4期

最新文章

• Econometrics with Privacy Preservation AI翻译
  作者：Cai, Ning; Kou, Steven
  作者单位：Hong Kong University of Science & Technology; Boston University
  摘要：Many data are sensitive in areas such as finance, economics, and other social sciences. We propose an ER (encryption and recovery) algorithm that allows a central administration to do statistical inference based on the encrypted data, while still preserving each party's privacy even for a colluding majority in the presence of cyber attack. We demonstrate the applications of our algorithm to linear regression, logistic regression, maximum likelihood estimation, the method of moments, and estima...
• Technical Note-Optimizing Foreclosed Housing Acquisitions in Societal Response to Foreclosures AI翻译
  作者：Solak, Senay; Bayram, Armagan; Gumus, Mehmet; Zhuo, Yueran
  作者单位：University of Massachusetts System; University of Massachusetts Amherst; McGill University
  摘要：A dramatic increase in U.S. mortgage foreclosures during and after the great economic recession of 2007-2009 had devastating impacts on the society and the economy. In response to such negative impacts, nonprofit community development corporations (CDCs) throughout the United States use various resources, such as grants and lines of credit, in acquiring and redeveloping foreclosed housing units to support neighborhood stabilization and revitalization. Given that the cost of all such acquisitio...
• Portfolio Construction by Mitigating Error Amplification: The Bounded-Noise Portfolio AI翻译
  作者：Zhao, Long; Chakrabarti, Deepayan; Muthuraman, Kumar
  作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
  摘要：We address the problem of poor portfolio performance when a minimum-variance portfolio is constructed using the sample estimates. Estimation errors are mostly blamed for the poor portfolio performance. However, we argue that even small unbiased estimation errors can lead to significantly bad performance because the optimization step amplifies errors, in a nonsymmetric way. Instead of trying to independently improve the estimation step or fix the optimization step for robustness, we disentangle...
• Long-Term Partnership for Achieving Efficient Capacity Allocation AI翻译
  作者：Liu, Fang; Lewis, Tracy R.; Song, Jing-Sheng; Kuribko, Nataliya
  作者单位：Nanyang Technological University; Duke University
  摘要：We consider a capacity provider and a group of independent buyers who partner to share a scarce but expensive-to-build capacity over a finite horizon under privately informed demand conditions. At the beginning of the time horizon, the capacity provider must invest in building capacity; all members may invest in increasing their own and possibly other members' market sizes. Then each member observes and updates its private, history-dependent demand information over time. Because the value of t...
• Data-Driven Incentive Design in the Medicare Shared Savings Program AI翻译
  作者：Aswani, Anil; Shen, Zuo-Jun Max; Siddiq, Auyon
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley; University of California System; University of California Berkeley; University of California System; University of California Los Angeles
  摘要：The Medicare Shared Savings Program (MSSP) was created under the Patient Protection and Affordable Care Act to control escalating Medicare spending by incentivizing providers to deliver healthcare more efficiently. Medicare providers that enroll in the MSSP earn bonus payments for reducing spending to below a risk-adjusted financial benchmark that depends on the provider's historical spending. To generate savings, a provider must invest to improve efficiency, which is a cost that is absorbed e...
• Coordinating Pricing and Inventory Replenishment with Nonparametric Demand Learning AI翻译
  作者：Chen, Boxiao; Chao, Xiuli; Ahn, Hyun-Soo
  作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：We consider a firm (e.g., retailer) selling a single nonperishable product over a finite-period planning horizon. Demand in each period is stochastic and price sensitive, and unsatisfied demands are backlogged. At the beginning of each period, the firm determines its selling price and inventory replenishment quantity with the objective of maximizing total profit, but it knows neither the average demand (as a function of price) nor the distribution of demand uncertainty a priori; hence, it has ...
• Dynamic Selling Mechanisms for Product Differentiation and Learning AI翻译
  作者：Keskin, N. Bora; Birge, John R.
  作者单位：Duke University; University of Chicago
  摘要：We consider a firm that designs a vertically differentiated product line for a population of customers with heterogeneous quality sensitivities. The firm faces an uncertainty about the cost of quality, and we formulate this uncertainty as a belief distribution on a set of cost models. Over a time horizon of T periods, the firm can dynamically adjust its menu and make noisy observations on the underlying cost model through customers' purchasing decisions. We characterize how optimal product dif...
• Recovering Best Statistical Guarantees via the Empirical Divergence-Based Distributionally Robust Optimization AI翻译
  作者：Lam, Henry
  作者单位：Columbia University
  摘要：We investigate the use of distributionally robust optimization (DRO) as a tractable tool to recover the asymptotic statistical guarantees provided by the central limit theorem, for maintaining the feasibility of an expected value constraint under ambiguous probability distributions. We show that using empirically defined Burg-entropy divergence balls to construct the DRO can attain such guarantees. These balls, however, are not reasoned from the standard data-driven DRO framework because, by t...
• The Weighted Nonnegative Least-Squares Problem with Implicitly Characterized Points AI翻译
  作者：Fattahi, Ali; Dasu, Sriram; Ahmadi, Reza
  作者单位：University of California System; University of California Los Angeles; University of Southern California
  摘要：The nonnegative least-squares (NNLS) problem is defined as finding the Euclidean distance to a convex cone generated by a set of discrete points in R. In this paper, we study NNLS when the discrete points are implicitly known and there are an exponentially large number of them (e.g., the set of integer feasible solutions of a mixed-integer program). This problem is motivated by a large auto manufacturer that produces mass customized products where the products are configured by choosing a subs...
• Mass Customization and Forecasting Options' Penetration Rates Problem AI翻译
  作者：Fattahi, Ali; Dasu, Sriram; Ahmadi, Reza
  作者单位：University of California System; University of California Los Angeles; University of Southern California
  摘要：Auto manufacturers produce a very large number of feasible configurations that make it impossible to forecast the demand of individual configurations. What the companies do forecast is the penetration rate of each option, which is the percentage of cars that include that option. The current forecasting approach ignores rules for selecting options, and as a result, forecast penetration rates are frequently infeasible, which results in excess inventories, shortages, and customer dissatisfaction....