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作者：Abdallah, Tarek; Braverman, Anton; Gu, Wenhao
作者单位：Northwestern University
摘要：The static assortment optimization problem, where customers select a single item according to some choice model such as a random utility model, is a classical and well-studied setting. In contrast, the multipurchase variant, where customers may choose multiple items, has received far less attention because modeling utility-maximizing behavior over sets of items is substantially more complex, even under natural extensions of the Multinomial Logit model. In this paper, we propose a general multi...
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作者：Daw, Andrew; Yom-Tov, Galit B.
作者单位：University of Southern California; Technion Israel Institute of Technology
摘要：On many dimensions, services can be seen to exist along spectra measuring the degree of interaction between customer and agent. For instance, every interaction features some number of contributions by each of those two sides, creating a spectrum of interdependence. Additionally, each interaction is further characterized by the relative pacing of these contributions, implying a spectrum of synchronicity. Where a service falls on such spectra can be a consequence of its design, but it can also b...
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作者：Grand-Clement, Julien; Petrik, Marek; Vieille, Nicolas
作者单位：University System Of New Hampshire; University of New Hampshire
摘要：Robust Markov decision processes (RMDPs) are a widely used framework for sequential decision-making under parameter uncertainty. RMDPs have been studied extensively when the objective was to maximize the discounted return, but little is known for average optimality (optimizing the long-run average of the rewards obtained over time) and Blackwell optimality (remaining discount optimal for all discount factors sufficiently close to 1). In this paper, we prove several foundational results for RMD...
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作者：Ge, Puyao; Kulkarni, Vidyadhar G.; Swaminathan, Tayashankar M.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：We consider the problem of allocating a single type of resource with limited supply to distinct groups, each with a finite population and characterized by a unique reward and arrival rate. We develop a stochastic model and formulate the problem as a Markov decision process. We study the structural properties of the optimal value function and derive the optimal allocation policy. Contrary to the conventional approach of incrementally extending access to groups of lower priority over time, our f...
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作者：Cory-Wright, Ryan; Pauphilet, Jean
作者单位：University of London; London Business School
摘要：Sparse principal component analysis (PCA) is a fundamental technique for obtaining interpretable combinations of features, or principal components (PCs), that explain the variance of high-dimensional data sets. This involves solving a sparsity- and orthogonality-constrained convex maximization problem, which is extremely computationally challenging. Most existing work addresses sparse PCA via methods-such as iteratively computing one sparse PC and deflating the covariance matrix-that do not gu...
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作者：Light, Bar
作者单位：National University of Singapore; National University of Singapore
摘要：We study the properties of a subclass of stochastic processes called discrete-time nonlinear Markov chains with an aggregator, which naturally appear in various topics such as strategic queueing systems, inventory dynamics, opinion dynamics, and wealth dynamics. In these chains, the next period's distribution depends on both the current state and a real-valued function of the current distribution. For these chains, we provide conditions for the uniqueness of an invariant distribution that do n...
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作者：Aouad, Ali; Ji, Jingwei; Shaposhnik, Yaron
作者单位：Massachusetts Institute of Technology (MIT); Stanford University; University of Rochester
摘要：The Pandora's box problem is a core model in economic theory that captures an agent's (Pandora's) search for the best alternative (box). We study an important generalization of the problem in which the agent can either fully open boxes for a certain fee to reveal their exact values or partially open them at a reduced cost. This introduces a new trade-off between information acquisition and cost efficiency. We establish a hardness result and employ an array of techniques in stochastic optimizat...
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作者：Thomae, Simon; Schiffer, Maximilian; Wiesemann, Wolfram
作者单位：RWTH Aachen University; Technical University of Munich; Technical University of Munich; Imperial College London
摘要：Multistage decision making under uncertainty, where decisions are taken under sequentially revealing uncertain problem parameters, is often essential to faithfully model managerial problems. Given the significant computational challenges involved, these problems are typically solved approximately. This short note introduces an algorithmic framework that revisits a popular approximation scheme for multistage stochastic programs and improves on it to deliver superior policies in the stochastic s...
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作者：Qu, Zhaonan; Galichon, Alfred; Gao, Wenzhi; Ugander, Johan
作者单位：New Jersey Institute of Technology; Columbia University; New York University; New York University; Institut d'Etudes Politiques Paris (Sciences Po); Stanford University; Stanford University
摘要：For a broad class of models widely used in practice for choice and ranking data based on the Luce choice axiom, including the Bradley-Terry-Luce and Plackett-Luce models, we show that the associated maximum likelihood estimation problems are equivalent to a classic matrix-balancing problem with target row and column sums. This perspective opens doors between two seemingly unrelated research areas and allows us to unify existing algorithms in the choice-modeling literature as special instances ...
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作者：Mao, Cheng; Wu, Yihong; Xu, Jiaming; Yu, Sophie H.
作者单位：University System of Georgia; Georgia Institute of Technology; Yale University; Duke University; University of Pennsylvania
摘要：We propose an efficient algorithm for graph matching based on similarity scores constructed from counting a certain family of weighted trees rooted at each vertex. For two Erdos-Renyi graphs G(n,q) whose edges are correlated through a latent vertex correspondence, we show that this algorithm correctly matches all but a vanishing fraction of the vertices with high probability, provided that nq -> infinity and the edge correlation coefficient rho satisfies rho(2) > alpha approximate to 0:338, wh...
