Colloquium/Seminar

YearMonth
2017 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Oct   Nov   Dec  
2016 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Oct   Nov   Dec  
2015 Jan   Feb   Mar   Apr   May   Jun   Aug   Sep   Oct   Nov   Dec  
2014 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec  
2013 Jan   Feb   Mar   Apr   May   Jun   Aug   Sep   Nov   Dec  
2012 Jan   Feb   Apr   May   Jun   Jul   Aug   Sep   Nov   Dec  
2011 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec  
2010 Jan   Feb   Mar   Apr   May   Jun   Sep   Oct   Nov   Dec  
2009 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec  
2008 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec  
2007 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec  
2006 Jan   Feb   Mar   Apr   May   Jun   Jul   Sep   Oct   Nov   Dec  
2005 Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec  
2004 Jan   Feb   Mar   Apr   May   Aug   Sep   Oct   Nov   Dec  

Event(s) on December 2010


  • Friday, 10th December, 2010

    Title: Generalized Linear Discriminant Analysis For Undersampled Problems
    Speaker: Prof. Delin CHU, Department of Mathematics, National University of Singapore, Singapore
    Time/Place: 11:30  -  12:30
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: Dimensionality reduction has become an ubiquitous preprocessing step in many applications. Linear discriminant analysis (LDA) has been known to be one of the most optimal dimensionality reduction methods for classification. However, a main disadvantage of LDA is that the so-called "total scatter matrix" must be nonsingular. But, in many applications, the scatter matrices can be singular since the data points are from a very high-dimensional space and thus usually the number of the data samples is smaller than the data dimension. This is known as the undersampled problem. Many generalized LDA methods have been proposed in the past to overcome this singularity problem. There is a commonality for these generalized LDA methods, that is, they compute the optimal linear transformations by computing some eigen-decompositions and involving some matrix inversions. However, the eigen-decomposition is computationally expensive, and the involvement of matrix inverses may lead to that the methods are not numerically stable if the associated matrices are ill-conditioned. Hence, many existing LDA methods have high computational cost and potentially numerical instability problems. In this talk we introduce a new orthogonal LDA method for the undersampled problem. The main features of the introduced orthogonal LDA method include: (i) the optimal transformation matrix is obtained easily by only orthogonal transformations without computing any eigen-decomposition and matrix inverse, and consequently, the new method is inverse-free and numerically stable; (ii) the new method is implemented by using several QR factorizations and is a fast one. The effectiveness of the new method is illustrated by some real-world data sets.


  • Tuesday, 14th December, 2010

    Title: Nonregular Designs: A Better Choice for Experiments
    Speaker: Dr. Frederick Kin Hing PHOA, Institute of Statistical Science, Academia Sinica, Taiwan
    Time/Place: 11:30  -  12:30
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: In the recent past, there was a realization that nonregular designs could be utilized in conducting efficient experiments with flexibility, run size economy, and ability to exploit interactions. The first part of this talk discusses about the advantages on using nonregular designs over regular designs when an experiment is conducted. Several real-life examples are given for reference. These explicit advantages led to a growing research on developing a general construction methodology of nonregular designs with good properties. Recent research indicates that designs constructed from quaternary codes (QC) are very promising. The second part of this talk introduces the construction of nonregular designs via quaternary codes. The properties of QC designs are formulated and optimized using some formulas, bypassing the tedious calculation of J-characteristics. In the last part of this talk, several tables compare the design properties between QC designs and the best regular designs in the literature. The comparisons show that QC designs have better design properties and therefore, QC designs are more cost-efficient than regular designs of the same size.


  • Friday, 17th December, 2010

    Title: Variational methods and their application on image processing
    Speaker: Dr. MAO Yu, Institute for Mathematics and Its Applications, University of Minnesota, USA
    Time/Place: 11:30  -  12:30
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: Variational PDE based methods in digital image processing have been well developed and studied for the past twenty years. These methods were soon applied to image reconstruction problems. In this talk I will explore some interesting applications of these methods as well as the challenges in this field.


  • Monday, 20th December, 2010

    Title: GPU Based Fluid Simulations
    Speaker: Mr. ZHANG Yubo, Department of Computer Science, University of California, Davis , USA
    Time/Place: 16:30  -  17:30
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: In this talk, I will introduce the basic architecture and thead models of modern GPUs. An example of GPU-based fluid simulation will be presented. Some optimization techniques for GPU-based finite difference computation will also be dicussed.


  • Tuesday, 21st December, 2010

    Title: Local absorbing boundary conditions for two-dimensional nonlinear wave equation
    Speaker: Mr. LI Hongwei, Department of Mathematics, Hong Kong Baptist University, Hong Kong SAR
    Time/Place: 15:30  -  16:30
    FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
    Abstract: In this talk, we consider the numerical solution of two-dimensional nonlinear wave equation on unbounded spatial domain. One of the difficulties is how to reduce the unbounded spatial problem to a bounded one. Using the idea of operator splitting method, here we construct the efficient local absorbing boundary conditions for the nonlinear wave equation on artificial boundary. Several numerical examples are provided to demonstrate the effectiveness of our method.