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作者：Shi, Xinbo; Peng, Yijie; Zhang, Gongbo
作者单位：Peking University; Nanjing University; Beihang University
摘要：We aim to efficiently allocate a fixed simulation budget to identify the best designs for each context among a finite number of contexts. The performance of each design in a context is measured by an identifiable statistical characteristic, possibly with the existence of nuisance parameters. In a Bayesian framework, we extend the top-two Thompson sampling method designed for selecting the best design in a single context to the contextual selection problems, leading to an efficient sampling pol...
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作者：Ernst, Philip A.; Mostovyi, Oleksii
作者单位：Imperial College London; University of Connecticut
摘要：We investigate a pricing rule that is applicable for streams of income or contingent claim liabilities and study how this rule changes under additional insider-type information that an investor might obtain. Considering a model where the risky asset might have jumps, we obtain an explicit form of the associated state price density for the three different types of agents considered in Ernst and Rogers: one who has no information about the jumps, one who knows in advance exactly when each jump w...
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作者：Liang, Zongxia; Yu, Xiang; Zhang, Keyu
作者单位：Tsinghua University; Hong Kong Polytechnic University
摘要：This paper studies a class of time-inconsistent mean field control (MFC) problems in the presence of common noise under nonexponential discount and joint law dependence of both state and control. We investigate the closed-loop, time-consistent equilibrium strategies for these extended MFC problems and characterize them through equilibrium Hamilton-Jacobi-Bellman equation defined on the Wasserstein space. We first apply the results to the linear quadratic (LQ) time-inconsistent MFC problems and...
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作者：Tang, Jingyong; Sun, Guo; Zhou, Jinchuan; Zhang, Hongchao
作者单位：Xinyang Normal University; Qufu Normal University; Shandong University of Technology; Louisiana State University System; Louisiana State University
摘要：This paper considers the stochastic symmetric cone linear complementarity problem (S-SCLCP), which includes the stochastic linear complementarity problem and the stochastic second-order cone linear complementarity problem as special cases. We propose a new expected residual minimization (ERM) formulation for S-SCLCP and apply the Monte Carlo technique to generate the corresponding approximation problem. Different from existing ERM formulations for stochastic complementarity problems, the propo...
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作者：Liu, Haiyan; Wang, Bin; Wang, Ruodu; Zhuang, Sheng Chao
作者单位：Michigan State University; Michigan State University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; University of Waterloo; University of Nebraska System; University of Nebraska Lincoln
摘要：Classic optimal transport theory is formulated through minimizing the expected transport cost between two given distributions. We propose the framework of distorted optimal transport by minimizing a distorted expected cost, which is the cost under a nonlinear expectation. This new formulation is motivated by concrete problems in decision theory, robust optimization, and risk management, and it has many distinct features compared with the classic theory. We choose simple cost functions and stud...
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作者：He, Shengyi; Lam, Henry
作者单位：Columbia University
摘要：Distributionally robust optimization (DRO) is a worst-case framework for stochastic optimization under uncertainty that has drawn fast-growing studies in recent years. When the underlying probability distribution is unknown and observed from data, DRO suggests computing the worst-case distribution within a so-called uncertainty set that captures the involved statistical uncertainty. In particular, DRO with uncertainty set constructed as a statistical divergence neighborhood ball has been shown...
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作者：Banerjee, Sayan; Budhiraja, Amarjit; Estevez, Benjamin
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：Consider a queuing system with K parallel queues in which the server for each queue processes jobs at rate n and the total arrival rate to the system is nK - v root n, where v is an element of (0,infinity) and n is large. Interarrival and service times are taken to be independent and exponentially distributed. It is well known that the join-the-shortest-queue (JSQ) policy has many desirable load-balancing properties. In particular, in comparison with uniformly at random routing, the time asymp...
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作者：Zhao, Jingyang; Xiao, Mingyu
作者单位：University of Electronic Science & Technology of China
摘要：The bipartite traveling tournament problem (BTTP) addresses interleague sports scheduling, which aims to design a feasible bipartite tournament between two n-team leagues under some constraints such that the total traveling distance of all participating teams is minimized. Since its introduction, several methods have been developed to design feasible schedules for the National Basketball Association (NBA), Nippon Professional Baseball (NPB), and so on. In terms of solution quality with a theor...
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作者：Brustle, Johannes; Perez-Salazar, Sebastian; Verdugo, Victor
作者单位：Sapienza University Rome; Rice University; Rice University; Pontificia Universidad Catolica de Chile; Pontificia Universidad Catolica de Chile
摘要：The prophet inequality is one of the cornerstone problems in optimal stopping theory and has become a crucial tool for designing sequential algorithms in Bayesian settings. In the i.i.d. k-selection prophet inequality problem, we sequentially observe n nonnegative random values sampled from a known distribution. Each time, a decision is made to accept or reject the value, and under the constraint of accepting at most k items. For k = 1, Hill and Kertz [Ann. Probab. 1982] provided an upper boun...
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作者：Xu, Meng; Jiang, Bo; Liu, Ya-Feng; So, Anthony Man-Cho
作者单位：Chinese Academy of Sciences; Nanjing Institute of Geology & Paleontology, CAS; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Nanjing Normal University; Beijing University of Posts & Telecommunications; Chinese University of Hong Kong
摘要：In this paper, we consider a class of nonconvex-linear minimax problems on Riemannian manifolds, which find wide applications in machine learning and signal processing. For solving this class of problems, we develop a flexible Riemannian alternating descent ascent (RADA) algorithmic framework. Within this framework, we propose two easy-to-implement yet efficient algorithms that alternately perform one or multiple projected/Riemannian gradient descent steps and a proximal gradient ascent step a...
