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Prof.
Fun-Den Wang, Colorado School of Mines, USA |
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2009Äê11ÔÂ11ÈÕÉÏÎç9:00
S1013 |
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On
a degenerate free-boundary value problem arising from subsonic-sonic
flows(ϵÁб¨¸æ04) |
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ÐÁÖÜÆ½½ÌÊÚ
(Ïã¸ÛÖÐÎÄ´óѧ§) |
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2009Äê7ÔÂ24ÈÕÉÏÎç10:30
³¿ÐËÖÐÐÄ510ÊÒ |
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Navier-Stokes·½³Ì±ß½çÐÎ×´¿ØÖƺÍάÊý·ÖÁÑËã·¨ |
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»Æ°¬Ïã½ÌÊÚ
(Î÷°²½»Í¨´óѧ) |
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2009Äê7ÔÂ13ÈÕÏÂÎç4:00
˼Դ¥1013ÊÒ |
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Levenberg-Marquardt
method and trust region method for nonlinear equations |
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·¶½ðÑà
½ÌÊÚ (ÉϺ£½»Í¨´óѧ) |
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2009Äê7ÔÂ13ÈÕÏÂÎç3:50
˼Դ¥703ÊÒ |
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Warehouse-Retailer
Network Design Problem with Submodular Penalties: Heuristics
and Bounds |
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Ðì´ó´¨
½ÌÊÚ (±±¾©¹¤Òµ´óѧ) |
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2009Äê7ÔÂ13ÈÕÏÂÎç2:50
˼Դ¥703ÊÒ |
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Semismooth
Newton methods for SVM |
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Prof.Hongxia
Yin (Minnesota State University) |
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2009Äê7ÔÂ13ÈÕÏÂÎç2:00
˼Դ¥703ÊÒ |
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The
report on basic scientific directions of Institute for system
dynamics and control theory |
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Igor
BychkovԺʿ (¶íÂÞ˹¿ÆÑ§ÔºÎ÷²®ÀûÑÇ·ÖԺϵͳ¶¯Á¦Ñ§Óë¿ØÖÆÀíÂÛÑо¿ËùËù³¤) |
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2009Äê6ÔÂ23ÈÕÉÏÎç10:00
³¿ÐË110ÊÒ |
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Some
Recent Progress on Switching Diffusion Systems (ϵÁб¨¸æ03) |
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Prof.
G. Yin (Department of Mathematics Wayne State University) |
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2009Äê6ÔÂ22ÈÕÏÂÎç2:30
˼Դ¥1013ÊÒ |
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In this talk, we report some of our recent work
on switching diffusion processes in which continuous dynamics
and discrete events coexist. With motivation from treating control
and optimization of stochastic systems, we study stability problems.
After recalling the notion of regularity and recurrence, necessary
and sufficient conditions for positive recurrence will be provided;
ergodicity will be examined; stability about an equilibrium
point will be studied; rates of convergence of numerical algorithms
for optimal control of switching diffusions will be mentioned. |
| |
| ±¨¸æÌâÄ¿£º |
Nonlinear
stability of traveling waves from conservation laws with higher
order diffusion |
| ±¨
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Prof.
Changbing Hu (University of Louisville, USA) |
| ʱ¼äµØµã£º |
2009Äê6ÔÂ18ÈÕÏÂÎç4:00
˼Դ¥703ÊÒ |
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Special
geometry and holomorphic anomaly Equations for generalized Calabi-Yau
manifolds |
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ºúÉ
½ÌÊÚ (Öйú¿ÆÑ§¼¼Êõ´óѧÊýѧϵ) |
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2009Äê6ÔÂ17ÈÕÏÂÎç4:00
³¿ÐË410ÊÒ |
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ÕýÇúÂÊÁ÷ÐεķÖÀàÎÊÌâ |
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Öìì䯽
½ÌÊÚ (ÖÐɽ´óѧ) |
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2009Äê6ÔÂ16ÈÕÉÏÎç10:00
˼Դ¥1013ÊÒ |
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ÕýÇúÂÊÁ÷ÐεķÖÀàÎÊÌâ |
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Öìì䯽
½ÌÊÚ (ÖÐɽ´óѧ) |
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2009Äê6ÔÂ16ÈÕÉÏÎç10:00
˼Դ¥1013ÊÒ |
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On
the uniqueness of invariant measure for stochastic delay equations |
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Prof.
Michael Scheutzow (Technical University of Berlin, Germany) |
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2009Äê6ÔÂ15ÈÕÏÂÎç4:00
˼Դ¥1013ÊÒ |
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Three
Types of Exact Tail Asymptotics for Random Walks in the Quarter
Plane |
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Prof.
Tao Luo (Georgetown University, USA) |
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2009Äê6ÔÂ11ÈÕÏÂÎç4:00
˼Դ¥712ÊÒ |
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In this talk, I will present some results on the
stability of rotating and non-rotating white dwarfs stars for
the compressible Euler-Poisson equations, if the total mass
is less than a critical mass. This is a joint work with Joel
Smoller. |
| |
| ±¨¸æÌâÄ¿£º |
Three
Types of Exact Tail Asymptotics for Random Walks in the Quarter
Plane |
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Dr.
Yiqiang Q. Zhao (Carleton University, Canada) |
| ʱ¼äµØµã£º |
2009Äê6ÔÂ10ÈÕÉÏÎç10:30
˼Դ¥712ÊÒ |
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Random walks in the quarter plane can be viewed
as a discrete time Markov chain with a two-dimensional state
space. Under the stability condition, examples demonstrated
that for a fixed value of one variable, the stationary tail
probability as the other variable goes large decays according
to three types: (a) exact geometric; (b) geometric with the
subgeometric factor $n^{-3/2}$; and (c) geometric with the subgeometric
factor $n^{-1/2}$. It is believed that these are the only types
of tail asymptotics for any random walk in the quarter plane.
Under some irreducible (or non-singular) conditions, this has
been almost proved. In this talk, we discuss (i) why only these
three types of tail asymptotics are expected; and (ii) other
types may exist if the irreducible (or non-singular) condition
does not hold. We also ask the question: are these three the
only types of exact tail asymptotics for more general random
walks, say random walks with jumps, assuming suitable irreducibility? |
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ÐìÎ÷°²
½ÌÊÚ (ÐìÖÝʦ·¶´óѧ) |
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2009Äê5ÔÂ27ÈÕÉÏÎç11:00
˼Դ¥712ÊÒ |
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¶àµã±ßÖµÎÊÌâÊǽüÄê·ÇÏßÐÔ³£Î¢·Ö·½³ÌÑо¿ÁìÓòµÄÈȵãÎÊÌâÖ®Ò»£¬ÆäÌØÊâÇéÐΰüº¬Á˾µäµÄÁ½µã±ßÖµÎÊÌâ¡£½üÄêÀ´ÈËÃÇ½Ï¶àµØÑо¿Á˶àµã±ßÖµÎÊÌâÕý½âºÍ·Çƽ·²½âµÄ´æÔÚÎÊÌâ¡£Ñо¿¶àµã±ßÖµÎÊÌâ±äºÅ½âµÄ´æÔÚÐÔÎÊÌâÊǸöÓÐÒâÒåµÄ¹¤×÷£¬´æÔÚһЩеÄÀ§ÄÑ¡£
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Convergence
properties of solutions to several classes PDEs |
| ±¨
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Prof.
Lei Zhang (University of Alabama at Birmingham£USA) |
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2009Äê5ÔÂ27ÈÕÉÏÎç10:00
˼Դ¥712ÊÒ |
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Many problems in Geometry, Physics and Biology
are described by nonlinear partial differential equations of
second order or four order. In this talk I shall mainly mention
a class of fourth order equations from conformal geometry and
some systems of second order equations with rich background
in Physics and Ecology. These equations are challenging in analysis
and represent some typical difficulties. There are some important
open problems related to these equations and I will report the
recent progress on these problems. |
| |
| ±¨¸æÌâÄ¿£º |
Strong
maximum principle for singular solutions of nonlinear elliptic
equations |
| ±¨
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Professor
Yanyan Li (Rutgers University, USA) |
| ʱ¼äµØµã£º |
2009Äê5ÔÂ25ÈÕÉÏÎç10:00
˼Դ¥1013ÊÒ |
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|
| |
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Transformation
Optics and Three Dimensional Cloaking of Active Devices |
| ±¨
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Professor
Hongyu Liu (Dept of Mathematics, University of Washington, USA) |
| ʱ¼äµØµã£º |
2009Äê5ÔÂ22ÈÕÏÂÎç4:00
˼Դ¥1013ÊÒ |
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.In
this talk, we shall first discuss the transformation optics
in the design of cloaking devices to obtain customized electromagnetic
wave propogation. Then, using the transformation optics, we
give the construction of a three dimensional cloaking device,
which makes the cloaked region with a source invisible to wave
detection. Based on a new notion of "finite energy solution"
for singular PDE, the rigorous mathematical justification of
the invisibility cloaking is given. Finally, we briefly introduce
a specially designed finite element discretization for numerically
solving the cloaking problem |
| |
| ±¨¸æÌâÄ¿£º |
Navier£Stokes
equations in the critical Lebesgue spaces |
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¶¼´óÅô²©Ê¿
(¸´µ©´óѧÊýѧ¿ÆÑ§Ñ§Ôº) |
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2009Äê5ÔÂ21ÈÕÏÂÎç4:00
˼Դ¥1013ÊÒ |
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. |
| |
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Two-stage
efficient estimation of stratified mark-specific proportional
hazards models with missing marks£¨ÏµÁб¨¸æ2£© |
| ±¨
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Professor
Yanqing Sun (University of North Carolina at Charlotte) |
| ʱ¼äµØµã£º |
2009Äê2ÔÂ10ÈÕÏÂÎç4:00
˼Դ¥712ÊÒ |
| Õª  Òª£º |
Motivated
by the need to assess HIV vaccine efficacy, the competing risks
model with a continuum of competing risks, called mark, has
been studied in recent years by a few authors. The mark-specific
proportional hazards model is the proportional hazards model
for mark-specific hazard function in which the regression parameters
depend nonparametrically on the mark and the baseline hazard
to depend nonparametrically on both time and mark. In the HIV
vaccine efficacy trial, a very high percentage of marks of interest
may be missing for infected trial participants due to the evolving
nature of the HIV viruses. This research investigates the stratified
mark-specific proportional hazards model with missing marks
where the baseline functions may vary with strata. A two-stage
estimation procedure is proposed. In the first stage, we propose
an estimation procedure based on the inverse probability weighted
complete-case technique. A more efficient augmented inverse
probability weighted complete-case estimator is derived in the
second stage based on the knowledge of the distribution of marks.
In addition, the proposed two-stage procedure can utilize auxiliary
information for missing marks to improve efficiency. The asymptotic
properties of the proposed estimators are investigated. We show
that the AUG estimator is more efficient than the IPW estimator.
The finite sample performance of the proposed methods are evaluated
through simulations. The applications to the HIV vaccine efficacy
assessment are discussed . |
| |
| ±¨¸æÌâÄ¿£º |
Jackknife
empirical likelihood£¨ÏµÁб¨¸æ1£© |
| ±¨
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Professor
Bing-Yi JING (Hong Kong Univ. of Science & Technology) |
| ʱ¼äµØµã£º |
2009Äê1ÔÂ7ÈÕÏÂÎç4:00
˼Դ¥703ÊÒ |
| Õª  Òª£º |
Empirical
likelihood, since its first introduction by Owen in 1988, has
been found very useful in many different occasions. However,
it is not always trouble-free. For instance, when applied directly
to some more complicated statistics such as U-statistics, it
runs into serious computational difficulties, particularly when
the sample size gets larger. In this paper, we will take a fresh
look at the problem. We introduce a new approach which combines
two of popular nonparametric approaches: the jackknife and the
empirical likelihood. The resulting method, referred to as the
jackknife empirical likelihood (JEL), is extremely simple to
use in practice, in comparison with other existing methods.
In particular, the new method is shown to be very effictive
in handling U-statistics. The JEL can be potentially useful
for other nonlinear statistics, however, further research is
needed to justify its usage in those situations.
(This is joint work with Junqing YUAN and Want ZHOU.) . |
| |
| ±¨¸æÌâÄ¿£º |
Quasi-Likelihood
of Models: Modified Profile Likelihood for Model Selection |
| ±¨
¸æ ÈË£º |
Dr.
He Heping (The University of Kansas ) |
| ʱ¼äµØµã£º |
2009Äê1ÔÂ5ÈÕÏÂÎç3:00
˼Դ¥703ÊÒ |
| Õª  Òª£º |
The
goal of this research is to develop the modified profile likelihoods
(MPLs) as quasi-likelihood functions of models for model selection.
It treats those parameters in each possible model as nuisance
parameters, and the models themselves as the values of the ``parameter''
of interest, then uses the likelihood ratio approximation to
conditional distribution of maximum likelihood estimators of
the parameters in the possible models to develop the MPLs of
models. Note that the MPL proposed here is considered as a function
of models themselves instead of parameters in the models. The
selected model is then the one maximizing the quasi-likelihood
of models, i.e. the MPL. Some simulations have show that the
MPL works very well for the selection of error probability laws
in location-scale models. The MPL of models has also been obtained
for composite transformation models. In future, this research
may develop the MPL of models for model selection problems in
exponential family, regular models, regressions, change point
problems, AR or ARMA time series models and so on. |
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