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Articles 1  11 of 11
FullText Articles in Operations Research, Systems Engineering and Industrial Engineering
Five Lenses On Team Tutor Challenges: A Multidisciplinary Approach, Stephen B. Gilbert, Michael Dorneich, Jamiahus Walton, Eliot Winer
Five Lenses On Team Tutor Challenges: A Multidisciplinary Approach, Stephen B. Gilbert, Michael Dorneich, Jamiahus Walton, Eliot Winer
Industrial and Manufacturing Systems Engineering Publications
This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a ...
Iteration Complexity Analysis Of Block Coordinate Descent Methods, Mingyi Hong, Xiangfeng Wang, Mesiam Razaviyayn, ZhiQuan Luo
Iteration Complexity Analysis Of Block Coordinate Descent Methods, Mingyi Hong, Xiangfeng Wang, Mesiam Razaviyayn, ZhiQuan 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 socalled block successive upperbound minimization (BSUM) framework, and show that for a broad class of multiblock nonsmooth convex problems, all algorithms covered by the BSUM framework achieve a global sublinear iteration complexity of O(1/r)" role="presentation" style="boxsizing: borderbox; display: inlinetable; lineheight: normal; letterspacing: normal; wordspacing: normal; wordwrap: normal; whitespace: nowrap ...
On The Linear Convergence Of The Alternating Direction Method Of Multipliers, Mingyi Hong, ZhiQuan Luo
On The Linear Convergence Of The Alternating Direction Method Of Multipliers, Mingyi Hong, ZhiQuan 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 Rlinear convergence of the ADMM ...
Alternating Direction Method Of Multipliers For Penalized ZeroVariance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong
Alternating Direction Method Of Multipliers For Penalized ZeroVariance 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 zerovariance discriminant analysis, for simultaneously performing linear discriminant analysis and feature selection on high dimensional data. This method combines classical zerovariance discriminant analysis, where discriminant vectors are identified in the null space of the sample withinclass 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, YaFeng Liu
Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, YaFeng Liu
Industrial and Manufacturing Systems Engineering Publications
No abstract provided.
Sample ApproximationBased Deflation Approaches For Chance SinrConstrained Joint Power And Admission Control, YaFeng Liu, Mingyi Hong, Enbin Song
Sample ApproximationBased Deflation Approaches For Chance SinrConstrained Joint Power And Admission Control, YaFeng Liu, Mingyi Hong, Enbin Song
Industrial and Manufacturing Systems Engineering Publications
Consider the joint power and admission control (JPAC) problem for a multiuser singleinput singleoutput (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 ...
Sinr Constrained Beamforming For A Mimo MultiUser Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, ZhiQuan Luo
Sinr Constrained Beamforming For A Mimo MultiUser Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, ZhiQuan Luo
Industrial and Manufacturing Systems Engineering Publications
Consider a multipleinput multipleoutput (MIMO) downlink multiuser channel. A wellstudied 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 socalled minimum mean square error (MMSE)secondorder cone programming (SOCP) algorithm [Visotksy and Madhow, “Optimum Beamforming Using Transmit Antenna Arrays,” Proc. IEEE Veh. Technol. Conf., May 1999, vol. 1, pp. 851856] , [Wong, Zheng, and Ng, “Convergence Analysis of Downlink MIMO Antenna System Using SecondOrder Cone Programming,” Proc. 62nd IEEE Veh. Technol. Conf., Sep. 2005, pp. 492496] and ...
Asynchronous Distributed Admm For LargeScale Optimization—Part I: Algorithm And Convergence Analysis, TsungHui Chang, Mingyi Hong, WeiCheng Liao, Xiangfeng Wang
Asynchronous Distributed Admm For LargeScale Optimization—Part I: Algorithm And Convergence Analysis, TsungHui Chang, Mingyi Hong, WeiCheng Liao, Xiangfeng Wang
Industrial and Manufacturing Systems Engineering Publications
Aiming at solving largescale 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 ...
Asynchronous Distributed Admm For LargeScale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, TsungHui Chang, WeiCheng Lao, Mingyi Hong, Xiangfeng Wang
Asynchronous Distributed Admm For LargeScale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, TsungHui Chang, WeiCheng 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 largescale 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 ...
A Unified Algorithmic Framework For BlockStructured Optimization Involving Big Data: With Applications In Machine Learning And Signal Processing, Mingyi Hong, Meisam Razaviyayn, ZhiQuan Luo
A Unified Algorithmic Framework For BlockStructured Optimization Involving Big Data: With Applications In Machine Learning And Signal Processing, Mingyi Hong, Meisam Razaviyayn, ZhiQuan Luo
Industrial and Manufacturing Systems Engineering Publications
This article presents a powerful algorithmic framework for big data optimization, called the block successive upperbound minimization (BSUM). The BSUM includes as special cases many wellknown methods for analyzing massive data sets, such as the block coordinate descent (BCD) method, the convexconcave 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 SourceRelay Design For FullDuplex Mimo Af Relay Systems, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu
Joint SourceRelay Design For FullDuplex 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 fullduplex (FD) relay systems can be greatly impacted by the selfinterference (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 multipleinputmultipleoutput (MIMO) amplifyandforward (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 rankone structure. Then ...