Preface: Special Issue on Optimization Algorithms and Applications
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Preface: Special Issue on Optimization Algorithms and Applications Dong-Dong Ge1
· Zai-Wen Wen2 · Ya-Xiang Yuan3
Published online: 22 February 2019 © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature 2019
Optimization is one of the fundamental and essential components of operations research, a highly interdisciplinary subject. As one of the first researchers of the interior-point methods, Professor Yin-Yu Ye is responsible not only for developing many fundamental results, which have tremendously advanced the optimization theory, but also for enriching the field by applications emerging from statistics, machine learning, signal and imaging processing, communications, computational economics and finance. Computational methods and theory using semidefinite programming have been demonstrated to be helpful for the localization of network sensors. In computational economics, new complexity results have been established for problems related to the computation of an economic equilibrium. We appreciate Ye for his insatiable curiosity, openness to new ideas and a keen interest in the success of young people in our field of operations research. This issue is a perfect exhibition of his influence and inspiration to many operations research scholars, even to the youngest disciples. The topics in this collection of selected papers encompass a broad area of optimization algorithms and applications, including robust optimization, dynamic pricing, phase retrieval by sensor network localization and asynchronous computation, etc. These papers are summarized as follows. Zhimin Peng, Yangyang Xu, Ming Yan and Wotao Yin analyzed the convergence of the async-parallel block coordinate update method in a probabilistic way. They showed that the algorithm is guaranteed to converge for smooth problems if the expected
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Dong-Dong Ge [email protected] Zai-Wen Wen [email protected] Ya-Xiang Yuan [email protected]
1
Shanghai University of Finance and Economics, Shanghai 200433, China
2
Beijing International Center for Mathematical Research, Beijing 100871, China
3
Chinese Academy of Sciences, Beijing 100190, China
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2
D.-D. Ge et al.
delay is finite and for non-smooth problems if the variance of the delay is also finite; moreover, they established sublinear convergence of the method for weakly convex problems and linear convergence for strongly convex ones. Tao-Ran Fu and Jin-Yan Fan showed that the successive partial-symmetric rank-one approximation algorithm not only exactly recovers the unitary decomposition of the unitarily decomposable conjugate partial-symmetric tensors, but also robustly recovers the unitary decomposition of the underlying complex tensor in the presence of perturbations. They studied the partial-symmetric tensors in the complex domain involving conjugate terms and provided the first theoretical analysis of the exact recovery of these tensors. Peng-Yu Qian, Zi-Zhuo Wang and Zai-Wen Wen proposed
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