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作者：Ciocan, Dragos Florin; Iyer, Krishnamurthy
作者单位：INSEAD Business School; University of Minnesota System; University of Minnesota Twin Cities
摘要：We consider an ad network's problem of allocating the auction for each individual impression to an optimal subset of advertisers with the goal of revenue maximization. This is a variant of bipartite matching except that advertisers may strategize by choosing their bidding profiles and their total budget. Because the ad network's allocation rule affects the bidders' strategies, equilibrium analysis is challenging. We show that this analysis is tractable when advertisers face a linear budget cos...
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作者：Anton, Elene; Ayesta, Urtzi; Jonckheere, Matthieu; Verloop, Ina Maria
作者单位：Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Universite Federale Toulouse Midi-Pyrenees (ComUE); Institut National Polytechnique de Toulouse; Centre National de la Recherche Scientifique (CNRS); Centre National de la Recherche Scientifique (CNRS); CNRS - Institute of Physics (INP); Universite Federale Toulouse Midi-Pyrenees (ComUE); Universite de Toulouse; Institut National Polytechnique de Toulouse; Basque Foundation for Science; University of Basque Country; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET); University of Buenos Aires
摘要：We investigate the stability condition of redundancy-d multiserver systems. Each server has its own queue and implements popular scheduling disciplines such as first-come-first-serve (FCFS), processor sharing (PS), and random order of service (ROS). New jobs arrive according to a Poisson process, and copies of each job are sent to d servers chosen uniformly at random. The service times of jobs are assumed to be exponentially distributed. A job departs as soon as one of its copies finishes serv...
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作者：Kim, Anthony; Mirrokni, Vahab; Nazerzadeh, Hamid
作者单位：Amazon.com; Alphabet Inc.; Google Incorporated; University of Southern California
摘要：We present a formal study of first-look and preferred deals that are a recently introduced generation of contracts for selling online advertisements, which generalize traditional reservation contracts and are suitable for advertisers with advanced targeting capabilities. Under these deals, one or more advertisers gain priority access to an inventory of impressions before others and can choose to purchase in real time. In particular, we propose constant-factor approximation algorithms for maxim...
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作者：Tsitsiklis, John N.; Xu, Kuang; Xu, Zhi
作者单位：Massachusetts Institute of Technology (MIT); Stanford University
摘要：We formulate a private learning model to study an intrinsic tradeoff between privacy and query complexity in sequential learning. Our model involves a learner who aims to determine a scalar value v* by sequentially querying an external database and receiving binary responses. In the meantime, an adversary observes the learner's queries, although not the responses, and tries to infer from them the value of v*. The objective of the learner is to obtain an accurate estimate of v* using only a sma...
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作者：Eeckhoudt, Louis R.; Laeven, Roger J. A.
作者单位：University of Amsterdam; Tilburg University
摘要：In decision under risk, the primal moments of mean and variance play a central role to define the local index of absolute risk aversion. In this paper, we show that in the canonical nonexpected utility models provided by the dual theory and rank-dependent utility, dual moments have to be used instead of, or on par with, their primal counterparts to obtain an equivalent index of absolute risk aversion.
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作者：Chen, Xin; Long, Daniel Zhuoyu; Qi, Jin
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; Chinese University of Hong Kong; Hong Kong University of Science & Technology
摘要：This paper presents a systematic study of the preservation of supermodularity under parametric optimization, allowing us to derive complementarity among parameters and monotonic structural properties for optimal policies in many operational models. We introduce the new concepts of mostly sublattice and additive mostly sublattice, which generalize the commonly imposed sublattice condition significantly, and use them to establish the necessary and sufficient conditions for the feasible set so th...
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作者：Brown, David B.; Zhang, Jingwei
作者单位：Duke University
摘要：We consider a sequential decision problem involving shared resources and signals in which a decision maker repeatedly observes some exogenous information (the signal), modeled as a finite-state Markov process, then allocates a limited amount of a shared resource across a set of projects. The framework includes a number of applications and generalizes Markovian multiarmed bandit problems by (a) incorporating exogenous information through the signal and (b) allowing for more general resource all...
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作者：Aflaki, Arian; Swinney, Robert
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Duke University
摘要：We study the value of inventory integration (or pooling) for a firm selling a seasonal good over two periods: in the first period the firm charges a high price, and in the second period the firm charges a low price to clear remaining inventory. Consumers are rational and decide when to visit the firm based on the price of the product and its anticipated availability. We show that integration-which combines inventory from distinct selling channels or geographic regions, for example, online and ...
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作者：Xin, Linwei
作者单位：University of Chicago
摘要：Single-sourcing lost-sales inventory systems with lead times are notoriously difficult to optimize. In this paper, we propose a new family of capped base-stock policies and provide a new perspective on constructing a practical hybrid policy combining two well-known heuristics: base-stock and constant-order policies. Each capped base-stock policy is associated with two parameters: a base-stock level and an order cap. We prove that for any fixed order cap, the capped base-stock policy converges ...
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作者：Dey, Santanu S.; Mazumder, Rahul; Wang, Guanyi
作者单位：University System of Georgia; Georgia Institute of Technology; Massachusetts Institute of Technology (MIT)
摘要：Principal component analysis (PCA) is one of the most widely used dimensionality reduction tools in scientific data analysis. The PCA direction, given by the leading eigenvector of a covariance matrix, is a linear combination of all features with nonzero loadings; this impedes interpretability. Sparse principal component analysis (SPCA) is a framework that enhances interpretability by incorporating an additional sparsity requirement in the feature weights (factor loadings) while finding a dire...
