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In this talk, a distributed stochastic gradient (SG) algorithm is proposed where the estimators are aimed to collectively estimate an unknown time-invariant parameter from a set of noisy measurements ...
In this talk I plan to survey some progress on Hardy and BMO spaces, Riesz transforms, Bochner-Riesz means and spherical means by using the method of wave equation,and show interesting connections and...
作者: Peter Ladefoged 出版社: Blackwell Publishing Limited 副标题: An Introduction to Fieldwork and Instrumental Techniques 出版年: 2003-09-01 页数: 208 ISBN: 9780631232704
We focus on numerical study of the dynamical Ginzburg-Landau equations under the temporal gauge, and propose a decoupled numerical scheme based on the finite element method. For the variable A, the se...
近日,江南大学人工智能与计算机学院吴小俊教授团队的李辉博士等在深度学习及多模态视觉信息融合研究中取得重要进展,研究成果以“LRRNet: A Novel Representation Learning Guided Fusion Framework for Infrared and Visible Images”为题发表在人工智能领域顶级学术期刊《IEEE Transactions on Patt...
Zero-One Composite Optimization (0/1-COP) is a prototype of nonsmooth, non- convex optimization problems and it has attracted much attention recently. Augmented Lagrangian Method (ALM) has stood out a...
Let G be a finite abelian group. If f: G → C is a nonzero function with Fourier transform f , the Donoho-Stark uncertainty principle states that|supp(f)||supp(f )|≥|G|. The purpose of this talk is two...
We investigate informal risk sharing using a dynamic network game model. In each round, a randomly selected agent experiences a negative shock, and the agent's friends decide whether to provide assist...
Low rank matrix recovery is about reconstructing a low rank matrix from incomplete measurements. It arises frequently in many research areas of science and engineering, for example, machine learning, ...
In this talk, we present the pointwise convergence of one-point large deviations rate functions (LDRFs) of the spatial finite difference method and further the fully discrete method based on the tempo...
Score-based generative modeling (SGM) is a highly successful approach for learning a probability distribution from data and generating further samples, based on learning the score function (gradient o...
We study multi-period inventory control systems in which managers face seasonal demands with unknown distributions and make inventory decisions based on past demand data. It can be shown that a data-d...
Recent advances in analyzing data at the single-cell level have helped biologists make great strides in uncovering new information about cells and their behaviors. One commonly used approach, known as...
When solving the Helmholtz equation numerically, the accuracy of numerical solution deteriorates as the wave number k increases, known as `pollution effect' which is directly related to the phase diff...
We devise fast algorithms for computing the linear response, which is the parameter-gradient of long-time statistics of hyperbolic chaotic dynamical systems. The algorithm is in the form of progressiv...

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