2023

最新文章

• Differential Privacy in Personalized Pricing with Nonparametric Demand Models AI翻译
  作者：Chen, Xi; Miao, Sentao; Wang, Yining
  作者单位：New York University; McGill University; University of Texas System; University of Texas Dallas
  摘要：In recent decades, the advance of information technology and abundant personal data facilitate the application of algorithmic personalized pricing. However, this leads to the growing concern of potential violation of privacy because of adversarial attack. To address the privacy issue, this paper studies a dynamic personalized pricing problem with unknown nonparametric demand models under data privacy protection. Two concepts of data privacy, which have been widely applied in practices, are int...
• Preface to Special Issue on Computational Advances in Short-Term Power System Operations AI翻译
  作者：Baldick, Ross; Low, Steven; O'Neill, Richard; Ralph, Daniel; Zakeri, Golbon
  作者单位：University of Texas System; University of Texas Austin; California Institute of Technology; United States Department of Energy (DOE); Advanced Research Projects Agency-Energy (ARPA-E); University of Cambridge; University of Massachusetts System; University of Massachusetts Amherst
• Optimal Subscription Planning for Digital Goods AI翻译
  作者：Alaei, Saeed; Makhdoumi, Ali; Malekian, Azarakhsh
  作者单位：Alphabet Inc.; Google Incorporated; Duke University; University of Toronto
  摘要：We consider a media service provider that gives users access to digital goods through subscription. In our model, different types of users with heterogeneous usage rates repeatedly use a platform over a period of time. There are multiple item types on the platform, and the value of an item to a user is random and depends on both the user type and the item type. The design of the platform's subscription planning comprises selecting a subscription fee for each set of item types. Before the begin...
• Using Hospital Admission Predictions at Triage for Improving Patient Length of Stay in Emergency Departments AI翻译
  作者：Chen, Wanyi; Argon, Nilay Tanik; Bohrmann, Tommy; Linthicum, Benjamin; Lopiano, Kenneth; Mehrotra, Abhishek; Travers, Debbie; Ziya, Serhan
  作者单位：Harvard University; Harvard Medical School; Harvard University Medical Affiliates; Massachusetts General Hospital; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Duke University
  摘要：Long boarding times have long been recognized as one of the main reasons behind emergency department (ED) crowding. One of the suggestions made in the literature to reduce boarding times was to predict, at the time of triage, whether a patient will eventually be admitted to the hospital and if the prediction turns out to be admit, start preparations for the patient's transfer to the main hospital early in the ED visit. However, there has been no systematic effort in developing a method to help...
• Optimal Pricing and Introduction Timing of Technology Upgrades in Subscription-Based Services AI翻译
  作者：Kash, Ian A.; Key, Peter B.; Zoumpoulis, Spyros I.
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; INSEAD Business School
  摘要：In the context of subscription-based services, many technologies improve over time, and service providers can provide increasingly powerful service upgrades to their customers but at a launching cost and the expense of the sales of existing products. We propose a model of technology upgrades and characterize the optimal pricing and timing of technology introductions for a service provider who price-discriminates among customers based on their upgrade experience in the face of customers who are...
• Information Retrieval Under Network Uncertainty: Robust Internet Ranking AI翻译
  作者：Timonina-Farkas, Anna; Seifert, Ralf W.
  作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; International Institute for Management Development (IMD)
  摘要：Internet ranking algorithms play a crucial role in information technologies and numerical analysis due to their efficiency in high dimensions and wide range of possible applications, including scientometrics and systemic risk in finance (SinkRank, DebtRank, etc.). The traditional approach to internet ranking goes back to the seminal work of Sergey Brin and Larry Page, who developed the initial method PageRank (PR) in order to rank websites in search engine results. Recent works have studied ro...
• Stability and Sample-Based Approximations of Composite Stochastic Optimization Problems AI翻译
  作者：Dentcheva, Darinka; Lin, Yang; Penev, Spiridon
  作者单位：Stevens Institute of Technology; University of New South Wales Sydney; University of New South Wales Sydney
  摘要：Optimization under uncertainty and risk is indispensable in many practical situations. Our paper addresses stability of optimization problems using composite risk functionals that are subjected to multiple measure perturbations. Our main focus is the asymptotic behavior of data-driven formulations with empirical or smoothing estimators such as kernels or wavelets applied to some or to all functions of the compositions. We analyze the properties of the new estimators and we establish strong law...
• Dynamic Pricing and Matching for Two-Sided Queues AI翻译
  作者：Varma, Sushil Mahavir; Bumpensanti, Pornpawee; Maguluri, Siva Theja; Wang, He
  作者单位：University System of Georgia; Georgia Institute of Technology
  摘要：Motivated by applications from gig economy and online marketplaces, we study a two-sided queueing system under joint pricing and matching controls. The queueing systemismodeled by a bipartite graph, where the vertices represent customer or server types and the edges represent compatible customer-server pairs. Both customers and servers sequentially arrive to the system and join separate queues according to their types. The arrival rates of different types depend on the prices set by the system...
• Dynamic Programming Principles for Mean-Field Controls with Learning AI翻译
  作者：Gu, Haotian; Guo, Xin; Wei, Xiaoli; Xu, Renyuan
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley; Tsinghua Shenzhen International Graduate School; University of Southern California
  摘要：The dynamic programming principle (DPP) is fundamental for control and optimization, including Markov decision problems (MDPs), reinforcement learning (RL), and, more recently, mean-field controls (MFCs). However, in the learning framework of MFCs, the DPP has not been rigorously established, despite its critical importance for algorithm designs. In this paper, we first present a simple example in MFCs with learning where the DPP fails with a misspecified Q function and then propose the correc...
• From Proper Scoring Rules to Max-Min Optimal Forecast Aggregation AI翻译
  作者：Neyman, Eric; Roughgarden, Tim
  作者单位：Columbia University
  摘要：This paper forges a strong connection between two seemingly unrelated forecasting problems: incentive-compatible forecast elicitation and forecast aggregation. Proper scoring rules are the well-known solution to the former problem. To each such rule s, we associate a corresponding method of aggregation, mapping expert forecasts and expert weights to a consensus forecast, which we call quasi-arithmetic (QA) pooling with respect to s. We justify this correspondence in several ways: QA pooling wi...