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<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>WHAT:<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>Amir Globerson:
"Message Passing and Inference - A Dual Perspective"<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'><o:p> </o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>WHEN:<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>Mon Nov 26 12:30pm - Mon Nov
26 1:30pm<o:p></o:p></span></font></p>
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style='font-size:10.0pt;font-family:"Courier New"'><o:p> </o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>WHERE:<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>TTI-C conference room<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'><o:p> </o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>ABSSTRACT:<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>Graphical models are a
powerful tool for representing distributions over complex multivariate objects
such as images or documents. Although graphical models have been used with
considerable success in many domains, such as machine vision and signal
processing, it is theoretically NP hard to infer even simple model properties,
such as the marginals over single variables, or the most likely assignment.
This difficulty has been addressed in practice by designing approximate
inference algorithms (such as belief propagation) that often work well in
practice, although with relatively weak theoretical guarantees.<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'><o:p> </o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>In this work we use the
notion of convex duality to design a class of message passing algorithms that
solve convex variational formulations of inference problems. Specifically, we
use the geometric and linear programming duals of two variational
approximations, and show that coordinate ascent on these duals yields a convergent
message passing algorithm.<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'><o:p> </o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>We illustrate the
performance of our new algorithms on various problems, and show that they
converge in cases where message passing algorithms such as max product do not.<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'><o:p> </o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>Host: Nati Srebro<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'><o:p> </o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2 face="Courier New"><span
style='font-size:10.0pt;font-family:"Courier New"'>Contact host at
nati@tti-c.org to be placed on the speaker's schedule.<o:p></o:p></span></font></p>
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font-family:Arial'><o:p> </o:p></span></font></p>
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font-family:Arial'><o:p> </o:p></span></font></p>
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12.0pt'><o:p> </o:p></span></font></p>
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