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solid windowtext; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} </style> <![endif]--><!--[if gte mso 9]><xml> <o:shapedefaults v:ext="edit" spidmax="1026"/> </xml><![endif]--><!--[if gte mso 9]><xml> <o:shapelayout v:ext="edit"> <o:idmap v:ext="edit" data="1"/> </o:shapelayout></xml><![endif]--> </head> <body lang=EN-GB link=blue vlink=purple style='tab-interval:36.0pt'> <div class=WordSection1> <p class=MsoPlainText><span style='font-size:18.0pt;font-family:"Arial","sans-serif"; color:#993300'>The 6<sup>th</sup> ICDM Workshop on High Dimensional Data Mining (HDM 18)<br> </span><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'>In conjunction with the <a href="http://icdm2018.org/">IEEE International Conference on Data Mining</a> (IEEE ICDM 2018)<o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'>Singapore, November 17-20, 2018.<br style='mso-special-character:line-break'> <![if !supportLineBreakNewLine]><br style='mso-special-character:line-break'> <![endif]><o:p></o:p></span></p> <p style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:54.0pt; margin-bottom:.0001pt;background:white'><span class=aqj><span style='font-family: "Arial","sans-serif";color:black'><a href="https://wi-lab.com/cyberchair/2018/icdm18/scripts/submit.php?subarea=S10&amp;undisplay_detail=1&amp;wh=/cyberchair/2018/icdm18/scripts/ws_submit.php">SUBMIT HERE</a></span></span><span style='color:black'><o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:10.0pt'><b style='mso-bidi-font-weight: normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:#993300'><br> Description of Workshop</span></b><span style='font-family:"Arial","sans-serif"; color:#222222'><o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:#993300'><o:p>&nbsp;</o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'>Over a decade ago, Stanford statistician David <span class=SpellE>Donoho</span> predicted that the 21st century will be the century of data. &quot;We can say with complete confidence that in the coming century, high-dimensional data analysis will be a very significant activity, and completely new methods of high-dimensional data analysis will be developed; we just don't know what they are yet.&quot; -- D. <span class=SpellE>Donoho</span>, 2000.<o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'><o:p>&nbsp;</o:p></span></p> <p class=MsoNormal style='mso-layout-grid-align:none;text-autospace:none'><span style='font-family:"Arial","sans-serif"'>Unprecedented technological advances lead to increasingly high dimensional data sets in all areas of science, engineering and businesses. These include genomics and proteomics, biomedical imaging, signal processing, astrophysics, finance, web and market basket analysis, among many others. The number of features in such data is often of the order of thousands or millions - that is much larger than the available sample size.<br> <br> For a number of reasons, classical data analysis methods inadequate, questionable, or inefficient at best when faced with high dimensional data spaces: </span><span style='font-size:11.0pt;font-family:"Courier New"'><o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt;tab-stops:270.0pt'><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'><span style='mso-spacerun:yes'></span>1. High dimensional geometry defeats our intuition rooted in low dimensional experiences, and this makes data presentation and visualisation particularly challenging.<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'><span style='mso-spacerun:yes'></span>2. Phenomena that occur in high dimensional probability spaces, such as the concentration of measure, are counter-intuitive for the data mining practitioner. For instance, distance concentration is the phenomenon that the contrast between pair-wise distances may vanish as the dimensionality increases. <o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>3. Bogus correlations and misleading estimates may result when trying to fit complex models for which the effective dimensionality is too large compared to the number of data points available.<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'><span style='mso-spacerun:yes'></span>4. The accumulation of noise may confound our ability to find low dimensional intrinsic structure hidden in the high dimensional data.<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'><span style='mso-spacerun:yes'></span>5. The computation cost of processing high dimensional data or carrying out optimisation over a high dimensional parameter spaces is often prohibiting.<o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'><o:p>&nbsp;</o:p></span></p> <p class=MsoPlainText><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#984806; mso-themecolor:accent6;mso-themeshade:128'>Topics<o:p></o:p></span></b></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'><o:p>&nbsp;</o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'>This workshop aims to promote new advances and research directions to address the curses and uncover and exploit the blessings of high dimensionality in data mining. <o:p></o:p></span></p> <p class=MsoNormal style='tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt; background:white'><span style='font-family:"Arial","sans-serif";color:black'><o:p>&nbsp;</o:p></span></p> <p class=MsoNormal style='tab-stops:45.8pt 91.6pt 137.4pt 183.2pt 229.0pt 274.8pt 320.6pt 366.4pt 412.2pt 458.0pt 503.8pt 549.6pt 595.4pt 641.2pt 687.0pt 732.8pt; background:white'><span style='font-family:"Arial","sans-serif";color:black'>This year we would like to particularly encourage submissions that define and exploit some notion of &quot;intrinsic dimension&quot; or &quot;intrinsic structure&quot; in the learning or optimisation problem that allows solving high dimensional data mining tasks more reliably and more efficiently.<o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'><o:p>&nbsp;</o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'>Topics of interest include all aspects of high dimensional data mining, including the following:<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Systematic studies of how the curse of dimensionality affects data mining methods<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Models of low intrinsic dimension: sparse representation, manifold models, latent structure models, large margin, other?<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- How to exploit intrinsic dimension in optimisation tasks for data mining?<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- New data mining techniques that scale with the intrinsic dimension, or exploit some properties of high dimensional data spaces<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Dimensionality reduction <o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Methods of random projections, compressed sensing, and random matrix theory applied to high dimensional data mining and high dimensional optimisation<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Theoretical underpinning of mining data whose dimensionality is larger than the sample size<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Classification, regression, clustering, visualisation of high dimensional complex data sets<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Functional data mining<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Data presentation and visualisation methods for very high dimensional data sets<o:p></o:p></span></p> <p class=MsoPlainText style='margin-top:6.0pt'><span style='font-size:12.0pt; font-family:"Arial","sans-serif"'>- Data mining applications to real problems in science, engineering or businesses where the data is high dimensional<o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:#993300'><o:p>&nbsp;</o:p></span></p> <p class=MsoPlainText><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'>Paper submission</span></b><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:#993300'><o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'>High quality original submissions are solicited for oral and poster presentation at the </span><span style='font-size:11.0pt;font-family:"Arial","sans-serif"'>workshop. <span style='background:white'>The page limit of workshop papers is <span style='color:red'>8 pages </span>in the standard</span> <span style='background: white'>IEEE 2-column format</span> <span style='background:white'>(</span><a href="https://www.ieee.org/conferences/publishing/templates.html" data-saferedirecturl="https://www.google.com/url?hl=en&amp;q=http://www.ieee.org/conferences_events/conferences/publishing/templates.html&amp;source=gmail&amp;ust=1470355943385000&amp;usg=AFQjCNEfQQwCkp9KgX4PFL11JPDjyPLEAw" style='font-variant-ligatures: normal;font-variant-caps: normal;orphans: 2; text-align:start;widows: 2;-webkit-text-stroke-width: 0px;word-spacing:0px'>https://www.ieee.org/conferences/publishing/templates.html</a><span style='background:white'>),</span> <span style='background:white'>including the bibliography and any possible appendices.</span> Reviewing is triple-blind! Therefore, please do not include author identifying information.<o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:11.0pt;font-family:"Arial","sans-serif"'>All papers must be formatted according to the IEEE Computer <span style='background: white'>Society proceedings manuscript style, following</span></span><span style='font-size:12.0pt;font-family:"Arial","sans-serif";background:white'> IEEE ICDM 2018</span><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'> <span style='background:white'>submission guidelines, which are the same as for the main conference (except the page limit), and available at<span class=apple-converted-space>&nbsp;</span></span><a href="http://icdm2018.org/calls/call-for-papers/" data-saferedirecturl="https://www.google.com/url?hl=en&amp;q=http://icdm2016.eurecat.org/&amp;source=gmail&amp;ust=1470355943385000&amp;usg=AFQjCNGl4SGV-GibwTjMLlaDPPpGaoAEyg" style='font-variant-ligatures: normal;font-variant-caps: normal;orphans: 2; text-align:start;widows: 2;-webkit-text-stroke-width: 0px;word-spacing:0px'>http://icdm2018.org/calls/call-for-papers/</a>. A<span style='background:white'>ccepted papers will be</span> <span style='background:white'>included in the IEEE ICDM 2018 Workshops Proceedings volume published</span> <span style='background:white'>by IEEE Computer Society Press, and will also be included in the IEEE</span> <span class=SpellE><span style='background:white'>Xplore</span></span><span style='background:white'> Digital Library. The workshop proceedings will be in a CD</span> <span style='background:white'>separated from the CD of the main conference. The CD is produced by</span> <span style='background:white'>IEEE Conference Publishing Services (CPS</span>). <o:p></o:p></span></p> <p class=MsoPlainText><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:#993300'><br> <b style='mso-bidi-font-weight:normal'>Important dates</b><o:p></o:p></span></p> <p style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:54.0pt; margin-bottom:.0001pt;background:white'><span style='font-family:"Arial","sans-serif"; color:black'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=apple-converted-space>&nbsp;</span><span class=aqj>Submission deadline: 7<sup>th</sup> August, 2018. <a href="https://wi-lab.com/cyberchair/2018/icdm18/scripts/submit.php?subarea=S10&amp;undisplay_detail=1&amp;wh=/cyberchair/2018/icdm18/scripts/ws_submit.php">SUBMIT HERE</a></span></span><span class=aqj><span style='color:black'><o:p></o:p></span></span></p> <p style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:54.0pt; margin-bottom:.0001pt;background:white'><span style='font-family:"Arial","sans-serif"; color:black'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=apple-converted-space>&nbsp;</span>Workshop paper notifications:<span class=apple-converted-space>&nbsp;</span><span class=aqj><span style='z-index:-1'><span data-term="goog_114112750" tabindex=0 style='z-index:0'>September 4, 2018</span></span></span></span><span class=aqj><span style='font-size:9.5pt;font-family:"Arial","sans-serif";color:#222222'><o:p></o:p></span></span></p> <p style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:54.0pt; margin-bottom:.0001pt;background:white;font-variant-ligatures: normal; font-variant-caps: normal;orphans: 2;text-align:start;widows: 2;-webkit-text-stroke-width: 0px; text-decoration-style: initial;text-decoration-color: initial;word-spacing: 0px'><span class=aqj><span style='font-family:"Arial","sans-serif";color:black'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span></span><span class=apple-converted-space><span style='font-family:"Arial","sans-serif"; color:black'>&nbsp;</span></span><span class=aqj><span style='font-family:"Arial","sans-serif"; color:black'>Camera-ready deadline for the final version of accepted papers:</span></span><span class=apple-converted-space><span style='font-family:"Arial","sans-serif"; color:black'>&nbsp;</span></span><span class=aqj><span style='z-index:-1'><span style='font-family:"Arial","sans-serif";color:black'><span data-term="goog_114112751" tabindex=0 style='z-index:0'>September 15, 2018</span></span></span></span><span class=aqj><span style='font-size:9.5pt;font-family:"Arial","sans-serif"; color:#222222'><o:p></o:p></span></span></p> <p class=MsoPlainText style='font-variant-ligatures: normal;font-variant-caps: normal; orphans: 2;text-align:start;widows: 2;-webkit-text-stroke-width: 0px; text-decoration-style: initial;text-decoration-color: initial;word-spacing: 0px'><span class=aqj><span style='font-size:12.0pt;color:#993300'><o:p>&nbsp;</o:p></span></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'>Registration &amp; Expenses<o:p></o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:black;background:white'>Every workshop paper must have at least one full paid conference registration in</span></span><span class=aqj><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:black'> <span style='background:white'>order to be published. Check the main conference pages for details.<o:p></o:p></span></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#993300'><o:p>&nbsp;</o:p></span></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'>Program committee<o:p></o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'>Stephan <span class=SpellE>Gunnemann</span> - Carnegie Mellon University, USA<span style='mso-spacerun:yes'> </span><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'>Michael E. Houle - National Institute of Informatics, Japan<span style='mso-spacerun:yes'> </span><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'>Ata <span class=SpellE>Kaban</span> - University of Birmingham, United Kingdom<span style='mso-spacerun:yes'> </span><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'>Mehmed <span class=SpellE>Kantardzic</span> - University of Louisville, USA<span style='mso-spacerun:yes'> </span><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'>Mark Last - BGU, Israel<span style='mso-spacerun:yes'> </span><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'>Milos <span class=SpellE>Radovanovic</span> - University of Novi Sad, Serbia <span style='mso-spacerun:yes'></span><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=SpellE><span class=aqj><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#222222'>Nenad</span></span></span><span class=aqj><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:#222222'> <span class=SpellE>Tomasev</span> - Google, Mountain View, CA, USA<o:p></o:p></span></span></p> <p class=MsoPlainText><span class=SpellE><span class=aqj><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#222222'>Guoxian</span></span></span><span class=aqj><span style='font-size:12.0pt;font-family:"Arial","sans-serif"; color:#222222'> Yu - Southwest University, China<span style='mso-spacerun:yes'> </span><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'><o:p>&nbsp;</o:p></span></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'>Workshop organisation &amp; contact</span></b></span><span class=aqj><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#222222'><o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'><a href="http://www.cs.bham.ac.uk/~axk/"><span class=SpellE>Dr.</span> Ata <span class=SpellE>Kaban</span></a> <o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='font-size:12.0pt;font-family: "Arial","sans-serif";color:#222222'>School of Computer Science, University of Birmingham, UK<o:p></o:p></span></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-family:"Arial","sans-serif";color:#222222'><o:p>&nbsp;</o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'>Previous editions: <o:p></o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'><a href="http://www.cs.bham.ac.uk/~axk/HDM17.htm">HDM 17</a><o:p></o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'><a href="http://www.cs.bham.ac.uk/~axk/HDM16.htm">HDM 16</a><o:p></o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'><a href="http://www.cs.bham.ac.uk/~axk/HDM15.htm">HDM 15</a></span></b></span><span class=MsoHyperlink><o:p></o:p></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'><a href="http://www.cs.bham.ac.uk/~axk/HDM14.htm">HDM 14</a> <o:p></o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#993300'><a href="http://www.cs.bham.ac.uk/~axk/HDM.htm">HDM 13</a><o:p></o:p></span></b></span></p> <p class=MsoPlainText><span class=aqj><span style='color:#993300'><o:p>&nbsp;</o:p></span></span></p> <p class=MsoPlainText><span class=aqj><span style='color:#993300'><o:p>&nbsp;</o:p></span></span></p> <p class=MsoPlainText><span class=aqj><!--<p class=MsoPlainText><span lang=EN-GB style='font-size:12.0pt;font-family: Arial;mso-ansi-language:EN-GB'>Adam <span class=SpellE>Kowalczyk</span> - Victoria Research Laboratory, NICTA, Australia<o:p></o:p></span></p> <p class=MsoPlainText><span lang=EN-GB style='font-size:12.0pt;font-family: Arial;mso-ansi-language:EN-GB'>Arthur <span class=SpellE>Zimek</span> - LMU Munich, Germany<o:p></o:p></span></p> --><b style='mso-bidi-font-weight:normal'><span style='font-family:"Arial","sans-serif"; color:#222222'>Related Links &amp; resources: <a href="http://www.kdnuggets.com/">Analytics, Big Data, Data Mining, &amp; Data Science Resources</a></span></b></span><span class=aqj><span style='font-family: "Arial","sans-serif";color:#222222'> <o:p></o:p></span></span></p> </div> </body> </html>