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    <title>Archetypal Analysis Lab</title>

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        <h1>aalab</h1>

	<p>aalab
	is <a href="https://github.com/aalab?tab=members">our</a>
	place to do research on archetypal analysis.</p>

	<p><class="view"><a href="https://github.com/aalab">View
	GitHub repositories</a></p>
       </header>

      <section>
	<p>
	  The <a href="http://www.merriam-webster.com/dictionary/archetype">Merriam-Webster
	    Online Dictionary</a> defines an archetype as the original
	  pattern or model of which all things of the same type are
	  representations or copies. Then, the aim of the archetypal
	  analysis is to find the "pure types", the archetypes, within a
	  set defined in a specific context. The concept of archetypes
	  is used in many different areas, the set can be defined in
	  terms of literature, philosophy, psychology and also
	  statistics. Here, the concrete problem is to find a few, not
	  necessaily observed, points (archetypes) in a set of
	  multivariate observations such that all the data can be well
	  represented as convex mixtures of the archetypes.
	</p>


	<h5>Probabilistic formulation</h5>

	<p>
	  <img class="blockImg" src="images/naa.png">
	  <div class="blockTxt">
	    <em> Archetypal analysis for nominal observations</em><br/>
	    Sohan Seth and Manuel J. A. Eugster. IEEE Transactions on
	    Pattern Analysis and Machine Intelligence, to appear.<br/>
	    [
	    <a href="http://dx.doi.org/10.1109/TPAMI.2015.2470655">URL</a> |
	    <a href="https://github.com/aalab/naa/">Code</a>
	    ]
	  </div>
	</p>

	<p>
	  <img class="blockImg" src="images/paa.png">
	  <div class="blockTxt">
	    <em>Probabilistic archetypal analysis</em><br/>
	    Sohan Seth and Manuel J. A. Eugster. Machine Learning, to
	    appear.<br/>
	    [
	    <a href="http://link.springer.com/article/10.1007%2Fs10994-015-5498-8">URL</a> |
	    <a href="http://arxiv.org/abs/1312.7604">Preprint</a> |
	    <a href="https://github.com/aalab/paa/">Code</a>
	    ]
	  </div>
	</p>


	<h5>Original algorithm and extensions</h5>

	<p>
	  <img class="blockImg" src="images/robust.png">
	  <div class="blockTxt">
	    <em>Weighted and robust archetypal analysis</em><br/>
	    Manuel J. A. Eugster and Friedrich Leisch. Computational
	    Statistics and Data Analysis, 55(3):1215-1225, 2011.<br/>
	    [
	    <a href="http://dx.doi.org/10.1016/j.csda.2010.10.017">PDF</a> |
	    <a href="http://epub.ub.uni-muenchen.de/11498/">Preprint</a> |
	    <a href="http://archetypes.r-forge.r-project.org/">R package</a>
	    ]
	  </div>
	</p>

	<p>
	  <img class="blockImg" src="images/atypes.png">
	  <div class="blockTxt">
	    <em>From Spider-man to Hero -- Archetypal analysis in R</em><br/>
	    Manuel J. A. Eugster and Friedrich Leisch. Journal of
	    Statistical Software, 30(8):1-23, 2009.<br/>
	    [
	    <a href="http://www.jstatsoft.org/v30/i08">PDF</a> |
	    <a href="http://archetypes.r-forge.r-project.org/">R package</a>
	    ]
	  </div>
	</p>
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