549期

最新文章

• Doubly-Valid/Doubly-Sharp Sensitivity Analysis for Causal Inference with Unmeasured Confounding AI翻译
  作者：Dorn, Jacob; Guo, Kevin; Kallus, Nathan
  作者单位：Princeton University; Stanford University; Cornell University
  摘要：We consider the problem of constructing bounds on the average treatment effect (ATE) when unmeasured confounders exist but have bounded influence. Specifically, we assume that omitted confounders could not change the odds of treatment for any unit by more than a fixed factor. We derive the sharp partial identification bounds implied by this assumption by leveraging distributionally robust optimization, and we propose estimators of these bounds with several novel robustness properties. The firs...
• An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series AI翻译
  作者：Zheng, Yao
  作者单位：University of Connecticut
  摘要：As a special infinite-order vector autoregressive (VAR) model, the vector autoregressive moving average (VARMA) model can capture much richer temporal patterns than the widely used finite-order VAR model. However, its practicality has long been hindered by its non-identifiability, computational intractability, and difficulty of interpretation, especially for high-dimensional time series. This article proposes a novel sparse infinite-order VAR model for high-dimensional time series, which avoid...
• Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection AI翻译
  作者：Ward, Kes; Dilillo, Giuseppe; Eckley, Idris; Fearnhead, Paul
  作者单位：Lancaster University; Istituto Nazionale Astrofisica (INAF); University of Udine; Lancaster University
  摘要：Gamma ray bursts are flashes of light from distant, new-born black holes. CubeSats that monitor high-energy photons across different energy bands are used to detect these bursts. There is a need for computationally efficient algorithms, able to run using the limited computational resource onboard a CubeSats, that can detect when gamma ray bursts occur. Current algorithms are based on monitoring photon counts across a grid of different sizes of time window. We propose a new method, which extend...
• ROC Analysis for Classification and Prediction in Practice AI翻译
  作者：Tec, Mauricio
  作者单位：Harvard University
• Data Fission and Sampling Designs: A Discussion AI翻译
  作者：Chan, Kwun Chuen Gary; Prentice, Ross L.; Yuan, Zhenman
  作者单位：University of Washington; University of Washington Seattle; Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle
• Comment on Data Fission: Splitting a Single Data Point Data Fission for Unsupervised Learning: A Discussion on Post-Clustering Inference and the Challenges of Debiasing AI翻译
  作者：Wang, Changhu; Ge, Xinzhou; Song, Dongyuan; Li, Jingyi Jessica
  作者单位：University of California System; University of California Los Angeles; Oregon State University; University of California System; University of California Los Angeles
• Neural Networks for Geospatial Data AI翻译
  作者：Zhan, Wentao; Datta, Abhirup
  作者单位：Johns Hopkins University
  摘要：Analysis of geospatial data has traditionally been model-based, with a mean model, customarily specified as a linear regression on the covariates, and a Gaussian process covariance model, encoding the spatial dependence. While nonlinear machine learning algorithms like neural networks are increasingly being used for spatial analysis, current approaches depart from the model-based setup and cannot explicitly incorporate spatial covariance. We propose NN-GLS, embedding neural networks directly w...
• Controlled Discovery and Localization of Signals via Bayesian Linear Programming AI翻译
  作者：Spector, Asher; Janson, Lucas
  作者单位：Stanford University; Harvard University
  摘要：Scientists often must simultaneously localize and discover signals. For instance, in genetic fine-mapping, high correlations between nearby genetic variants make it hard to identify the exact locations of causal variants. So the statistical task is to output as many disjoint regions containing a signal as possible, each as small as possible, while controlling false positives. Similar problems arise, for example, when locating stars in astronomical surveys and in changepoint detection. Common B...
• A Discussion on: Data Fission: Splitting a Single Data Point by Leiner, J., Duan, B., Wasserman, L. and Ramdas, A. AI翻译
  作者：Catalano, Marta; Fasano, Augusto; Giordano, Matteo; Rebaudo, Giovanni
  作者单位：Luiss Guido Carli University; University of Turin
• Probability Modeling and Statistical Inference in Cancer Screening AI翻译
  作者：Cheung, Li C.
  作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics