2024

最新文章

• Gradient synchronization for multivariate functional data, with application to brain connectivity AI翻译
  作者：Chen, Yaqing; Lin, Shu-Chin; Zhou, Yang; Carmichael, Owen; Mueller, Hans-Georg; Wang, Jane-Ling
  作者单位：Rutgers University System; Rutgers University New Brunswick; University of California System; University of California Davis; Louisiana State University System; Louisiana State University; Pennington Biomedical Research Center
  摘要：Quantifying the association between components of multivariate random curves is of general interest and is a ubiquitous and basic problem that can be addressed with functional data analysis. An important application is the problem of assessing functional connectivity based on functional magnetic resonance imaging (fMRI), where one aims to determine the similarity of fMRI time courses that are recorded on anatomically separated brain regions. In the functional brain connectivity literature, the...
• Integrative conformal p-values for out-of-distribution testing with labelled outliers AI翻译
  作者：Liang, Ziyi; Sesia, Matteo; Sun, Wenguang
  作者单位：University of Southern California; University of Southern California; Zhejiang University; Zhejiang University
  摘要：This paper presents a conformal inference method for out-of-distribution testing that leverages side information from labelled outliers, which are commonly underutilized or even discarded by conventional conformal p-values. This solution is practical and blends inductive and transductive inference strategies to adaptively weight conformal p-values, while also automatically leveraging the most powerful model from a collection of one-class and binary classifiers. Further, this approach leads to ...
• Least squares estimation of a quasiconvex regression function AI翻译
  作者：Mukherjee, Somabha; Patra, Rohit K.; Johnson, Andrew L.; Morita, Hiroshi
  作者单位：National University of Singapore; State University System of Florida; University of Florida; Texas A&M University System; Texas A&M University College Station; University of Osaka
  摘要：We develop a new approach for the estimation of a multivariate function based on the economic axioms of quasiconvexity (and monotonicity). On the computational side, we prove the existence of the quasiconvex constrained least squares estimator (LSE) and provide a characterisation of the function space to compute the LSE via a mixed-integer quadratic programme. On the theoretical side, we provide finite sample risk bounds for the LSE via a sharp oracle inequality. Our results allow for errors t...
• Mode-wise principal subspace pursuit and matrix spiked covariance model AI翻译
  作者：Tang, Runshi; Yuan, Ming; Zhang, Anru R.
  作者单位：University of Wisconsin System; University of Wisconsin Madison; Columbia University; Duke University
  摘要：This paper introduces a novel framework called Mode-wise Principal Subspace Pursuit (MOP-UP) to extract hidden variations in both the row and column dimensions for matrix data. To enhance the understanding of the framework, we introduce a class of matrix-variate spiked covariance models that serve as inspiration for the development of the MOP-UP algorithm. The MOP-UP algorithm consists of two steps: Average Subspace Capture (ASC) and Alternating Projection. These steps are specifically designe...
• Jason Wyse, James Ng, Arthur White and Michael Fop's contribution to the Discussion of 'Root and community inference on the latent growth process of a network' by Crane and Xu AI翻译
  作者：Wyse, Jason; Ng, James; White, Arthur; Fop, Michael
  作者单位：Trinity College Dublin; University College Dublin
• Andi Wang's contribution to the Discussion of 'the Discussion Meeting on Probabilistic and statistical aspects of machine learning' AI翻译
  作者：Li, Jie; Fearnhead, Paul; Fryzlewicz, Piotr; Wang, Tengyao
  作者单位：University of London; London School Economics & Political Science; Lancaster University
• Bayesian inference with the L1-ball prior: solving combinatorial problems with exact zeros AI翻译
  作者：Xu, Maoran; Duan, Leo L.
  作者单位：Duke University; State University System of Florida; University of Florida; State University System of Florida; University of Florida
  摘要：The l(1)-regularisation is very popular in high-dimensional statistics-it changes a combinatorial problem of choosing which subset of the parameter is zero, into a simple continuous optimisation. Using a continuous prior concentrated near zero, the Bayesian counterparts are successful in quantifying the uncertainty in the variable selection problems; nevertheless, the lack of exact zeros makes it difficult for broader problems such as change-point detection and rank selection. Inspired by the ...
• Joshua Bon and Christian P. Robert's contribution to the Discussion of 'Safe testing' by Grünwald, de Heide, and Koolen AI翻译
  作者：Bon, Joshua; Robert, Christian P.
  作者单位：Universite PSL; Universite Paris-Dauphine; University of Warwick
• Proposer of the vote of thanks to Grünwald, de Heide, and Koolen and contribution to the Discussion of 'Safe testing' AI翻译
  作者：Wang, Ruodu
  作者单位：University of Waterloo
• Simultaneous false discovery proportion bounds via knockoffs and closed testing AI翻译
  作者：Li, Jinzhou; Maathuis, Marloes H.; Goeman, Jelle J.
  作者单位：Stanford University; Swiss Federal Institutes of Technology Domain; ETH Zurich; Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC
  摘要：We propose new methods to obtain simultaneous false discovery proportion bounds for knockoff-based approaches. We first investigate an approach based on Janson and Su's k-familywise error rate control method and interpolation. We then generalize it by considering a collection of k values, and show that the bound of Katsevich and Ramdas is a special case of this method and can be uniformly improved. Next, we further generalize the method by using closed testing with a multi-weighted-sum local t...