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Nonconvex minimax problems have attracted wide attention in machine learning, signal processing and many other fields in recent years. In this paper, we propose a primal dual alternating proximal grad...
Based on the newly constructed input-output model that distinguishes firm size categories and the structural decomposition analysis method, this study quantitatively calculates the employment effects ...
In this talk, we consider a distributed interval optimization problem (DIOP) with uncertainties, whose global function is formed by local convex interval functions. In seeking Pareto solutions for dis...
In this work, we propose and analyze domain decomposition methods to decouple the large system arisen from the discretization of dual-porosity-Stokes model. Robin boundary conditions are used to decou...
The dual weighted residual (DWR) method yields reliable a posteriori error bounds for linear output functionals provided that the error incurred by the numerical approximation of the dual solution i...
A spanning tree T in a finite planar connected graph G determines a dual spanning tree T* in the dual graph G* such that T and T* do not intersect. We show that it is not always possible to find T in ...
The Kolmogorov]Smirnov distance is an important tool for constructing confidence sets and tests in univariate problems. In multivariate settings, an analogous role is played by the halfspace di...
De nition 2.0.1. A representation (;X) on a Hilbert space X is called unitary if X admits a (nondegenerate) inner product h ; i such that G acts by unitary transformations.
Much of the material in this talk was presented at the conference in honor of Roger Howe. The slides are available at http://math.mit.edu/conferences/howe/program.php The theme of the talk is to n...
G is the real points of a linear connected reductive group. - g0 := Lie(G),  Cartan involution, g0 = k0 + s0, g := (g0)C, K maximal compact subgroup, g = k + s, - P = MAN minimal parabolic subgrou...
The full unitary dual for the complex classical groups viewed as real Lie groups is computed in [B1]. This was close to 20 years ago. Since then there have been many advances, but the general proble...
We describe a potential reduction method for convex optimization problems involving matrix inequalities. The method is based on the theory developed by Nesterov and Nemirovsky and generalizes Gonzaga ...
We develop a simple operator splitting method for solving a primal conic optimization problem; we show that the iterates also solve the dual problem. The resulting algorithm is very simple to describe...
First order optimization methods often perform poorly on ill-conditioned optimization problems. However, by preconditioning the problem data and solving the preconditioned problem, the performance of ...
The orientation preserving conditions and approximation errors of a dual-parametric bi-quadratic finite element method for the computation of both radially symmetric and general nonsymmetric cavity s...

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