4期

最新文章

• Characterizing Rational Transplant Program Response to Outcome-Based Regulation AI翻译
  作者：Mildebrath, David; Lee, Taewoo; Sinha, Saumya; J., Andrew; Gaber, A. Osama
  作者单位：Rice University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; University of Minnesota System; University of Minnesota Twin Cities; Houston Methodist
  摘要：Organ transplantation is an increasingly common therapy for many types of end-stage organ failure, including lungs, hearts, kidneys, and livers. The last 20 years have seen increased scrutiny of posttransplant outcomes in the United States to ensure the efficient utilization of the scarce organ supply. Under regulations by the Organ Procurement Transplantation Network (OPTN) and Centers for Medicare and Medicaid Services (CMS), the United States has seen a rise in risk-averse patient selection...
• Treatment Planning for Victims with Heterogeneous Time Sensitivities in Mass Casualty Incidents AI翻译
  作者：Shi, Yunting; Liu, Nan; Wan, Guohua
  作者单位：Shanghai Jiao Tong University; Boston College
  摘要：The current emergency response guidelines suggest giving priority of treatment to those victims whose initial health conditions are more critical. Although this makes intuitive sense, it does not consider potential deterioration of less critical victims. Deterioration may lead to longer treatment time and irrecoverable health damage, but could be avoided if these victims were to receive care in time. Informed by a unique timestamps data set of surgeries carried out in a field hospital set up i...
• Static Pricing for Multi-unit Prophet Inequalities AI翻译
  作者：Chawla, Shuchi; Devanur, Nikhil; Lykouris, Thodoris
  作者单位：University of Texas System; University of Texas Austin; Amazon.com; Massachusetts Institute of Technology (MIT)
  摘要：We study a pricing problem where a seller has k identical copies of a product, buyers arrive sequentially, and the seller prices the items aiming to maximize social welfare. When k =1, this is the so-called prophet inequality problem for which there is a simple pricing scheme achieving a competitive ratio of 1/2. On the other end of the spectrum, as k goes to infinity, the asymptotic performance of both static and adaptive pricing is well understood. We provide a static pricing scheme for the ...
• Comparing Sequential Forecasters AI翻译
  作者：Choe, Yo Joong; Ramdas, Aaditya
  作者单位：University of Chicago; Carnegie Mellon University
  摘要：Consider two forecasters, each making a single prediction for a sequence of events over time. We ask a relatively basic question: how might we compare these forecasters, either online or post hoc, avoiding unverifiable assumptions on how the forecasts and outcomes were generated? In this paper, we present a rigorous answer to this question by designing novel sequential inference procedures for estimating the time-varying difference in forecast scores. To do this, we employ confidence sequences...
• Assortment Optimization Under the Multinomial Logit Model with Utility-Based Rank Cutoffs AI翻译
  作者：Bai, Yicheng; Feldman, Jacob; Topaloglu, Huseyin; Wagner, Laura
  作者单位：Washington University (WUSTL); University of Navarra; IESE Business School
  摘要：We study assortment optimization problems under a natural variant of the multinomial logit model where the customers are willing to focus only on a certain number of products that provide the largest utilities. In particular, each customer has a rank cutoff, characterizing the number of products that she will focus on during the course of her choice process. Given that we offer a certain assortment of products, the choice process of a customer with rank cutoff k proceeds as follows. The custom...
• A Lyapunov Theory for Finite-Sample Guarantees of Markovian Stochastic Approximation AI翻译
  作者：Chen, Zaiwei; Maguluri, Siva T.; Shakkottai, Sanjay; Shanmugam, Karthikeyan
  作者单位：University System of Georgia; Georgia Institute of Technology; University of Texas System; University of Texas Austin
  摘要：This paper develops a unified Lyapunov framework for finite-sample analysis of a Markovian stochastic approximation (SA) algorithm under a contraction operator with respect to an arbitrary norm. The main novelty lies in the construction of a valid Lyapunov function called the generalized Moreau envelope. The smoothness and an approximation property of the generalized Moreau envelope enable us to derive a one-step Lyapunov drift inequality, which is the key to establishing the finite-sample bou...
• Technical Note-Asymptotically Optimal Control of Omnichannel Service Systems with Pick-up Guarantees AI翻译
  作者：Gao, Xuefeng; Huang, Junfei; Zhang, Jiheng
  作者单位：Chinese University of Hong Kong; Chinese University of Hong Kong; Hong Kong University of Science & Technology
  摘要：Motivated by the recent popularity of omnichannel service systems, we analyze the joint admission and scheduling control of a queueing system with two classes of customers: online and walk-in. Unlike walk-in customers, online customers are given a target time for pick up upon placing an order. Thus, in addition to minimizing the waiting costs of walk-in customers and the rejection cost of both classes, we need to minimize the earliness and tardiness costs of online customers. Such a distinctiv...
• Uncertainty Quantification and Exploration for Reinforcement Learning AI翻译
  作者：Zhu, Yi; Dong, Jing; Lam, Henry
  作者单位：Northwestern University; Columbia University; Columbia University
  摘要：We investigate statistical uncertainty quantification for reinforcement learning (RL) and its implications in exploration policy. Despite ever-growing literature on RL applications, fundamental questions about inference and error quantification, such as large-sample behaviors, appear to remain quite open. In this paper, we fill in the literature gap by studying the central limit theorem behaviors of estimated Q-values and value functions under various RL settings. In particular, we explicitly ...
• Best of Both Worlds: Ex Ante and Ex Post Fairness in Resource Allocation AI翻译
  作者：Aziz, Haris; Freeman, Rupert; Shah, Nisarg; Vaish, Rohit
  作者单位：University of New South Wales Sydney; University of Virginia; University of Toronto; Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Delhi
  摘要：We study the problem of allocating indivisible goods among agents with additive valuations. When randomization is allowed, it is possible to achieve compelling notions of fairness such as envy-freeness, which states that no agent should prefer any other agent's allocation to their own. When allocations must be deterministic, achieving exact fairness is impossible but approximate notions such as envy-freeness up to one good can be guaranteed. Our goal in this work is to achieve both simultaneou...
• Risk-Averse Regret Minimization in Multistage Stochastic Programs AI翻译
  作者：Poursoltani, Mehran; Delage, Erick; Georghiou, Angelos
  作者单位：Universite de Montreal; HEC Montreal; Universite de Montreal; HEC Montreal; University of Cyprus
  摘要：Within the context of optimization under uncertainty, a well-known alternative to minimizing expected value or the worst-case scenario consists in minimizing regret. In a multistage stochastic programming setting with a discrete probability distribution, we explore the idea of risk-averse regret minimization, where the benchmark policy can only benefit from foreseeing increment steps into the future. The increment -regret model naturally interpolates between the popular ex ante and ex post reg...