监管技术巨头：技术力量作为市场支配地位认定因素之再审视

如何有效规制技术巨头已然成为当前《反垄断法》修订的重要任务。技术力量虽然作为传统的市场支配地位认定要素,但长期以来呈现被虚置化的客观状态,致使技术巨头市场支配地位的认定难度增大,技术力量自身的传导效应被显著低估。数字技术对市场竞争的影响异于以往,其通过平台、数据、算法的数字市场三维结构框架影响生产与交易的全过程。技术与三维结构结合所形成的技术力量极为强大,超越了以控制价格为主的传统市场力量,结合社会与资本力量形成了更牢固的市场固化结构。在判断技术巨头的市场支配地位时,亟需发挥技术力量作为非价格型认定要素的重要作用。应当摒弃虚置技术力量作为市场支配地位认定要素的固有症结,提高技术力量在认定市场支配地位时所占权重,回归结构性视角,妥善防范技术巨头无序扩张。     

一类推广的控制收敛定理及其应用

本文研究了一类推广的控制收敛定理及其应用,利用对控制函数满足条件的修改,建立了推广的控制收敛定理,获得其在弱奇异性积分算子中的应用,简化了经典结论的证明.     

Bounds for Systems of Maximal Differential Polynomials without Mixed Derivatives

Mathematical Notes -     

H-矩阵的实用判定

H-矩阵在许多领域中都发挥着重要作用，但在实用中要判别H-矩阵却是很困难的．本文中，我们获得了H-矩阵判别的新的实用充分条件，所得结果包含了[1]的一个主要结果，并用例子说明了文中结果的有效性.     

圆盘定理的改进与弱连对角占优矩阵

本文对圆盘定理进行了改进，给出了特征值分布新的估计，由此引出了弱连对角占优矩阵，讨论了其基本性质，重点分析了该类矩阵的逆与分裂特征，证明了在该类矩阵条件下Ｈ－相容分裂是收敛分裂，并给出迭代矩阵谱半径的上界及ＳＯＲ算法中参数ω的选取范围。     

Non-cooperative implementation: A survey of recent results

Strategic decentralization of collective decision-making is considered when the agents' behaviour is non-cooperative. Specifically they use dominant, maximin risk-avert or sophisticated strategies. The existing results applying these equilibrium concepts are reviewed in three familiar economically meaningful contexts: ordinal (as in voting), random (as in bargaining) and quasilinear (as in public goods problems).     

Fast algorithms for placing large entries along the diagonal of a sparse matrix

Solving a sparse system of linear equations Ax=b is one of the most fundamental operations inside any circuit simulator. The equations/rows in the matrix A are often rearranged/permuted before factorization and applying direct or iterative methods to obtain the solution. Permuting the rows of the matrix A so that the entries with large absolute values lie on the diagonal has several advantages like better numerical stability for direct methods (e.g., Gaussian elimination) and faster convergence for indirect methods (such as the Jacobi method). Duff (2009) [3] has formulated this as a weighted bipartite matching problem (the MC64 algorithm). In this paper we improve the performance of the MC64 algorithm with a new labeling technique which improves the asymptotic complexity of updating dual variables from O(|V|+|E|) to O(|V|), where |V| is the order of the matrix A and |E| is the number of non-zeros. Experimental results from using the new algorithm, when benchmarked with both industry benchmarks and UFL sparse matrix collection, are very promising. Our algorithm is more than 60 times faster (than Duff’s algorithm) for sparse matrices with at least a million non-zeros.     

On diagonal-Schur complements of block diagonally dominant matrices

It is known that the diagonal-Schur complements of strictly diagonally dominant matrices are strictly diagonally dominant matrices [J.Z. Liu, Y.Q. Huang, Some properties on Schur complements of H-matrices and diagonally dominant matrices, Linear Algebra Appl. 389 (2004) 365-380], and the same is true for nonsingular H-matrices [J.Z. Liu, J.C. Li, Z.T. Huang, X. Kong, Some properties of Schur complements and diagonal-Schur complements of diagonally dominant matrices, Linear Algebra Appl. 428 (2008) 1009-1030]. In this paper, we research the properties on diagonal-Schur complements of block diagonally dominant matrices and prove that the diagonal-Schur complements of block strictly diagonally dominant matrices are block strictly diagonally dominant matrices, and the same holds for generalized block strictly diagonally dominant matrices.     

A fast algorithm for solving a Toeplitz system

In this paper, we present a fast algorithm for solving Symmetric penta-diagonal systems. We give the feasibility and Stability analysis of the algorithm. Moreover, parallel computations can be implemented in the algorithm. The numerical examples verify the efficiency of the algorithm.     

On modified block SSOR iteration methods for linear systems from steady incompressible viscous flow problems

In order to solve the large sparse systems of linear equations arising from numerical solutions of two-dimensional steady incompressible viscous flow problems in primitive variable formulation, we present block SSOR and modified block SSOR iteration methods based on the special structures of the coefficient matrices. In each step of the block SSOR iteration, we employ the block LU factorization to solve the sub-systems of linear equations. We show that the block LU factorization is existent and stable when the coefficient matrices are block diagonally dominant of type-II by columns. Under suitable conditions, we establish convergence theorems for both block SSOR and modified block SSOR iteration methods. In addition, the block SSOR iteration and AF-ADI method are considered as preconditioners for the nonsymmetric systems of linear equations. Numerical experiments show that both block SSOR and modified block SSOR iterations are feasible iterative solvers and they are also effective for preconditioning Krylov subspace methods such as GMRES and BiCGSTAB when used to solve this class of systems of linear equations.