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作者：Cao, Jian; Katzfuss, Matthias
作者单位：University of Houston System; University of Houston; University of Wisconsin System; University of Wisconsin Madison
摘要：Multivariate normal (MVN) probabilities arise in myriad applications, but they are analytically intractable and need to be evaluated via Monte Carlo-based numerical integration. For the state-of-the-art minimax exponential tilting (MET) method, we show that the complexity of each of its components can be greatly reduced through an integrand parameterization that uses the sparse inverse Cholesky factor produced by the Vecchia approximation, whose approximation error is often negligible relative...
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作者：He, Chenxuan; Chen, Canyi; Zhu, Liping
作者单位：Renmin University of China; University of Michigan System; University of Michigan
摘要：Black-box learners have demonstrated remarkable success across various fields due to their high predictive accuracy. However, the complexity of their learning procedures poses significant challenges in evaluating whether a given learner has achieved optimal performance on datasets with unknown data-generating mechanisms. We propose a general goodness-of-fit test for assessing different learning procedures involving high-dimensional predictors, encompassing methods from classical linear regress...
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作者：Garcia-Portugues, Eduardo; Meilan-Vila, Andrea
作者单位：Universidad Carlos III de Madrid
摘要：A kernel density estimator for data on the polysphere S(d1)x & ctdot;xS(dr), with r,d(1),& mldr;,d(r)>= 1, is presented in this article. We derive the main asymptotic properties of the estimator, including mean square error, normality, and optimal bandwidths. We address the kernel theory of the estimator beyond the von Mises-Fisher kernel, introducing new kernels that are more efficient and investigating normalizing constants, moments, and sampling methods thereof. Plug-in and cross-validated ...
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作者：Lin, Xihong
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University
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作者：Chen, Elynn; Chen, Xi; Jing, Wenbo
作者单位：New York University; City University of Hong Kong
摘要：In data-driven decision-making across marketing, healthcare, and education, leveraging large datasets from existing ventures is crucial for navigating high-dimensional feature spaces and addressing data scarcity in new ventures. We investigate knowledge transfer in dynamic decision-making by focusing on batch stationary environments and formally defining task discrepancies through the framework of Markov decision processes (MDPs). We propose the Transfer Fitted Q-Iteration algorithm with gener...
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作者：Han, Jiale; Dai, Xiaowu
作者单位：University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
摘要：Online auction is a cornerstone of e-commerce, and a key challenge is designing incentive-compatible mechanisms that maximize expected revenue. Existing approaches often assume known bidder value distributions and fixed sets of bidders and items, but these assumptions rarely hold in real-world settings where bidder values are unknown, and the number of future participants is uncertain. In this article, we introduce the Conformal Online Auction Design (COAD), a novel mechanism that maximizes re...
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作者：Kwon, Yonghyun; Kim, Jae Kwang; Qiu, Yumou
作者单位：Iowa State University; Peking University; Peking University
摘要：Incorporating auxiliary information into the survey estimation is a fundamental problem in survey sampling. Calibration weighting is a widely used technique to integrate such information by adjusting design weights to meet benchmarking constraints. Traditional methods, such as those proposed by Deville and S & auml;rndal, solve this problem by minimizing a distance between calibrated and design weights. In this article, we propose a novel calibration framework that instead maximizes a generali...
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作者：Wang, Siyao; Lopes, Miles E.
作者单位：University of California System; University of California Davis
摘要：Due to the broad applications of elliptical models, there is a long line of research on goodness-of-fit tests for empirically validating them. However, the existing literature on this topic is generally confined to low-dimensional settings, and to the best of our knowledge, there are no established goodness-of-fit tests for elliptical models that are supported by theoretical guarantees in high dimensions. In this article, we propose a new goodness-of-fit test for this problem, and our main res...
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作者：Ma, Tianwen; Huggins, Jane E.; Kang, Jian
作者单位：Emory University; Rollins School Public Health; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
摘要：An Event-Related Potential (ERP)-based Brain-Computer Interface (BCI) Speller System assists people with disabilities to communicate by decoding electroencephalogram (EEG) signals. A P300-ERP embedded in EEG signals arises in response to a rare, but relevant event (target) among a series of irrelevant events (non-target). Different machine learning methods have constructed binary classifiers to detect target events, known as calibration. The existing calibration strategy uses data from partici...
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作者：Zhou, Zheng; Mee, Robert; Hamers, Herbert; Zheng, Wei
作者单位：Beijing University of Technology; University of Tennessee System; University of Tennessee Knoxville; Tilburg University; Tilburg University
摘要：The Shapley value is a well-known concept in cooperative game theory that provides a fair way to distribute revenues or costs among players. It has found applications in many fields besides economics, such as marketing and biology. Recently, it has been widely applied in data science for data quality evaluation and model interpretation. However, the computation of the Shapley value is an NP-hard problem. For a cooperative game with n players, calculating Shapley values for all players requires...
