550期

最新文章

• Euclidean Mirrors and Dynamics in Network Time Series AI翻译
  作者：Athreya, Avanti; Lubberts, Zachary; Park, Youngser; Priebe, Carey
  作者单位：Johns Hopkins University; University of Virginia; Johns Hopkins University
  摘要：Analyzing changes in network evolution is central to statistical network inference. We consider a dynamic network model in which each node has an associated time-varying low-dimensional latent vector of feature data, and connection probabilities are functions of these vectors. Under mild assumptions, the evolution of latent vectors exhibits low-dimensional manifold structure under a suitable distance. This distance can be approximated by a measure of separation between the observed networks th...
• Off-Policy Evaluation in Doubly Inhomogeneous Environments AI翻译
  作者：Bian, Zeyu; Shi, Chengchun; Qi, Zhengling; Wang, Lan
  作者单位：University of Miami; University of London; London School Economics & Political Science; George Washington University
  摘要：This work aims to study off-policy evaluation (OPE) under scenarios where two key reinforcement learning (RL) assumptions-temporal stationarity and individual homogeneity are both violated. To handle the double inhomogeneities, we propose a class of latent factor models for the reward and transition functions, under which we develop a general OPE framework that consists of both model-based and model-free approaches. To our knowledge, this is the first article that develops statistically sound ...
• GeoWarp: Warped Spatial Processes for Inferring Subsea Sediment Properties AI翻译
  作者：Bertolacci, Michael; Zammit-Mangion, Andrew; Giraldo, Juan Valderrama; O'Neill, Michael; Bransby, Fraser; Watson, Phil
  作者单位：University of Western Australia; University of Wollongong; University of Western Australia
  摘要：For offshore structures like wind turbines, subsea infrastructure, pipelines, and cables, it is crucial to quantify the properties of the seabed sediments at a proposed site. However, data collection offshore is costly, so analysis of the seabed sediments must be made from measurements that are spatially sparse. Adding to this challenge, the structure of the seabed sediments exhibits both nonstationarity and anisotropy. To address these issues, we propose GeoWarp, a hierarchical spatial statis...
• Space-Time Extremes of Severe US Thunderstorm Environments AI翻译
  作者：Koh, Jonathan; Koch, Erwan; Davison, Anthony C.
  作者单位：University of Bern; University of Lausanne; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
  摘要：Severe thunderstorms cause substantial economic and human losses in the United States. Simultaneous high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are favorable to severe weather, and both they and the composite variable PROD=CAPExSRH can be used as indicators of severe thunderstorm activity. Their extremal spatial dependence exhibits temporal non-stationarity due to seasonality and large-scale atmospheric signals such as El Ni & ntilde;o-Southern...
• Robust Matrix Completion with Heavy-Tailed Noise AI翻译
  作者：Wang, Bingyan; Fan, Jianqing
  作者单位：Princeton University
  摘要：This article studies noisy low-rank matrix completion in the presence of heavy-tailed and possibly asymmetric noise, where we aim to estimate an underlying low-rank matrix given a set of highly incomplete noisy entries. Though the matrix completion problem has attracted much attention in the past decade, there is still lack of theoretical understanding when the observations are contaminated by heavy-tailed noises. Prior theory falls short of explaining the empirical results and is unable to ca...
• Statistical Inference for Hüsler-Reiss Graphical Models Through Matrix Completions AI翻译
  作者：Hentschel, Manuel; Engelke, Sebastian; Segers, Johan
  作者单位：University of Geneva; Universite Catholique Louvain
  摘要：The severity of multivariate extreme events is driven by the dependence between the largest marginal observations. The H & uuml;sler-Reiss distribution is a versatile model for this extremal dependence, and it is usually parameterized by a variogram matrix. In order to represent conditional independence relations and obtain sparse parameterizations, we introduce the novel H & uuml;sler-Reiss precision matrix. Similarly to the Gaussian case, this matrix appears naturally in density representati...
• On Optimality of Mallows Model Averaging AI翻译
  作者：Peng, Jingfu; Li, Yang; Yang, Yuhong
  作者单位：Tsinghua University; Renmin University of China; Renmin University of China
  摘要：In the past decades, model averaging (MA) has attracted much attention as it has emerged as an alternative tool to the model selection (MS) statistical approach. Hansen introduced a Mallows model averaging (MMA) method with model weights selected by minimizing a Mallows' Cp criterion. The main theoretical justification for MMA is an asymptotic optimality (AOP), which states that the risk/loss of the resulting MA estimator is asymptotically equivalent to that of the best but infeasible averaged...
• Model-Based Clustering of Categorical Data Based on the Hamming Distance AI翻译
  作者：Argiento, Raffaele; Filippi-Mazzola, Edoardo; Paci, Lucia
  作者单位：University of Bergamo; Universita della Svizzera Italiana; Catholic University of the Sacred Heart
  摘要：A model-based approach is developed for clustering categorical data with no natural ordering. The proposed method exploits the Hamming distance to define a family of probability mass functions to model the data. The elements of this family are then considered as kernels of a finite mixture model with an unknown number of components. Conjugate Bayesian inference has been derived for the parameters of the Hamming distribution model. The mixture is framed in a Bayesian nonparametric setting, and ...
• Natural Gradient Variational Bayes Without Fisher Matrix Analytic Calculation and Its Inversion AI翻译
  作者：Godichon-Baggioni, A.; Nguyen, D.; Tran, M. -n.
  作者单位：Universite Paris Cite; Sorbonne Universite; Marist College; University of Sydney
  摘要：This article introduces a method for efficiently approximating the inverse of the Fisher information matrix, a crucial step in achieving effective variational Bayes inference. A notable aspect of our approach is the avoidance of analytically computing the Fisher information matrix and its explicit inversion. Instead, we introduce an iterative procedure for generating a sequence of matrices that converge to the inverse of Fisher information. The natural gradient variational Bayes algorithm with...
• Rate-Optimal Rank Aggregation with Private Pairwise Rankings AI翻译
  作者：Xu, Shirong; Sun, Will Wei; Cheng, Guang
  作者单位：University of California System; University of California Los Angeles; Purdue University System; Purdue University
  摘要：In various real-world scenarios, such as recommender systems and political surveys, pairwise rankings are commonly collected and used for rank aggregation to derive an overall ranking of items. However, preference rankings can reveal individuals' personal preferences, highlighting the need to protect them from exposure in downstream analysis. In this article, we address the challenge of preserving privacy while ensuring the utility of rank aggregation based on pairwise rankings generated from ...