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Event(s) on March 2010
- Tuesday, 2nd March, 2010
| Title: |
Shape invariant modeling pricing kernels and risk aversion |
| Speaker: |
Prof. Wolfgang Hardle, Centre for Applied Statistics & Economics, School of Business and Economics, Humboldt-Universität zu Berlin, Germany |
| Time/Place: |
11:30 - 12:30
FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
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| Abstract: |
Pricing kernels play a major role in quantifying risk aversion
and investors’ preferences. Several empirical studies reported
that pricing kernels exhibit a common pattern across different
markets. Mostly visual inspection and occasionally numerically
summarize are used to make comparison. With increasing amount
of information updated every day, the empirical pricing kernels
can be viewed as an object evolving over time. We propose a systematic
modeling approach to describing the evolution of the empirical
pricing kernels. The approach is based on shape invariant models.
It captures the common features contained in the shape of the
functions and at the same time characterizes the variability
between the pricing kernels based on a few interpretable parameters.
The method is demonstrated with the European options and returns
values of DAX index.
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- Wednesday, 3rd March, 2010
| Title: |
Applications of Semismooth Newton method for nonsmooth variational problems |
| Speaker: |
Kazufumi Ito, Department of Mathematics, North Carolina State University, USA |
| Time/Place: |
11:30 - 12:30
FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
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| Abstract: |
Applications and analysis of the semismooth Newton method for
non-smooth equations associated with a general class of nonsmooth
variational problems will be presented. The semismmooth Newton
method is a generalized Newton method for a class of the Lipschitz
but not $C^1$ equations in Banach spaces. It has been used to
solve non-smooth equations that arise in the constrained optimization,
variational inequality, contact and friction problems and mathematical
finance, and numerical partial differential equations. In the
case of the variational problem the nonsmooth equation is reduced
from the necessary optimality condition for minimizing the cost
functional involving $L^1$, $L^infty$ and $TV$ (total variation)
norms and/or subject to the point-wise constraint of the solution
and its gradient. In the image analysis and the control problem
the $L^1$ norm is used to obtain the spike and impulsive solutions
and $TV$ norm is used to capture the edge and the discontinuity
in the image. A robust algorithm based on the primal and dual
variable and the semismooth Newton is developed and analyzed.
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- Wednesday, 3rd March, 2010
| Title: |
CMIV Colloquium: Prediction of protein-RNA binding sites by a random forest method with combined features |
| Speaker: |
Prof. Luonan Chen, Osaka Sangyo University, Japan |
| Time/Place: |
17:00 - 18:00
DLB514, David C. Lam Building, Shaw Campus, Hong Kong Baptist University
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| Abstract: |
In this work, we propose a novel classification method to identify
the RNA binding sites in proteins by combining a new interacting
feature (interaction propensity) with other sequence and structure
based features. Specifically, the interaction propensity represents
a binding specificity of a protein residue to the interacting
RNA nucleotide by considering its two-side neighborhood in a
protein residue triplet. The sequence as well as the structure
based features of the residues are combined together to discriminate
the interaction propensity of amino acids with RNA. We predict
RNA interacting residues in proteins by implementing a well-built
random forest classifier. The experiments show that our method
is able to detect the annotated protein-RNA interaction sites
in a high accuracy. Our method achieves an accuracy of 84.5%,
F-measure of 0.85, and AUC of 0.92 prediction of the RNA-binding
residues for a dataset containing 205 non-homologous RNA-binding
proteins, and also outperforms the existing methods in the comparison
study. Furthermore, we provide some biological insights into
the roles of sequences and structures in protein-RNA interactions
by both evaluating the importance of features for their contributions
in predictive accuracy and analyzing the binding patterns of
interacting residues.
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- Thursday, 4th March, 2010
| Title: |
Progress of the IIM for CFD problems with free boundary/moving interface |
| Speaker: |
Prof. Li Zhilin, Center for Research in Scientific Computation & Mathematics, North Carolina State University, USA |
| Time/Place: |
11:30 - 12:30
FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
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| Abstract: |
The Immersed Interface Method (IIM) is an efficient numerical
method for solving interface, free boundary/moving interface
problems, and problems on irregular domains. The IIM is motivated
by the Peskin's Immersed Boundary (IB) method with better accuracy
and more flexible to deal with different situations. The IIM
is a sharp interface method that enforces jump conditions either
exactly or approximately. In this talk, I will summarize some
recent advances of the IIM, particularly, the applications to
incompressible Stokes and Navier-Stokes equations with singular
sources, discontinuous viscosity, irregular domains, and free
boundary and moving interfaces using the augmented IIM. Applications
include flow past cylinders, moving contact line problems, deformable
moving interfaces, and incompressible interfaces in incompressible
flows.
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- Tuesday, 9th March, 2010
| Title: |
DLS: High Accuracy Analysis of Finite Element Methods with applications for convection-diffusion problems |
| Speaker: |
Prof. Lin Qun, The Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, China |
| Time/Place: |
16:30 - 17:30 (Preceded by Reception at 4:00pm)
RRS905, Sir Run Run Shaw Building, HSH Campus, Hong Kong Baptist University
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| Abstract: |
Conventional accuracy analysis of finite element methods depends
on the Schwarz inequality which yields the optimal accuracy for
general meshes. However, for constructed meshes higher order
of accuracy may be obtained without using the Schwarz inequality.
Instead, we should use the “identity method” to recover the
full accuracy. Especially for convection-diffusion problems involving
small parameters, the traditional estimate certainly depends
on the parameters and thus we can not obtain the optimal result.
By using the “identity method” together with the properties
of the target problems, we can obtain the optimal accuracy independent
of the parameters. Moreover, the “identity method” only uses
the integration by parts, thus most math postgraduate students
may follow the approaches used.
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- Thursday, 11th March, 2010
| Title: |
Two Data Mining Methods for SNP specific extraction and analysis |
| Speaker: |
Ms. Liu Yang, Department of Mathematics, Hong Kong Baptist University, HKSAR |
| Time/Place: |
10:00 - 11:30
FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
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| Abstract: |
In this paper, two data mining methods were proposed to identify
and analyze a set of relevant SNPs for the association between
a disease and multiple marker genotypes. The first one is a subspace
categorical clustering algorithm, which computes a weight for
each SNP in the group of case samples and control samples, and
uses the weights to identify the subsets of relevant SNPs that
categorize these two groups. The second one is a classification
shrunken centroid method, which can succinctly characterize each
class (case and control) by shrinking each centroid with respect
to the overall centroid by a certain threshold in a categorical
manner, and select a set of SNPs associated with a particular
disease. Both methods are applied in a genome-wide Parkinson
disease data set. Results show that the proposed methods are
suitable and useful tools to select relevant SNPs with genetic
variations in a genome-wide association disease study.
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- Friday, 12th March, 2010
| Title: |
CMIV Colloquium: Gene-Gene interaction analysis for the genome-wide association studies: analysis of Korea Genome-wide Association data |
| Speaker: |
Prof. Taesung Park, Department of Statistics, Seoul National University, Korea |
| Time/Place: |
11:00 - 12:00
DLB514, David C. Lam Building, Shaw Campus, Hong Kong Baptist University
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| Abstract: |
Gene-gene interaction is well recognized as playing an important
role in understanding complex traits. Multifactor dimensionality
reduction (MDR) was proposed by Ritchie, et al. (2001) to identify
the multiple loci that affect disease susceptibility simultaneously.
Although the MDR method has been widely used to detect gene-gene
interactions in disease association studies, it cannot be easily
applied to handle the whole genome association due to two limitations.
First, the MDR procedure would require heavy computing in the
genome-wide association research because the interaction effects
are evaluated for all possible SNP combinations. Second, the
evaluation is based on a cross-validation (CV) approach, and
the single best SNP combination for each-order interaction is
usually reported without declaring statistical significance.
We propose a simple two-step strategy to unravel the gene-gene
interactions in the framework of MDR approach for the whole genome
association studies. In the first step, the marginal effects
are tested for all SNPs, and the significant effects are reported.
In the second step, we perform the second-order interactions
via MDR analysis only for the SNP combinations of those SNPs
which have significant marginal effects. Our proposed method
is applied to Korea Association Resource Project (KARE) for 8800
subjects with 550K SNPs.
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- Wednesday, 24th March, 2010
| Title: |
Stepwise Searching in High-Dimensional Regression |
| Speaker: |
Prof. YAO Qiwei, Department of Statistics, The London School of Economics and Political Science, UK |
| Time/Place: |
11:30 - 12:30
FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
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| Abstract: |
We investigate the classical stepwise forward and backward search
methods for selecting sparse models in the context of linear
regression with the number of candidate variables p greater than
the number of observations n. Two types of new information criteria
BICP and BICC are proposed to serve as the stopping rules in
the stepwise searches, since the traditional information criteria
such as BIC and AIC are designed for the cases with p |
- Monday, 29th March, 2010
| Title: |
DLS: Recent Progresses on Schrodinger Flows |
| Speaker: |
Prof. Weiyue Ding, Chinese Academy of Sciences, China |
| Time/Place: |
11:30 - 12:30 (Preceded by Reception at 11:00am)
RRS905, Sir Run Run Shaw Building, HSH Campus, Hong Kong Baptist University
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| Abstract: |
About 12 years ago the speaker and his colleague Wang, Youde,
published a paper in which they proposed the notion of Schrodinger
Flows inspired by the well-known Heisenberg model. This is an
infinite dimensional Hamiltonnian system for maps from Riemannian
manifolds into Kahler manifolds. In the past 10 years many research
works have been done for Schrodinger Flows. In this lecture we
will review some main results in the study of Schrodinger Flows,
including local and global existence of the Cauchy problems;
possible blow-up phenomenon; existence of self-similar solutions,
time-periodic solutions and other special solutions.
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- Monday, 29th March, 2010
| Title: |
Numerical Simulation of Subsurface Multiphase Flow using Locally Conservative Finite Element Methods |
| Speaker: |
Prof. SUN Shuyu, Computational Transport Phenomena Laboratory Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Kingdom of Saudi Ara |
| Time/Place: |
14:30 - 15:30
FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
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| Abstract: |
Subsurface multiphase flow has important applications in petroleum
reservoir engineering and environmental science. Modeling equation
system of subsurface multiphase flow can be generally split into
1) an elliptic partial differential equation (PDE) for the pressure
and 2) one or multiple convection dominated convection-diffusion
PDE for the saturation or for the chemical composition. Accurate
simulation of the phenomena not only requires local mass conservation
to be retained in discretization, but it also demands steep gradients
to be preserved with minimal oscillation and numerical diffusion.
The heterogeneous permeability of the media often comes with
spatially varied capillary pressure functions, both of which
impose additional difficulties to numerical algorithms. To address
these issues, we solve the saturation equation (or species transport
equation) by discontinuous Galerkin (DG) method, a specialized
finite element method that utilizes discontinuous spaces to approximate
solutions. Among other advantages, DG possesses local mass conservation,
small numerical diffusion, and little oscillation. The pressure
equation is solved by either a mixed finite element (MFE) scheme
or a Galerkin finite element method with local conservative postprocessing.
In this talk, we will present the theory and numerical examples
of this combined finite element approach for simulating subsurface
multiphase flow.
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