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作者：Guo, Wenshuo; Haghtalab, Nika; Kandasamy, Kirthevasan; Vitercik, Ellen
作者单位：University of California System; University of California Berkeley; University of Wisconsin System; University of Wisconsin Madison; Stanford University
摘要：In online marketplaces, buyers often use reviews from other customers that share their type-such as height for clothing and skin type for skincare products-to estimate their values. Customers with few relevant reviews may hesitate to purchase except at a low price, so for the seller, there is a tension between setting high prices and ensuring there are enough reviews so buyers can confidently estimate their values. Simultaneously, sellers may use reviews to gauge the demand for items they wish...
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作者：Wen, Xin; Sun, Will Wei; Zhang, Yichen
作者单位：New York University; Purdue University System; Purdue University
摘要：Contemporary applications, such as recommendation systems and mobile health monitoring, require real-time processing and analysis of sequentially arriving highdimensional tensor data. Traditional offline learning, involving the storage and utilization of all data in each computational iteration, becomes impractical for these tasks. Furthermore, existing low-rank tensor methods lack the capability for online statistical inference, which is essential for real-time predictions and informed decisi...
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作者：Yue, Man-Chung; Rychener, Yves; Kuhn, Daniel; Nguyen, Viet Anh
作者单位：University of Hong Kong; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：The state-of-the-art methods for estimating high-dimensional covariance matrices all shrink the eigenvalues of the sample covariance matrix toward a data-insensitive shrinkage target. The underlying shrinkage transformation is either chosen heuristically-without compelling theoretical justification-or optimally in view of restrictive distributional assumptions. In this paper, we propose a principled approach to construct covariance estimators without imposing restrictive assumptions. That is, ...
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作者：Singhvi, Divya; Singhvi, Somya; Zhang, Xinyu
作者单位：New York University; University of Southern California
摘要：Despite their vital role in the global rural economy, and as a major source of employment for women in the developing world, artisanal supply chains continue to be plagued by low productivity and high poverty levels. Identifying effective and implementable solutions to improve artisan productivity is a challenging task due to high fragmentation in the upstream parts of the supply chain. This paper presents research conducted in close collaboration with one of the leading exporters of handmade ...
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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...
