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作者：Shamsi, Davood; Luenberger, Robert; Ye, Yinyu
作者单位：Shanghai Jiao Tong University; Shanghai Institute for Mathematics & Interdisciplinary Sciences
摘要：This research note revisits the framework proposed in our earlier work and explores its conceptual and algorithmic connection to recent advances in dual-based online resource allocation-particularly the dual mirror descent method introduced previously. Both approaches address the challenge of making real-time sequential allocation decisions under dynamically revealed constraints. Although the dual mirror descent method relies on Bregman divergence to guide dual updates, our framework derives n...
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作者：Chen, Du; Chua, Geoffrey A.
作者单位：Nanyang Technological University
摘要：Data are now widely considered a key firm asset for enabling better operational decisions. However, data-driven decisions can inadvertently expose private data, leaving firms vulnerable to unforeseen danger. How to manage data security risks by protecting data from being inferred from observable decisions thus becomes an important question. In this paper, we focus on data security in supply chains because of their data-intensive nature. Specifically, we examine a data-driven contextual newsven...
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作者：Bichuch, Maxim; Feinstein, Zachary
作者单位：University at Albany, SUNY; State University of New York (SUNY) System; University at Buffalo, SUNY; Stevens Institute of Technology
摘要：Within this work we consider an axiomatic framework for Automated Market Makers (AMMs). AMMs are smart contracts that set prices for swaps on a pool of assets. By imposing reasonable axioms on the underlying utility function, we are able to characterize the properties of the swap size of the assets and of the resulting pricing oracle. In providing these general axioms, we define a novel measure of price impacts that can be used to quantify those costs between different AMM constructions. We ha...
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作者：Shapiro, Alexander; Zhou, Enlu; Lin, Yifan; Wang, Yuhao
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：Stochastic optimal control with unknown randomness distributions has been studied for a long time, encompassing robust control, distributionally robust control, and adaptive control. We propose a new episodic Bayesian approach that incorporates Bayesian learning with optimal control. In each episode, the approach learns the randomness distribution with a Bayesian posterior and subsequently solves the corresponding Bayesian average estimate of the true problem. The resulting policy is exercised...
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作者：Hartmann, Lorenz; Kauffeldt, T. Florian
作者单位：University of Basel
摘要：Suggestion for abstract without references: In this paper, we present the first axiomatic characterization of preferences that can be represented by a Choquet integral with respect to an exact capacity. The characterizing axiom, binary diversification, is novel and reflects an inclination for bets on events, thereby capturing a specific type of ambiguity aversion. Furthermore, we demonstrate that the three capacity classes balanced, exact, and convex fully exhaust all levels of our family of k...
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作者：Correa, Jose; Golz, Paul; Schmidt-Kraepelin, Ulrike; Tucker-Foltz, Jamie; Verdugo, Victor
作者单位：Universidad de Chile; Cornell University; Eindhoven University of Technology; Yale University; Pontificia Universidad Catolica de Chile; Pontificia Universidad Catolica de Chile
摘要：Apportionment is the act of distributing the seats of a legislature among political parties (or states) in proportion to their vote shares (or populations). A famous impossibility proven by Balinski and Young shows that no apportionment method can be proportional up to one seat (i.e., quota) while also responding monotonically to changes in the votes (i.e., population monotone). Grimmett proposed to overcome this impossibility by randomizing the apportionment, which can achieve quota as well a...
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作者：Banerjee, Sid; Hssaine, Chamsi; Sinclair, Sean R.
作者单位：Cornell University; University of Southern California; Northwestern University
摘要：We consider a practically motivated variant of the canonical online fair allocation problem: A decision maker has a budget of perishable resources to allocate over a fixed number of rounds. Each round sees a random number of arrivals, and the decision maker must commit to an allocation for these individuals before moving on to the next round. The goal is to construct a sequence of allocations that is envy-free and efficient. Our work makes two important contributions toward this problem: We fi...
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作者：Ata, Baris; Lehman, Amy; Montgomery, Robert John
作者单位：University of Chicago; University of California System; University of California San Diego
摘要：This paper studies inventory management policies to improve the last-mile delivery of healthcare products in remote settings prone to supply chain disruptions. It is motivated by the need for a reliable and cost-effective delivery system to resupply new mosquito-repellent products to combat malaria in the Lake Tanganyika region of the Democratic Republic of the Congo. The primary delivery methods used to supply villages along Lake Tanganyika can become inoperable during periods of flooding, ma...
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作者：Ji, Jingwei; Xu, Renyuan; Zhu, Ruihao
作者单位：Stanford University; Cornell University
摘要：Motivated by practical considerations in machine learning for financial decision making, such as risk aversion and large action space, we consider risk-aware bandits optimization with applications in smart order routing (SOR). Specifically, based on preliminary observations of linear price impacts made from the Nasdaq TotalView-ITCH (NASDAQ ITCH) data set, we initiate the study of risk-aware linear bandits. In this setting, we aim at minimizing regret, which measures our performance deficit co...
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作者：Shafiee, Soroosh; Aolaritei, Liviu; Dorller, Florian; Kuhn, Daniel
作者单位：Cornell University; University of California System; University of California Berkeley; Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：We study optimal transport-based distributionally robust optimization problems in which a fictitious adversary, often envisioned as nature, can choose the distribution of the uncertain problem parameters by reshaping a prescribed reference distribution at a finite transportation cost. In this framework, we show that robustification is intimately related to various forms of variation and Lipschitz regularization even if the transportation cost function fails to be (some power of) a metric. We a...
