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This paper presents a survey on some recent advances for the type I error rate control in multiple testing methodology. We consider the problem of controlling the $k$-family-wise error rate (kFWER, probability to make $k$ false discoveries…

Methodology · Statistics 2011-03-15 Etienne Roquain

In this paper we proposed the alternative test to the two independent and normally distributed samples t test based on the cross variance concept. We present the simulation results of the power and the error rate of the special case of the…

Methodology · Statistics 2015-01-27 Rohmatul Fajriyah

The Distributional Random Forest (DRF) is a recently introduced Random Forest algorithm to estimate multivariate conditional distributions. Due to its general estimation procedure, it can be employed to estimate a wide range of targets such…

Statistics Theory · Mathematics 2023-12-20 Jeffrey Näf , Corinne Emmenegger , Peter Bühlmann , Nicolai Meinshausen

Paramagnetic luminescent impurities in solids such as Nitrogen-Vacancy (NV) centers in diamond represent a promising and versatile platform for the development of a wide range of chemical and biological sensors. This goal can be…

Applied Physics · Physics 2021-05-07 Alexei Goun , Herschel Rabitz

The main goal is to develop and, consequently, compare stochastic methods for detection whether a structural change in panel data occurred at some unknown time or not. Panel data of our interest consist of a moderate or relatively large…

Methodology · Statistics 2016-08-22 Barbora Peštová , Michal Pešta

In this paper we consider Sparse Fourier Transform (SFT) algorithms for approximately computing the best $s$-term approximation of the Discrete Fourier Transform (DFT) $\mathbf{\hat{f}} \in \mathbb{C}^N$ of any given input vector…

Numerical Analysis · Mathematics 2017-06-12 Sami Merhi , Ruochuan Zhang , Mark A. Iwen , Andrew Christlieb

Technological advancements have made it possible to deliver mobile health interventions to individuals. A novel framework that has emerged from such advancements is the just-in-time adaptive intervention (JITAI), which aims to suggest the…

Methodology · Statistics 2023-07-10 Jing Xu , Xiaoxi Yan , Caroline Figueroa , Joseph Jay Williams , Bibhas Chakraborty

Training diffusion models on limited datasets poses challenges in terms of limited generation capacity and expressiveness, leading to unsatisfactory results in various downstream tasks utilizing pretrained diffusion models, such as domain…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Jiwan Hur , Jaehyun Choi , Gyojin Han , Dong-Jae Lee , Junmo Kim

This paper presents a novel approach that combines the Deep Ritz Method (DRM) with Fourier feature mapping to solve minimization problems comprised of multi-well, non-convex energy potentials. These problems present computational challenges…

Machine Learning · Computer Science 2025-02-12 Ensela Mema , Ting Wang , Jaroslaw Knap

The presence of interharmonics in power systems can lead to asynchronous sampling, a phenomenon further aggravated by shifts in the fundamental frequency, which significantly degrades the accuracy of power measurements. Under such…

Signal Processing · Electrical Eng. & Systems 2026-01-30 Jian Liu , Wei Zhao , Jianting Zhao , Shisong Li

Image retouching aims to enhance the visual quality of photos. Considering the different aesthetic preferences of users, the target of retouching is subjective. However, current retouching methods mostly adopt deterministic models, which…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Zheng-Peng Duan , Jiawei zhang , Zheng Lin , Xin Jin , Dongqing Zou , Chunle Guo , Chongyi Li

Despite their recent success, deep neural networks continue to perform poorly when they encounter distribution shifts at test time. Many recently proposed approaches try to counter this by aligning the model to the new distribution prior to…

Computer Vision and Pattern Recognition · Computer Science 2022-09-26 Samarth Sinha , Peter Gehler , Francesco Locatello , Bernt Schiele

The contamination detection problem aims to determine whether a set of observations has been contaminated, i.e. whether it contains points drawn from a distribution different from the reference distribution. Here, we consider a supervised…

Methodology · Statistics 2024-04-10 Solenne Gaucher , Gilles Blanchard , Frédéric Chazal

Large-scale multiple testing with correlated and heavy-tailed data arises in a wide range of research areas from genomics, medical imaging to finance. Conventional methods for estimating the false discovery proportion (FDP) often ignore the…

Methodology · Statistics 2018-09-19 Jianqing Fan , Yuan Ke , Qiang Sun , Wen-Xin Zhou

Development generating diffraction-related valuable expressions and formulas capable of initiating new era for diffraction and for scientific domains that use it provided. The main expression, among these, gives diffracted intensity as…

Materials Science · Physics 2021-03-16 Noureddine Hadji

Currently, statistical tests for random number generators (RNGs) are widely used in practice, and some of them are even included in information security standards. But despite the popularity of RNGs, consistent tests are known only for…

Statistics Theory · Mathematics 2021-05-17 Boris Ryabko

The Discrete Fourier Transform (DFT) is a fundamental computational primitive, and the fastest known algorithm for computing the DFT is the FFT (Fast Fourier Transform) algorithm. One remarkable feature of FFT is the fact that its runtime…

Data Structures and Algorithms · Computer Science 2019-02-28 Michael Kapralov , Ameya Velingker , Amir Zandieh

Recent advances have shown that statistical tests for the rank of cross-covariance matrices play an important role in causal discovery. These rank tests include partial correlation tests as special cases and provide further graphical…

Machine Learning · Computer Science 2025-06-13 Xinshuai Dong , Ignavier Ng , Boyang Sun , Haoyue Dai , Guang-Yuan Hao , Shunxing Fan , Peter Spirtes , Yumou Qiu , Kun Zhang

This paper presents a significant modification to the Random Demodulator (RD) of Tropp et al. for sub-Nyquist sampling of frequency-sparse signals. The modification, termed constrained random demodulator, involves replacing the random…

Information Theory · Computer Science 2018-03-06 Andrew Harms , Waheed U. Bajwa , Robert Calderbank

In the present paper new light is shed on the non-central extensions of the Dirichlet distribution. Due to several probabilistic and inferential properties and to the easiness of parameter interpretation, the Dirichlet distribution proves…

Statistics Theory · Mathematics 2021-08-02 Carlo Orsi
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