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Statistics and Data Science Seminar Tracy Ke (Harvard University)

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Statistics and Data Science Seminar Will Perkins (University of Illinois at Chicago)

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Learning for Dynamics and Control (L4DC)

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Optimal Adaptivity of Signed-Polygon Statistics for Network Testing (Tracy Ke, Harvard University)

Tracy Ke (Harvard University)
E18-304

Abstract: Given a symmetric social network, we are interested in testing whether it has only one community or multiple communities. The desired tests should (a) accommodate severe degree heterogeneity, (b) accommodate mixed-memberships, (c) have a tractable null distribution, and (d) adapt automatically to different levels of sparsity, and achieve the optimal detection boundary. How to…

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Counting and sampling at low temperatures

Will Perkins (University of Illinois at Chicago)
E18-304

Abstract: We consider the problem of efficient sampling from the hard-core and Potts models from statistical physics. On certain families of graphs, phase transitions in the underlying physics model are linked to changes in the performance of some sampling algorithms, including Markov chains. We develop new sampling and counting algorithms that exploit the phase transition…

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Learning for Dynamics and Control (L4DC)

32-123

Over the next decade, the biggest generator of data is expected to be devices which sense and control the physical world. This explosion of real-time data that is emerging from the physical world requires a rapprochement of areas such as machine learning, control theory, and optimization. While control theory has been firmly rooted in tradition…

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Learning for Dynamics and Control (L4DC)

32-123

Over the next decade, the biggest generator of data is expected to be devices which sense and control the physical world. This explosion of real-time data that is emerging from the physical world requires a rapprochement of areas such as machine learning, control theory, and optimization. While control theory has been firmly rooted in tradition…

Find out more »


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