University of Edinburgh\", \"University of Washington\", \"Johns Hopkins University\", \"Peking University\", \"UT Austin\", \"University of Pennsylvania\", \"Tsinghua University\", \"Princeton University\", \"University of Toronto\", \"Facebook\", \"Chinese Academy of Sciences\", \"University of Maryland\", \"Cornell University\", \"University College London\", \"Harbin Institute of Technology\", \"INRIA\", ],\n  y: [109, 112, 58, 60, 44, 55, 21, 25, 42, 51, 32, 45, 53, 16, 28, 43, 1, 12, 18, 51, 31, 25, 7, 43, 6, ],\n  name: 'ACL',\n  type: 'bar'\n};\nvar data_graph2017allorg_source = [trace_graph2017allorg_source_0, trace_graph2017allorg_source_1, trace_graph2017allorg_source_2, trace_graph2017allorg_source_3, trace_graph2017allorg_source_4, trace_graph2017allorg_source_5, trace_graph2017allorg_source_6, trace_graph2017allorg_source_7, trace_graph2017allorg_source_8, trace_graph2017allorg_source_9, trace_graph2017allorg_source_10, trace_graph2017allorg_source_11];\nPlotly.newPlot('myplot_graph2017allorg_source', data_graph2017allorg_source, {barmode: 'stack', margin: { l: 30, r: 0, b: 270, t: 20, pad: 4 }});\n<\/script><\/p>\n<p>Looking at the time series, it seems CMU, Stanford, MIT and Berkeley are on the upward trajectory in terms of publications. In contrast, the industry leaders Google, Microsoft and IBM have slightly scaled back their publication numbers.<\/p>\n<div id=\"myplot_graph2017all_org_year\" style=\"width: 700px; height: 700px;\"><\/div>\n<p><script>\nvar trace_graph2017all_org_year_0 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [67, 83, 90, 88, 109, 126, ],\n  text: 'Carnegie Mellon University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_1 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [73, 89, 97, 85, 104, 97, ],\n  text: 'Microsoft',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_2 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [38, 43, 71, 75, 120, 109, ],\n  text: 'Google',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_3 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [52, 69, 74, 64, 84, 89, ],\n  text: 'Stanford University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_4 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [32, 29, 51, 38, 61, 57, ],\n  text: 'University of Cambridge',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_5 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [27, 36, 50, 42, 60, 45, ],\n  text: 'IBM',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_6 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [25, 27, 35, 46, 53, 67, ],\n  text: 'Massachusetts Institute of Technology',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_7 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [28, 32, 35, 45, 43, 64, ],\n  text: 'UC Berkeley',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_8 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [34, 47, 48, 44, 40, 29, ],\n  text: 'Columbia University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_9 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [29, 33, 47, 39, 42, 47, ],\n  text: 'University of Edinburgh',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_10 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [29, 33, 35, 43, 56, 37, ],\n  text: 'University of Washington',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_11 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [28, 37, 20, 46, 31, 33, ],\n  text: 'Johns Hopkins University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_12 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [24, 15, 27, 29, 47, 37, ],\n  text: 'Peking University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_13 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [21, 26, 37, 29, 41, 20, ],\n  text: 'UT Austin',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_14 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [30, 31, 28, 22, 28, 31, ],\n  text: 'University of Pennsylvania',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_15 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [20, 14, 23, 25, 40, 38, ],\n  text: 'Tsinghua University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_16 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [14, 12, 28, 28, 48, 21, ],\n  text: 'Princeton University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_17 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [28, 26, 24, 25, 22, 21, ],\n  text: 'University of Toronto',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_18 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [5, 6, 12, 28, 41, 53, ],\n  text: 'Facebook',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_19 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [21, 22, 27, 22, 26, 22, ],\n  text: 'Chinese Academy of Sciences',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_20 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [26, 24, 21, 26, 23, 17, ],\n  text: 'University of Maryland',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_21 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [11, 19, 28, 23, 24, 29, ],\n  text: 'Cornell University',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_22 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [25, 21, 19, 19, 22, 22, ],\n  text: 'University College London',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_23 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [17, 18, 34, 20, 21, 17, ],\n  text: 'Harbin Institute of Technology',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar trace_graph2017all_org_year_24 = {  x: [\"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", ],\n  y: [23, 22, 18, 25, 17, 22, ],\n  text: 'INRIA',\n  type: 'scatter',\nhoverinfo: \"text\"\n};\nvar data_graph2017all_org_year = [trace_graph2017all_org_year_0, trace_graph2017all_org_year_1, trace_graph2017all_org_year_2, trace_graph2017all_org_year_3, trace_graph2017all_org_year_4, trace_graph2017all_org_year_5, trace_graph2017all_org_year_6, trace_graph2017all_org_year_7, trace_graph2017all_org_year_8, trace_graph2017all_org_year_9, trace_graph2017all_org_year_10, trace_graph2017all_org_year_11, trace_graph2017all_org_year_12, trace_graph2017all_org_year_13, trace_graph2017all_org_year_14, trace_graph2017all_org_year_15];\nPlotly.newPlot('myplot_graph2017all_org_year', data_graph2017all_org_year, {margin: { l: 30, r: 0, b: 100, t: 0, pad: 4 }, showlegend: false, showticklabels: true, xaxis:{autotick: false}});\n<\/script><\/p>\n<p><strong>Topic Clustering<\/strong><\/p>\n<p>Finally, I did LDA on all the paper texts from authors that had 9 or more publications and visualised the results using tsne. In the middle is the topic of general machine learning, neural networks and adversarial learning. The top cluster covers reinforcement learning and different learning policies. The cluster on the left contains NLP applications, language modelling, parsing and machine translation. The cluster at the bottom covers information modelling and feature spaces.<\/p>\n<p><a href=\"https:\/\/www.marekrei.com\/blog\/wp-content\/uploads\/2018\/01\/clustering_authors_2017_last-1.png\" rel=\"attachment wp-att-1047\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.marekrei.com\/blog\/wp-content\/uploads\/2018\/01\/clustering_authors_2017_last-1.png\" alt=\"clustering_authors_2017_last\" width=\"871\" height=\"473\" class=\"aligncenter size-full wp-image-1047\" srcset=\"https:\/\/www.marekrei.com\/blog\/wp-content\/uploads\/2018\/01\/clustering_authors_2017_last-1.png 871w, https:\/\/www.marekrei.com\/blog\/wp-content\/uploads\/2018\/01\/clustering_authors_2017_last-1-150x81.png 150w, https:\/\/www.marekrei.com\/blog\/wp-content\/uploads\/2018\/01\/clustering_authors_2017_last-1-300x163.png 300w, https:\/\/www.marekrei.com\/blog\/wp-content\/uploads\/2018\/01\/clustering_authors_2017_last-1-768x417.png 768w\" sizes=\"auto, (max-width: 871px) 100vw, 871px\" \/><\/a><\/p>\n<p>That&#8217;s it for 2017. If you notice errors, let me know and I will continue updating this post.<br \/>\nLooking forward to all the exciting research coming in 2018!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>It has been a very productive year for NLP and ML research. Both areas continued to grow, with conferences reaching record numbers of publications. In&hellip;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1007","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>ML\/NLP Publications in 2017 - Marek Rei<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.marekrei.com\/blog\/ml-nlp-publications-in-2017\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ML\/NLP Publications in 2017 - Marek Rei\" \/>\n<meta property=\"og:description\" content=\"It has been a very productive year for NLP and ML research. 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