<div dir="ltr"> ------- Apology for multiple postings --------<div><br></div><div><font size="4">IEEE BigData 2014 Workshop on Scalable Machine Learning: Theory and Applications</font><br><div><div style="line-height:1.5;margin:0px;padding:0.5em 0px;font-family:Arial,Helvetica,sans-serif">
<font color="#000000"><font><strong style="line-height:1.5">In conjunction with the </strong><strong>IEEE International Conference on Big Data</strong><strong style="line-height:1.5"> (<a href="http://icdm2014.sfu.ca/home.html" title="" target="_blank" style="text-decoration:none">IEEE BigData 2014</a>) on </strong><strong>October  27, 2014,  </strong><strong style="line-height:1.5">Washington DC, USA</strong></font><br>
</font></div><div style="font-family:arial,sans-serif;font-size:12.800000190734863px;margin:0px;padding:0.5em 0px"><font color="#000000"><font style="font-family:Arial,Helvetica,sans-serif;font-size:13px;line-height:1.5"><font size="3">Big data are encountered in various areas, including Internet search, social networks, finance, business sectors, meteorology, genomics, complex physics simulations, biological and environmental research. Machine learning as an important tool of big data analytics is playing more and more important roles in the big data era. However, the characteristics of large volume, high velocity, variety and veracity bring challenges to current machine learning techniques. It is therefore desirable to discuss</font></font><br>
<font style="font-family:Arial,Helvetica,sans-serif;font-size:13px;line-height:1.5"><font size="3"> (1) how to scale up existing machine learning techniques for modeling and analyzing big data from various domains;</font></font><br>
<font style="font-family:Arial,Helvetica,sans-serif;font-size:13px;line-height:1.5"><font size="3"> (2) how to design new machine learning algorithms for various parallel/distributed machine learning platforms (such as Hadoop, GraphLab, Spark, etc.); and</font></font><br>
</font><font style="font-family:Arial,Helvetica,sans-serif;font-size:13px;line-height:1.5"><font size="3" color="#000000"> (3) how to design universal machine learning interfaces for GPUs or cloud computing architectures, and so on. </font><br>
<font size="3"><br><strong><u><font color="#000000">Topics of Interest</font></u></strong><br></font></font><ul style="font-family:Arial,Helvetica,sans-serif;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style-position:outside!important">
<li style="color:rgb(135,135,135);font-size:13px;line-height:1.5;margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a"><strong>Distributed data analytics architectures</strong></font></li>
<ul style="color:rgb(135,135,135);font-size:13px;line-height:1.5;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style:disc outside!important"><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Data separation and integration techniques</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Machine learning algorithms for GPUs</font></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Machine learning algorithms for clouds</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Machine learning algorithms for clusters</font></li></ul><li style="color:rgb(135,135,135);font-size:13px;line-height:1.5;margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a"><strong>Theory and algorithms of data reduction techniques for big data</strong></font></li><ul style="color:rgb(135,135,135);font-size:13px;line-height:1.5;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style:disc outside!important">
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Online/incremental/stochastic learning algorithms</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Random projection</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Hashing techniques</font></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Data sampling algorithms</font></li></ul><li style="color:rgb(135,135,135);font-size:13px;line-height:1.5;margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a"><strong>Theory and algorithms of large-scale matrix approximation</strong></font></li><ul style="color:rgb(135,135,135);font-size:13px;line-height:1.5;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style:disc outside!important">
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Bound analysis of matrix approximation algorithms</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Distributed matrix factorization</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Distributed multiway array analysis</font></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Online dictionary learning</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Distributed topic modeling algorithms</font></li></ul><li style="color:rgb(135,135,135);font-size:13px;line-height:1.5;margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a"><strong>Heterogeneous learning on big multimodal data</strong></font></li><ul style="color:rgb(135,135,135);font-size:13px;line-height:1.5;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style:disc outside!important">
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Multiview learning</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Multitask learning</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Transfer learning</font></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Semi-supervised learning</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Active learning</font></li></ul><li style="color:rgb(135,135,135);font-size:13px;line-height:1.5;margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a"><strong>Temporal analysis and spatial analysis in big data</strong></font></li>
<ul style="color:rgb(135,135,135);font-size:13px;line-height:1.5;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style:disc outside!important"><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Real-time analysis for data stream</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Trend prediction in financial data</font></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Topic detection in instant message systems</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Real time modeling of events in dynamic networks</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Spatial modeling on maps</font></li>
</ul><li style="color:rgb(135,135,135);font-size:13px;line-height:1.5;margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a"><strong>Scalable machine learning in large graphs</strong></font></li>
<ul style="color:rgb(135,135,135);font-size:13px;line-height:1.5;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style:disc outside!important"><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Communities discovery and analysis in social networks</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Link prediction in networks</font></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Anomaly detection in social networks</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Fusion of information from multiple blogs, rating systems, and social networks</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Integration of text, videos, images, sounds in social networks</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Recommender systems</font></li>
</ul><li style="color:rgb(135,135,135);font-size:13px;line-height:1.5;margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a"><strong>Novel applications of scalable machine learning in big data</strong></font></li>
<ul style="color:rgb(135,135,135);font-size:13px;line-height:1.5;overflow:hidden;padding-left:2.3em!important;margin:5px 0px!important;list-style:disc outside!important"><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important">
<font size="3" color="#2a2a2a">Decision making with big data</font></li><li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">Counterfactual reasoning with big data</font></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><font size="3" color="#2a2a2a">M</font><span style="color:rgb(42,42,42);font-size:medium;line-height:1.5;background-color:initial">edical/health informatics big data analysis</span></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><span style="color:rgb(42,42,42);font-size:medium;line-height:1.5;background-color:initial">S</span><span style="color:rgb(42,42,42);font-size:medium;line-height:1.5;background-color:initial">ecurity big data analysis</span></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><span style="color:rgb(42,42,42);font-size:medium;line-height:1.5;background-color:initial">Astronomy big data analysis</span></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><span style="color:rgb(42,42,42);font-size:medium;line-height:1.5;background-color:initial">Biological big data analysis</span></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><span style="color:rgb(42,42,42);font-size:medium;line-height:1.5;background-color:initial">Urban/smart city big data analysis</span></li>
<li style="margin:3px 0px 0px!important;padding-left:5px!important;list-style:disc outside!important"><span style="color:rgb(42,42,42);font-size:medium;line-height:1.5;background-color:initial">Education big data analysis </span></li>
</ul></ul><div><h2 style="font-family:Glegoo,'Myriad Pro',Arial,Helvetica,sans-serif;font-size:24px;margin:0px;padding:0.3em 0px;line-height:1.2;font-weight:normal;color:rgb(143,197,99)"><font color="#2a2a2a" size="4"><u><strong>Important Dates</strong></u></font></h2>
<div><ul type="disc"><li class="MsoNormal" style="margin-left:15px;text-align:left;background-image:initial;background-repeat:initial"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">August 30, 2014: Due date for workshop paper submission</span><span lang="EN-US" style="font-size:11pt;font-family:Arial,sans-serif"></span></li>
<li class="MsoNormal" style="margin-left:15px;text-align:left;background-image:initial;background-repeat:initial"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">September 20, 2014: Notification of paper decision to authors</span><span lang="EN-US" style="font-size:11pt;font-family:Arial,sans-serif"></span></li>
<li class="MsoNormal" style="margin-left:15px;text-align:left;background-image:initial;background-repeat:initial"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">October 5, 2014: Camera-ready of accepted papers</span><span lang="EN-US" style="font-size:11pt;font-family:Arial,sans-serif"></span></li>
<li class="MsoNormal" style="margin-left:15px;text-align:left;background-image:initial;background-repeat:initial"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">October 27-30, 2014: Workshop</span><span lang="EN-US" style="font-size:11pt;font-family:Arial,sans-serif"></span></li>
</ul></div><div><h2 style="font-family:Glegoo,'Myriad Pro',Arial,Helvetica,sans-serif;font-size:24px;margin:0px;padding:0.3em 0px;line-height:1.2;font-weight:normal;color:rgb(143,197,99)"><font color="#2a2a2a" size="4"><u><strong>Paper Sub</strong></u></font><u style="color:rgb(42,42,42);font-size:large;line-height:1.2"><strong>mission</strong></u></h2>
</div><div><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif;background-image:initial;background-repeat:initial"><font color="#000000">      We call for original and unpublished research contributions of (up to 8 pages and IEEE double-column format) manuscripts to the workshop. Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see the link to "</font><a href="http://www.ieee.org/conferences_events/conferences/publishing/templates.html" title="" target="_blank"><span style="text-decoration:none"><font color="#0000ff">Paper Format</font></span></a><font color="#000000">") and submitted to the </font></span><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif;background-image:initial;background-repeat:initial"><a href="https://wi-lab.com/cyberchair/2014/bigdata14/scripts/submit.php?subarea=S2&undisplay_detail=1&wh=/cyberchair/2014/bigdata14/scripts/ws_submit.php" title="" target="_blank"><span style="text-decoration:none"><font color="#0000ff">Submission Website</font></span></a></span><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif;color:black;background-image:initial;background-repeat:initial">.</span><br>
</div></div><div><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif;color:black;background-image:initial;background-repeat:initial"><br></span></div><div><h2 style="font-family:Glegoo,'Myriad Pro',Arial,Helvetica,sans-serif;font-size:24px;margin:0px;padding:0.3em 0px;line-height:1.2;font-weight:normal;color:rgb(143,197,99)">
<font color="#2a2a2a" size="4"><u><strong>Keynote Talks</strong></u></font></h2></div><div><ul style="font-family:Glegoo,'Myriad Pro',Arial,Helvetica,sans-serif;font-size:24px;line-height:28.799999237060547px"><li style="margin-left:15px">
<a href="http://research.microsoft.com/en-us/um/people/mbilenko/" title="" target="_blank" style="font-size:medium;text-decoration:none;background-color:initial"><font color="#0000ff">Mikhail Bilenko</font></a><font color="#000000" style="font-size:medium;background-color:initial">, Microsoft Research</font><br>
</li><li style="margin-left:15px"><a href="http://www.cs.cmu.edu/~epxing/" title="" target="_blank" style="font-size:medium;text-decoration:none;background-color:initial"><font color="#0000ff">Eric Xing</font></a><font color="#000000" style="font-size:medium;background-color:initial">, Carnegie Mellow University</font><br>
</li><li style="margin-left:15px"><a href="http://www.stat.rutgers.edu/home/pingli/" title="" target="_blank" style="font-size:medium;text-decoration:none;background-color:initial"><font color="#0000ff">Ping Li</font><font color="#6193b5">,</font></a><font color="#000000" style="font-size:medium;background-color:initial"> Rutgers University</font><br>
</li></ul><u style="font-family:Glegoo,'Myriad Pro',Arial,Helvetica,sans-serif;color:rgb(42,42,42);font-size:large;line-height:1.2;background-color:initial"><strong>Organizing Committee</strong></u><span style="color:rgb(0,0,0);font-size:medium;font-family:Glegoo,'Myriad Pro',Arial,Helvetica,sans-serif;line-height:28.799999237060547px"> </span><ul style="font-family:Glegoo,'Myriad Pro',Arial,Helvetica,sans-serif;font-size:24px;line-height:28.799999237060547px">
<li style="margin-left:15px"><span style="line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif"><a href="https://www.cs.purdue.edu/homes/xu218/" title="" target="_blank"><span style="text-decoration:none"><font color="#0000ff">Zenglin Xu</font></span></a></span></span><span style="line-height:14.65pt;color:rgb(0,0,0);font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif;color:rgb(135,135,135)">,</span></span><span lang="EN-US" style="line-height:14.65pt;color:rgb(0,0,0);font-size:12pt;font-family:Arial,sans-serif;background-image:initial;background-repeat:initial"> University of Electronic Science and Technology of China & Purdue University</span><br>
</li><ul type="disc"><font size="3"><font color="#000000"></font></font></ul><li style="margin-left:15px"><span style="line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif"><a href="http://appsrv.cse.cuhk.edu.hk/~hqyang/doku.php" title="" target="_blank"><span style="text-decoration:none"><font color="#0000ff">Haiqin Yang</font></span></a></span></span><span style="color:rgb(135,135,135);line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">, </span></span><span lang="EN-US" style="line-height:14.65pt;font-size:12pt;font-family:Arial,sans-serif;color:black;background-image:initial;background-repeat:initial">The Chinese University of Hong Kong</span><br>
</li><ul type="disc"><font size="3"><font color="#000000"></font></font></ul><li style="margin-left:15px"><span style="line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif"><a href="http://www.cse.cuhk.edu.hk/~king" title="" target="_blank"><span style="text-decoration:none"><font color="#0000ff">Irwin King</font></span></a></span></span><span style="color:rgb(135,135,135);line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">, </span></span><span lang="EN-US" style="line-height:14.65pt;font-size:12pt;font-family:Arial,sans-serif;color:black;background-image:initial;background-repeat:initial">The Chinese University of Hong Kong</span><br>
</li><ul type="disc"><font size="3"><font color="#000000"></font></font></ul><li style="margin-left:15px"><span style="line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif"><a href="http://www.cse.cuhk.edu.hk/~lyu" title="" target="_blank"><span style="text-decoration:none"><font color="#0000ff">Michael R. Lyu</font></span></a></span></span><span style="color:rgb(135,135,135);line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">,</span></span><span lang="EN-US" style="line-height:14.65pt;font-size:12pt;font-family:Arial,sans-serif;color:black;background-image:initial;background-repeat:initial"> The Chinese University of Hong Kong</span><br>
</li><ul type="disc"><font size="3"><font color="#000000"></font></font></ul><li style="margin-left:15px"><span style="line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif"><a href="http://research.microsoft.com/en-us/people/lihongli/" title="" target="_blank"><span style="text-decoration:none"><font color="#0000ff">Lihong Li</font></span></a></span></span><span style="color:rgb(135,135,135);line-height:14.65pt;font-size:medium"><span lang="EN-US" style="font-size:12pt;font-family:Arial,sans-serif">, </span></span><span lang="EN-US" style="line-height:14.65pt;font-size:12pt;font-family:Arial,sans-serif;color:black;background-image:initial;background-repeat:initial">Microsoft Research </span></li>
</ul></div></div></div></div></div>