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作者：Postek, Krzysztof; Ben-Tal, Aharon; den Hertog, Dick; Melenberg, Bertrand
作者单位：Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam; Technion Israel Institute of Technology; Shenkar College of Engineering, Design & Art; Tilburg University; Tilburg University; Tilburg University
摘要：In this paper we consider ambiguous stochastic constraints under partial information consisting of means and dispersion measures of the underlying random parameters. Whereas the past literature used the variance as the dispersion measure, here we use the mean absolute deviation from the mean (MAD). This makes it possible to use the 1972 result of Ben-Tal and Hochman (BH) m which tight upper and lower bounds on the expectation of a convex function of a random variable are given. First, we use t...
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作者：Jagabathula, Srikanth; Subramanian, Lakshminarayanan; Venkataraman, Ashwin
作者单位：New York University; New York University
摘要：We consider the problem of segmenting a large population of customers into nonoverlapping groups with similar preferences, using diverse preference observations such as purchases, ratings, clicks, and so forth, over subsets of items. We focus on the setting where the universe of items is large (ranging from thousands to millions) and unstructured (lacking well-defined attributes) and each customer provides observations for only a few items. These data characteristics limit the applicability of...
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作者：Massoulie, Laurent; Xu, Kuang
作者单位：Stanford University
摘要：We propose and analyze a family of information processing systems, where a finite set of experts or servers are employed to extract information about a stream of incoming jobs. Each job is associated with a hidden label drawn from some prior distribution. An inspection by an expert produces a noisy outcome that depends both on the job's hidden label and the type of the expert and occupies the expert for a finite time duration. A decision-maker's task is to dynamically assign inspections so tha...
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作者：Tsitsiklis, John N.; Xu, Kuang
作者单位：Massachusetts Institute of Technology (MIT); Stanford University
摘要：We formulate a model of sequential decision making, dubbed the Goal Prediction game, to study the extent to which an overseeing adversary can predict the final goal of an agent who tries to reach that goal quickly, through a sequence of intermediate actions. Our formulation is motivated by the increasing ubiquity of large-scale surveillance and data collection infrastructures, which can be used to predict an agent's intentions and future actions, despite the agent's desire for privacy. Our mai...
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作者：Aouad, Ali; Levi, Retsef; Segev, Danny
作者单位：University of London; London Business School; Massachusetts Institute of Technology (MIT); University of Haifa
摘要：We study the joint assortment planning and inventory management problem, where stock-out events elicit dynamic substitution effects, described by the multinomial logit (MNL) choice model. Special cases of this setting have been extensively studied in recent literature, notably the static assortment planning problem. Nevertheless, to our knowledge, the general formulation is not known to admit efficient algorithms with analytical performance guarantees before this work, and most of its computat...
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作者：Embrechts, Paul; Liu, Haiyan; Wang, Ruodu
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Finance Institute (SFI); Michigan State University; Michigan State University; University of Waterloo
摘要：We address the problem of risk sharing among agents using a two-parameter class of quantile-based risk measures, the so-called range-value-at-risk (RVaR), as their preferences. The family of RVaR includes the value-at-risk (VaR) and the expected shortfall (ES), the two popular and competing regulatory risk measures, as special cases. We first establish an inequality for RVaR-based risk aggregation, showing that RVaR satisfies a special form of subadditivity. Then, the Pareto-optimal risk shari...
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作者：Hanasusanto, Grani A.; Kuhn, Daniel
作者单位：University of Texas System; University of Texas Austin; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：Adaptive robust optimization problems are usually solved approximately by restricting the adaptive decisions to simple parametric decision rules. However, the corresponding approximation error can be substantial. In this paper we show that two-stage robust and distributionally robust linear programs can often be reformulated exactly as conic programs that scale polynomially with the problem dimensions. Specifically, when the ambiguity set constitutes a 2-Wasserstein ball centered at a discrete...
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作者：El-Amine, Hadi; Bish, Ebru K.; Bish, Douglas R.
作者单位：George Mason University; Virginia Polytechnic Institute & State University
摘要：Blood products are essential components of any healthcare system, and their safety, in terms of being free of transfusion-transmittable infections, is crucial. While the Food and Drug Administration (FDA) in the United States requires all blood donations to be tested for certain infection types, it does not dictate which particular tests should be used by blood centers. Multiple FDA-licensed blood screening tests are available for each infection type, and screening tests are imperfectly reliab...
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作者：Pu, Shi; Garcia, Alfredo
作者单位：Arizona State University; Arizona State University-Tempe; Texas A&M University System; Texas A&M University College Station
摘要：In recent years, the paradigm of cloud computing has emerged as an architecture for computing that makes use of distributed (networked) computing resources. In this paper, we consider a distributed computing algorithmic scheme for stochastic optimization, which relies on modest communication requirements among processors and most importantly, does not require synchronization. Specifically, we analyze a scheme with N > 1 independent threads each implementing a stochastic gradient algorithm. The...
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作者：Fazel-Zarandi, Mohammad M.; Kaplan, Edward H.
作者单位：Yale University; Massachusetts Institute of Technology (MIT); Yale University; Yale University
摘要：The first-come, first-served (FCFS) stochastic matching model, where each server in an infinite sequence is matched to the first eligible customer from a second infinite sequence, developed from queueing problems addressed by Kaplan (1984) in the context of public housing assignments. The goal of this model is to determine the matching rates between eligible customer types and server types, that is, the fraction of all matches that occur between type-i customers and type- j servers. This model...
