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Articles **1** - **10** of ** 10**

## Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Iteration Complexity Analysis Of Block Coordinate Descent Methods, Mingyi Hong, Xiangfeng Wang, Mesiam Razaviyayn, Zhi-Quan Luo

#### Iteration Complexity Analysis Of Block Coordinate Descent Methods, Mingyi Hong, Xiangfeng Wang, Mesiam Razaviyayn, Zhi-Quan Luo

*Industrial and Manufacturing Systems Engineering Publications*

In this paper, we provide a unified iteration complexity analysis for a family of general block coordinate descent methods, covering popular methods such as the block coordinate gradient descent and the block coordinate proximal gradient, under various different coordinate update rules. We unify these algorithms under the so-called block successive upper-bound minimization (BSUM) framework, and show that for a broad class of multi-block nonsmooth convex problems, all algorithms covered by the BSUM framework achieve a global sublinear iteration complexity of O(1/r)" role="presentation" style="box-sizing: border-box; display: inline-table; line-height: normal; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap ...

On The Linear Convergence Of The Alternating Direction Method Of Multipliers, Mingyi Hong, Zhi-Quan Luo

#### On The Linear Convergence Of The Alternating Direction Method Of Multipliers, Mingyi Hong, Zhi-Quan Luo

*Industrial and Manufacturing Systems Engineering Publications*

We analyze the convergence rate of the alternating direction method of multipliers (ADMM) for minimizing the sum of two or more nonsmooth convex separable functions subject to linear constraints. Previous analysis of the ADMM typically assumes that the objective function is the sum of only *two* convex functions defined on *two* separable blocks of variables even though the algorithm works well in numerical experiments for three or more blocks. Moreover, there has been no rate of convergence analysis for the ADMM without strong convexity in the objective function. In this paper we establish the global R-linear convergence of the ADMM ...

Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong

#### Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong

*Industrial and Manufacturing Systems Engineering Publications*

We consider the task of classification in the high dimensional setting where the number of features of the given data is significantly greater than the number of observations. To accomplish this task, we propose a heuristic, called sparse zero-variance discriminant analysis, for simultaneously performing linear discriminant analysis and feature selection on high dimensional data. This method combines classical zero-variance discriminant analysis, where discriminant vectors are identified in the null space of the sample within-class covariance matrix, with penalization applied to induce sparse structures in the resulting vectors. To approximately solve the resulting nonconvex problem, we develop a simple algorithm based ...

Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu

#### Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu

*Industrial and Manufacturing Systems Engineering Publications*

No abstract provided.

Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang

#### Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang

*Industrial and Manufacturing Systems Engineering Publications*

The alternating direction method of multipliers (ADMM) has been recognized as a versatile approach for solving modern large-scale machine learning and signal processing problems efficiently. When the data size and/or the problem dimension is large, a distributed version of ADMM can be used, which is capable of distributing the computation load and the data set to a network of computing nodes. Unfortunately, a direct synchronous implementation of such algorithm does not scale well with the problem size, as the algorithm speed is limited by the slowest computing nodes. To address this issue, in a companion paper, we have proposed ...

Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo

#### Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo

*Industrial and Manufacturing Systems Engineering Publications*

Consider a multiple-input multiple-output (MIMO) downlink multi-user channel. A well-studied problem in such a system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called minimum mean square error (MMSE)-second-order cone programming (SOCP) algorithm [Visotksy and Madhow, “Optimum Beamforming Using Transmit Antenna Arrays,” Proc. IEEE Veh. Technol. Conf., May 1999, vol. 1, pp. 851-856] , [Wong, Zheng, and Ng, “Convergence Analysis of Downlink MIMO Antenna System Using Second-Order Cone Programming,” Proc. 62nd IEEE Veh. Technol. Conf., Sep. 2005, pp. 492-496] and ...

Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song

#### Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song

*Industrial and Manufacturing Systems Engineering Publications*

Consider the joint power and admission control (JPAC) problem for a multiuser single-input single-output (SISO) interference channel. Most existing works on JPAC assume the perfect instantaneous channel state information (CSI). In this paper, we consider the JPAC problem with the imperfect CSI, i.e., we assume that only the channel distribution information (CDI) is available. We formulate the JPAC problem into a chance (probabilistic)-constrained program, where each link's SINR outage probability is enforced to be less than or equal to a specified tolerance. To circumvent the computational difficulty of the chance SINR constraints, we propose to use the ...

Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang

#### Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang

*Industrial and Manufacturing Systems Engineering Publications*

Aiming at solving large-scale optimization problems, this paper studies distributed optimization methods based on the alternating direction method of multipliers (ADMM). By formulating the optimization problem as a consensus problem, the ADMM can be used to solve the consensus problem in a fully parallel fashion over a computer network with a star topology. However, traditional synchronized computation does not scale well with the problem size, as the speed of the algorithm is limited by the slowest workers. This is particularly true in a heterogeneous network where the computing nodes experience different computation and communication delays. In this paper, we propose ...

A Unified Algorithmic Framework For Block-Structured Optimization Involving Big Data: With Applications In Machine Learning And Signal Processing, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo

#### A Unified Algorithmic Framework For Block-Structured Optimization Involving Big Data: With Applications In Machine Learning And Signal Processing, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo

*Industrial and Manufacturing Systems Engineering Publications*

This article presents a powerful algorithmic framework for big data optimization, called the block successive upper-bound minimization (BSUM). The BSUM includes as special cases many well-known methods for analyzing massive data sets, such as the block coordinate descent (BCD) method, the convex-concave procedure (CCCP) method, the block coordinate proximal gradient (BCPG) method, the nonnegative matrix factorization (NMF) method, the expectation maximization (EM) method, etc. In this article, various features and properties of the BSUM are discussed from the viewpoint of design flexibility, computational efficiency, parallel/distributed implementation, and the required communication overhead. Illustrative examples from networking, signal processing, and machine ...

Joint Source-Relay Design For Full-Duplex Mimo Af Relay Systems, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu

#### Joint Source-Relay Design For Full-Duplex Mimo Af Relay Systems, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu

*Industrial and Manufacturing Systems Engineering Publications*

The performance of full-duplex (FD) relay systems can be greatly impacted by the self-interference (SI) at relays. By exploiting multiple antennas, the spectral efficiency of FD relay systems can be enhanced through spatial SI mitigation. This paper studies joint source transmit beamforming and relay processing to achieve rate maximization for FD multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay systems with consideration of relay processing delay. The problem is difficult to solve mainly due to the SI constraint induced by the relay processing delay. In this paper, we first present a sufficient condition under which the relay amplification matrix has rank-one structure. Then ...