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作者：Liu, Yue; Fang, Ethan X.; Lu, Junwei
作者单位：Harvard University; Duke University; Harvard University; Harvard T.H. Chan School of Public Health
摘要：We propose a novel combinatorial inference framework to conduct general uncertainty quantification in ranking problems. We consider the widely adopted Bradley-Terry-Luce (BTL) model, where each item is assigned a positive preference score that determines the Bernoulli distributions of pairwise comparisons' outcomes. Our proposedmethod aims to infer general ranking properties of the BTLmodel. The general ranking properties include the local properties such as if an item is preferred over anothe...
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作者：Bai, Xingyu; Chen, Xin; Stolyar, Alexander L.
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign
摘要：We consider a partially observable lost-sales inventory system, in which the inventory level is observed only when it reaches zero. We use the vanishing discount factor approach to prove the existence of a stationary optimal policy for the average cost minimization. As our main methodological contribution, we provide a way to verify the key condition of the vanishing discount factor approach???the uniform boundedness of the relative discounted value function. To accomplish that, we construct a...
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作者：Li, Michael Lingzhi; Bouardi, Hamza Tazi; Lami, Omar Skali; Trikalinos, Thomas A.; Trichakis, Nikolaos; Bertsimas, Dimitris
作者单位：Massachusetts Institute of Technology (MIT); Brown University; Massachusetts Institute of Technology (MIT)
摘要：We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more than 200 geographical areas since early April 2020 and recorded 6% and 11% two-week, out-of-sample median mean absolute percentage error on predicting cases and deaths, respectively. DELPHI compares favorably with other top COVI...
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作者：Zhou, Zhengyuan; Athey, Susan; Wager, Stefan
作者单位：New York University; Stanford University
摘要：In many settings, a decision maker wishes to learn a rule, or policy, that maps from observable characteristics of an individual to an action. Examples include selecting offers, prices, advertisements, or emails to send to consumers, choosing a bid to submit in a contextual first-price auctions, and determining which medication to prescribe to a patient. In this paper, we study the offline multi-action policy learning problem with observational data and where the policy may need to respect bud...
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作者：Brown, David B.; Zhang, Jingwei
作者单位：Duke University
摘要：Many stochastic dynamic programs (DPs) have a weakly coupled structure in that a set of linking constraints in each period couples an otherwise independent collection of subproblems. Two widely studied approximations of such problems are approximate linear programs (ALPs), which involve optimizing value function approximations that additively separate across subproblems, and Lagrangian relaxations, which involve relaxing the linking constraints. It is well known that both of these approximatio...
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作者：Aouad, Ali; Segev, Danny
作者单位：University of London; London Business School; Tel Aviv University
摘要：We study the incremental knapsack problem, where one wishes to sequentially pack items into a knapsack whose capacity expands over a finite planning horizon, with the objective of maximizing time-averaged profits. Although various approximation algorithms were developed under mitigating structural assumptions, obtaining nontrivial performance guarantees for this problem in its utmost generality has remained an open question thus far. In this paper, we devise a polynomial-time approximation sch...
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作者：Mazumder, Rahul; Radchenko, Peter; Dedieuc, Antoine
作者单位：Massachusetts Institute of Technology (MIT); University of Sydney
摘要：We study a seemingly unexpected and relatively less understood overfitting aspect of a fundamental tool in sparse linear modeling-best subset selection-which minimizes the residual sum of squares subject to a constraint on the number of nonzero coefficients. Whereas the best subset selection procedure is often perceived as the gold standard in sparse learning when the signal-to-noise ratio (SNR) is high, its predictive performance deteriorates when the SNR is low. In particular, it is outperfo...
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作者：Balseiro, Santiago R.; Lu, Haihao; Mirrokni, Vahab
作者单位：Columbia University; Alphabet Inc.; Google Incorporated; University of Chicago
摘要：Online allocation problems with resource constraints are central problems in revenue management and online advertising. In these problems, requests arrive sequentially during a finite horizon and, for each request, a decision maker needs to choose an action that consumes a certain amount of resources and generates reward. The objective is to maximize cumulative rewards subject to a constraint on the total consumption of resources. In this paper, we consider a data-driven setting in which the r...
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作者：Kremer, Mirko; de Vericourt, Francis
作者单位：Frankfurt School Finance & Management; European School of Management & Technology
摘要：To study the effect of congestion on the fundamental tradeoff between diagnostic accuracy and speed, we empirically test the predictions of a formal sequential testing model in a setting where the gathering of additional information can improve diagnostic accuracy but may also take time and increase congestion as a result. The efficient management of such systems requires a careful balance of congestion-sensitive stopping rules. These include diagnoses made based on very little or no diagnosti...
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作者：Lamas-Fernandez, Carlos; Bennell, Julia A.; Martinez-Sykora, Antonio
作者单位：University of Southampton; Solent University; University of Leeds
摘要：Research on the three-dimensional (3D) packing problem has largely focused on packing boxes for the transportation of goods. As a result, there has been little focus on packing irregular shapes in the operational research literature. New technologies have raised the practical importance of 3D irregular packing problems and the need for efficient solutions. In this work, we address the variant of the problem where the aim is to place a set of 3D irregular items in a container, while minimizing ...
