Week of November 28, 2011 - December 2, 2011 Monday, November 28, 2011 1:30 PM Advisory Committee Meeting 400 MSC 3:30 PM Education Seminar 459 MSC Craig L. Zirbel, BGSU Developing materials for 1000-level mathematics classes I would like to discuss making it our mission to develop high-quality activities and methods to be used in 1000-level math/stat classes. Examples of activities that are already being used are the Random Rectangles activity in Math 1150 and an activity in which students discover properties of logarithms themselves in Math 1220. I think we can design things that are so good that everyone teaching will want to use them. Well-designed activities can improve student learning and attendance in classes. They make it easier for new TAs to get away from lecturing. If we assess their effectiveness and improve them afterward, the materials get better, our students learn more, and all of us gain experience with the paradigm of constant assessment and improvement. TAs who participate in the development and improvement process should get better teaching jobs when they graduate. In my mind, the main thing is to get organized and be deliberate. The more of this we do, the easier teaching becomes, especially if we work together. Tuesday, November 29, 2011 3:45 PM Faculty Meeting 459 MSC Unit-Level Strategic Plan Wednesday, November 30, 2011 3:30 PM Analysis Seminar 459 MS Dr. Yun-Su Kim, University of Toledo Hilbert Spaces with respect to Operator-Valued Norm We introduce two kinds of operator-valued norms. One of them is an L(H)-valued norm. The other one is an L(C(K))-valued norm. We provide the notion of a Hilbert space with respect to an L(H)-valued norm. By a Hilbert space with respect to an L(H)-valued norm, we generalize the notion of a Hilbert space. Furthermore, we provide several interesting examples (L-infinity and C(Y)) of Hilbert spaces with respect to an operator-valued norm. Thursday, December 1, 2011 10:45 AM Math 1210 Instructor Meeting 459 MSC 11:30 AM Math 1220 Instructor Meeting 400 MSC 1:30 PM Math 1260 Instructor Meeting 400 MSC Friday, December 2, 2011 2:30 PM Presidential Inauguration Stroh Center Robing by 1:45 PM 3:30 PM Refreshments 3:45 PM Colloquium 459 MSC Dr. Xiaoli Gao, Oakland University, Michigan Estimation and Selection Properties of the LAD Fused Lasso Signal Approximator The fused lasso is an important method for signal processing when the hidden signals are sparse and blocky. It is often used in combination with the squared loss function. However, the squared loss is not suitable for heavy tail error distributions nor is robust against outliers which arise often in practice. The least absolute deviations (LAD) loss provides a robust alternative to the squared loss. In this paper, we study the asymptotic properties of the fused lasso estimator with the LAD loss for signal approximation. We refer to this estimator as the LAD fused lasso signal approximator, or LAD-FLSA. We investigate the estimation consistency properties of the LAD-FLSA and provide sufficient conditions under which the LAD-FLSA is sign consistent. We also construct an unbiased estimator for the generalized degrees of freedom (GDF) of the LAD-FLSA for any given tuning parameters. Both simulation studies and real data analysis are conducted to illustrate the performance of the LAD-FLSA and the effect of the unbiased estimator of GDF.
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