Monday, February 24, 2014 - 14:00 , Location: Skiles 005 , Le Song , Georgia Tech CSE , Organizer: Martin Short
Dynamical processes, such as information diffusion in social networks, gene regulation in biological systems and functional collaborations between brain regions, generate a large volume of high dimensional “asynchronous” and “interdependent” time-stamped event data. This type of timing information is rather different from traditional iid. data and discrete-time temporal data, which calls for new models and scalable algorithms for learning, analyzing and utilizing them. In this talk, I will present methods based on multivariate point processes, high dimensional sparse recovery, and randomized algorithms for addressing a sequence of problems arising from this context. As a concrete example, I will also present experimental results on learning and optimizing information cascades in web logs, including estimating hidden diffusion networks and influence maximization with the learned networks. With both careful model and algorithm design, the framework is able to handle millions of events and millions of networked entities.
Monday, February 17, 2014 - 14:00 , Location: Skiles 005 , Junshan Lin , Auburn University , Organizer: Haomin Zhou
Resonances are important in the study of transient phenomenaassociated with the wave equation, especially in understanding the largetime behavior of the solution to the wave equation when radiation lossesare small. In this talk, I will present recent studies on the scatteringresonances for photonic structures and Schrodinger operators. I will beginwith a study on the finite symmetric photoinc structure to illustrate theconvergence behavior of resonances. Then a general perturbation approachwill be introduced for the analysis of near bound-state resonances for bothcases. In particular, it is shown that, for a finite one dimensionalphotonic crystal with a defect, the near bound-state resonances converge tothe point spectrum of the infinite structure with an exponential rate whenthe number of periods increases. An analogous exponential decay rate alsoholds for the Schrodinger operator with a potential function that is alow-energy well surrounded by a thick barrier. The analysis also leads to asimple and accurate numerical approach to approximate the near bound-stateresonances. This is a joint work with Prof. Fadil Santosa in University ofMinnesota.
Wednesday, December 4, 2013 - 14:00 , Location: Skiles 005 , Prof. Riccardo March , Istituto per le Applicazioni del Calcolo "Mauro Picone" of C.N.R and University of Rome , Organizer: Sung Ha Kang
We consider a variational model for image segmentation which takes into account the occlusions between different objects. The model consists in minimizing a functional which depends on: (i) a partition (segmentation) of the image domain constituted by partially overlapping regions; (ii) a piecewise constant function which gives information about the visible portions of objects; (iii) a piecewise constant function which constitutes an approximation of a given image. The geometric part of the energy functional depends on the curvature of the boundaries of the overlapping regions. Some variational properties of the model are discussed with the aim of investigating the reconstruction capabilities of occluded boundaries of shapes. Joint work with Giovanni Bellettini.
Tuesday, November 5, 2013 - 11:00 , Location: Skiles 006 , Ha Quang, Minh , Istituto Italiano di Technologia (IIT), Genova, Italy , email@example.com , Organizer: Sung Ha Kang
Reproducing kernel Hilbert spaces (RKHS) have recently emerged as a powerful mathematical framework for many problems in machine learning, statistics, and their applications. In this talk, we will present a formulation in vector-valued RKHS that provides a unified treatment of several important machine learning approaches. Among these, one is Manifold Regularization, which seeks to exploit the geometry of the input data via unlabeled examples, and one is Multi-view Learning, which attempts to integrate different features and modalities in the input data. Numerical results on several challenging multi-class classification problems demonstrate the competitive practical performance of our approach.
Monday, November 4, 2013 - 14:05 , Location: Skiles 005 , Chad Higdon-Topaz , Macalester College , Organizer: Martin Short
From bird flocks to ungulate herds to fish schools, nature abounds with examples of biological aggregations that arise from social interactions. These interactions take place over finite (rather than infinitesimal) distances, giving rise to nonlocal models. In this modeling-based talk, I will discuss two projects on insect swarms in which nonlocal social interactions play a key role. The first project examines desert locusts. The model is a system of nonlinear partial integrodifferential equations of advection-reaction type. I find conditions for the formation of an aggregation, demonstrate transiently traveling pulses of insects, and find hysteresis in the aggregation's existence. The second project examines the pea aphid. Based on experiments that motion track aphids walking in a circular arena, I extract a discrete, stochastic model for the group. Each aphid transitions randomly between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid’s nearest neighbor. For large nearest neighbor distances, when an aphid is isolated, its motion is ballistic and it is less likely to stop. In contrast, for short nearest neighbor distances, aphids move diffusively and are more likely to become stationary; this behavior constitutes an aggregation mechanism.
Monday, October 28, 2013 - 14:00 , Location: Skiles 005 , Francesco G. Fedele , GT Civil Eng and ECE , firstname.lastname@example.org , Organizer: Sung Ha Kang
Rogue waves are unusually large waves that appear from nowhere at the ocean. In the last 10 years or so, they have been the subject of numerous studies that propose homoclinic orbits of the NLS equation, the so-called breathers, to model such extreme events. Clearly, the NLS equation is an asymptotic approximation of the Euler equations in the spectral narrowband limit and it does not capture strong nonlinear features of the full Euler model. Motivated by the preceding studies, I will present recent results on deep-water modulated wavetrains and breathers of the Hamiltonian Zakharov equation, higher-order asymptotic model of the Euler equations for water waves. They provide new insights into the occurrence and existence of rogue waves and their breaking. Web info: http://arxiv.org/abs/1309.0668
Monday, October 21, 2013 - 14:00 , Location: Skiles 005 , Jeff Geronimo , GT Math , Organizer: Sung Ha Kang
The Alpert multiwavelets are an extension of the Haar wavelet to higher degree piecewise polynomials thereby giving higher approximation order. This system has uses in numerical analysis in problems where shocks develop. An orthogonal basis of scaling functions for this system are the Legendre polynomials and we will examine the consequence of this. In particular we will show that the coefficients in the refinement equation can be written in terms of Jacobi polynomials with varying parameters. Difference equationssatisfied by these coefficients will be exhibited that give rise to generalized eigenvalue problems. Furthermore an orthogonal basis of wavelet functions will be discussed that have explicit formulas as hypergeometric polynomials.
Monday, September 9, 2013 - 14:00 , Location: Skiles 005 , Seong Jun Kim , GT Math , Organizer: Sung Ha Kang
The main aim of this talk is to design efficient and novel numerical algorithms for highly oscillatory dynamical systems with multiple time scales. Classical numerical methods for such problems need temporal resolution to resolve the finest scale and become very inefficient when the longer time intervals are of interest. In order to accelerate computations and improve the long time accuracy of numerical schemes, we take advantage of various multiscale structures established from a separation of time scales. The framework of the heterogeneous multiscale method (HMM) will be considered as a general strategy both for the design and for the analysis of multiscale methods.(Keywords: Multiscale oscillatory dynamical systems, numerical averaging methods.)
Monday, April 22, 2013 - 14:00 , Location: Skiles 005 , Prof. Seyed Moghadas , York University , Organizer: Haomin Zhou
Modelling and computational approaches provide powerful tools in the study of disease dynamics at both the micro- and macro-levels. Recent advances in information and communications technologies have opened up novel vistas and presented new challenges in mathematical epidemiology. These challenges are central to the understanding of the collective dynamics of heterogeneous ensembles of individuals, and analyzing pertinent data that are less coarse and more complex. The evolution of dynamic modelling is typified by the agent-based modelling (ABM) as a shifting paradigm, a lattice-distributed collection of autonomous decision-making entities (i.e., agents), the interactions of which unveil the dynamics and emergent properties of a real-life problem, such as an infectious disease outbreak. In this talk, we show a general framework for developing an ABM that can be used to computationally optimize intervention strategies for novel influenza viruses with pandemic potential. Our findings contrast previous results !
Monday, April 15, 2013 - 14:05 , Location: Skiles 005 , Alexander Kurganov , Tulane University , Organizer: Yingjie Liu
I will first give a brief review on simple and robust central-upwind schemes for hyperbolic conservation laws. I will then discuss their application to the Saint-Venant system of shallow water equations. This can be done in a straightforward manner, but then the resulting scheme may suffer from the lack of balance between the fluxes and (possibly singular) geometric source term, which may lead to a so-called numerical storm, and from appearance of negative values of the water height, which may destroy the entire computed solution. To circumvent these difficulties, we have developed a special technique, which guarantees that the designed second-order central-upwind scheme is both well-balanced and positivity preserving. Finally, I will show how the scheme can be extended to the two-layer shallow water equations and to the Savage-Hutter type model of submarine landslides and generated tsunami waves, which, in addition to the geometric source term, contain nonconservative interlayer exchange terms. It is well-known that such terms, which arise in many different multiphase models, are extremely sensitive to a particular choice their numerical discretization. To circumvent this difficulty, we rewrite the studied systems in a different way so that the nonconservative terms are multiplied by a quantity, which is, in all practically meaningful cases, very small. We then apply the central-upwind scheme to the rewritten system and demonstrate robustness and superb performance of the proposed method on a number numerical examples.