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作者：Kamath, Gautam; Mouzakis, Argyris; Regehr, Matthew; Singhal, Vikrant; Steinke, Thomas; Ullman, Jonathan
作者单位：University of Waterloo; Alphabet Inc.; DeepMind; Northeastern University
摘要：Differential privacy (DP) is a rigorous notion of data privacy, used for private statistics. The canonical algorithm for differentially private mean estimation is to first clip the samples to a bounded range and then add noise to their empirical mean. Clipping controls the sensitivity and, hence, the variance of the noise that we add for privacy. But clipping also introduces statistical bias. This tradeoff is inherent: we prove that no algorithm can simultaneously have low bias, low error, and...
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作者：Zhang, Yangfan; Wang, Runmin; Shao, Xiaofeng
作者单位：Texas A&M University System; Texas A&M University College Station; University of Illinois System; University of Illinois Urbana-Champaign
摘要：In this article, we propose a class of L-q -norm based U-statistics for a family of global testing problems related to high-dimensional data. This includes testing of mean vector and its spatial sign, simultaneous testing of linear model coefficients, and testing of component-wise independence for high-dimensional observations, among others. Under the null hypothesis, we derive asymptotic normality and independence between L-q -norm based U-statistics for several qs under mild moment and cumul...
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作者：Nguyen, Hien D.
作者单位：La Trobe University
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作者：Yuan, Yubai; Zhang, Yijiao; Shahbaba, Babak; Fortin, Norbert; Cooper, Keiland; Nie, Qing; Qu, Annie
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Fudan University; University of California System; University of California Irvine; University of California System; University of California Irvine; University of California System; University of California Irvine; University of California System; University of California Santa Barbara
摘要：Detecting dynamic patterns shared across heterogeneous datasets is a critical yet challenging task in many scientific domains, particularly within the biomedical sciences. Systematic heterogeneity inherent in diverse data sources can significantly hinder the effectiveness of existing machine learning methods in uncovering shared underlying dynamics. Additionally, practical and technical constraints in real-world experimental designs often limit data collection to only a small number of subject...
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作者：Sun, Dayu; Sun, Zhuowei; Zhao, Xingqiu; Cao, Hongyuan
作者单位：Indiana University System; Indiana University Bloomington; Jilin University; Dalian Medical University; Hong Kong Polytechnic University; State University System of Florida; Florida State University
摘要：We study the transformed hazards model with time-dependent covariates observed intermittently for the censored outcome. Existing work assumes the availability of the whole trajectory of the time-dependent covariates, which is unrealistic. We propose combining kernel-weighted log-likelihood and sieve maximum log-likelihood estimation to conduct statistical inference. The method is robust and easy to implement. We establish the asymptotic properties of the proposed estimator and contribute to a ...
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作者：Lyu, Zhongyuan; Chen, Ling; Gu, Yuqi
作者单位：Columbia University; Columbia University
摘要：The latent class model is a widely used mixture model for multivariate discrete data. Besides the existence of qualitatively heterogeneous latent classes, real data often exhibit additional quantitative heterogeneity nested within each latent class. The modern latent class analysis also faces extra challenges, including the high-dimensionality, sparsity, and heteroscedastic noise inherent in discrete data. Motivated by these phenomena, we introduce the Degree-heterogeneous Latent Class Model a...
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作者：Duan, Yunshan; Guo, Shuai; Wang, Wenyi; Mueller, Peter
作者单位：University of Texas System; University of Texas Austin; University of Texas System; UTMD Anderson Cancer Center
摘要：Comparison of transcriptomic data across different conditions is of interest in many biomedical studies. In this article, we consider comparative immune cell profiling for early-onset (EO) versus late-onset (LO) colorectal cancer (CRC). EOCRC, diagnosed between ages 18-45, is a rising public health concern that needs to be urgently addressed. However, its etiology remains poorly understood. We work toward filling this gap by identifying homogeneous T cell sub-populations that show significantl...
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作者：Gu, Yu; Zeng, Donglin; Lin, D. Y.
作者单位：University of Hong Kong; University of Michigan System; University of Michigan; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
摘要：In studies of chronic diseases, the health status of a subject can often be characterized by a finite number of transient disease states and an absorbing state, such as death. The times of transitions among the transient states are ascertained through periodic examinations and thus interval-censored. The time of reaching the absorbing state is known or right-censored, with the transient state at the previous instant being unobserved. In this article, we provide a general framework for analyzin...
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作者：Kuusela, Mikael
作者单位：Carnegie Mellon University
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作者：Ai, Mingyao; Dette, Holger; Liu, Zhengfu; Yu, Jun
作者单位：Peking University; Peking University; Ruhr University Bochum; Beijing Institute of Technology
摘要：An optimal design is usually model-dependent and is sub-optimal if the postulated model is not correctly specified. Furthermore, it is far from ideal even if it is efficient for model selection but has a poor performance for estimating parameters in the selected model. In practice, it is common that a researcher has a list of candidate models at hand and a design has to be found that is efficient for both model discrimination and parameter estimation in the (unknown) true model. In this articl...
