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	<title>Michael P. Verdicchio &#187; Statistical Relational Learning</title>
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		<title>Statistical Relational Learning</title>
		<link>http://www.michaelverdicchio.com/2008/04/05/statistical-relational-learning/</link>
		<comments>http://www.michaelverdicchio.com/2008/04/05/statistical-relational-learning/#comments</comments>
		<pubDate>Sat, 05 Apr 2008 19:33:19 +0000</pubDate>
		<dc:creator>Michael</dc:creator>
				<category><![CDATA[Bayesian Networks]]></category>
		<category><![CDATA[Graphical Models]]></category>
		<category><![CDATA[Probabilistic Networks]]></category>
		<category><![CDATA[Statistical Relational Learning]]></category>

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		<description><![CDATA[This semester we’ve covered a number of topics in Sungwook Yoon’s Statistical Relational Learning reading group. My turn came a couple of weeks ago and I presented Bayesian Logic Programming. It is essentially a methodology which combines the structural conveniences of Bayesian networks and the theorem proving aspects of logic programming. The chapter in the [...]]]></description>
			<content:encoded><![CDATA[<p>This semester we’ve covered a number of topics in Sungwook Yoon’s <a href="http://www.public.asu.edu/%7Esyoon10/StatisticalRelationalLearning.html">Statistical Relational Learning reading group</a>. My turn came a couple of weeks ago and I presented Bayesian Logic Programming. It is essentially a methodology which combines the structural conveniences of Bayesian networks and the theorem proving aspects of logic programming. The chapter in the Getoor/Taskar text was not especially liked in the group as it lacked, among a number of things, specific examples of its use and advantages; in other words, we didn’t know WHY we should use such a framework, only that it was an interesting hybrid of two seemingly separate methodologies. Nonetheless, my slides are below.</p>
<p>Slides (<a href="http://www.michaelverdicchio.com/talks/Bayesian%20Logic%20Programming%20MV.ppt">ppt</a>)</p>
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		<title>Probabilistic Graphical Models</title>
		<link>http://www.michaelverdicchio.com/2008/02/01/probabilistic-graphical-models/</link>
		<comments>http://www.michaelverdicchio.com/2008/02/01/probabilistic-graphical-models/#comments</comments>
		<pubDate>Fri, 01 Feb 2008 19:31:56 +0000</pubDate>
		<dc:creator>Michael</dc:creator>
				<category><![CDATA[Bayesian Networks]]></category>
		<category><![CDATA[Graphical Models]]></category>
		<category><![CDATA[Probabilistic Networks]]></category>
		<category><![CDATA[Statistical Relational Learning]]></category>

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		<description><![CDATA[In my Statistical Relational Learning reading group I have a few slides to chirp in with regarding joint probabilities in Bayesian Networks.  The first slide show has a brief synopsis of what a Bayes net is, and then has a simple probability factorization example.  The second set of slides just lists some different application areas [...]]]></description>
			<content:encoded><![CDATA[<p>In my <a href="http://www.public.asu.edu/%7Esyoon10/StatisticalRelationalLearning.html" target="_blank">Statistical Relational Learning reading group</a> I have a few slides to chirp in with regarding joint probabilities in Bayesian Networks.  The first slide show has a brief synopsis of what a Bayes net is, and then has a simple probability factorization example.  The second set of slides just lists some different application areas where Bayes nets are in use.  It focuses on biologically related areas, and then summarizes one paper.  Another student is giving the bulk of the talk.</p>
<p>Bayesian Network Example (<a href="http://www.michaelverdicchio.com/talks/Bayesian%20Network%20Example.ppt" target="_blank">ppt</a>)</p>
<p>Bayesian Networks in Use (<a href="http://www.michaelverdicchio.com/talks/Bayesian%20Networks%20in%20Use.ppt" target="_blank">ppt</a>)</p>
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