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Optimal transport (OT) is a powerful geometric tool for comparing two distributions and has been employed in various machine learning applications. In this work, we propose a novel OT formulation that takes feature correlations into account…

Machine Learning · Computer Science 2021-10-08 Pratik Jawanpuria , N T V Satyadev , Bamdev Mishra

Signal detection in colored noise with an unknown covariance matrix has a myriad of applications in diverse scientific/engineering fields. The test statistic is the largest generalized eigenvalue (l.g.e.) of the whitened sample covariance…

Information Theory · Computer Science 2019-02-08 Lahiru D. Chamain , Prathapasinghe Dharmawansa , Saman Atapattu , Chintha Tellambura

In precision frequency transfer systems, stringent requirements are imposed on the phase stability of transmitted signals. Throughout the transmission process, the inherent challenges of long-haul signal propagation inevitably introduce…

Optics · Physics 2025-12-24 Xuan Yang. Junhui Li , Bin Luo , Ziyang Chen , Hong guo

We propose a novel motion estimation/compensation (ME/MC) method for wavelet-based (in-band) motion compensated temporal filtering (MCTF), with application to low-bitrate video coding. Unlike the conventional in-band MCTF algorithms, which…

Computer Vision and Pattern Recognition · Computer Science 2017-05-17 Vildan Atalay Aydin , Hassan Foroosh

Visual inspection of industrial products is used to determine the control quality for these products. This paper deals with the problem of visual inspection of ceramic tiles industry using Wavelet Transform. The third level the coefficients…

Other Computer Science · Computer Science 2010-03-10 Samir Elmougy , Ibrahim El-Henawy , Ahmed El-Azab

Density Functional Theory (DFT) is a pivotal method within quantum chemistry and materials science, with its core involving the construction and solution of the Kohn-Sham Hamiltonian. Despite its importance, the application of DFT is…

Randomized smoothing is a well-established method for achieving certified robustness against l2-adversarial perturbations. By incorporating a denoiser before the base classifier, pretrained classifiers can be seamlessly integrated into…

Machine Learning · Computer Science 2025-09-16 Ali Hedayatnia , Mostafa Tavassolipour , Babak Nadjar Araabi , Abdol-Hossein Vahabie

Multivariate regression techniques are commonly applied to explore the associations between large numbers of outcomes and predictors. In real-world applications, the outcomes are often of mixed types, including continuous measurements,…

Methodology · Statistics 2020-10-19 Aditya Mishra , Dipak K. Dey , Yong Chen , Kun Chen

We consider the convolution model where i.i.d. random variables $X_i$ having unknown density $f$ are observed with additive i.i.d. noise, independent of the $X$'s. We assume that the density $f$ belongs to either a Sobolev class or a class…

Statistics Theory · Mathematics 2009-09-29 Cristina Butucea

A consistent goodness-of-fit test for distributional regression is introduced. The test statistic is based on a process that traces the difference between a nonparametric and a semi-parametric estimate of the marginal distribution function…

Methodology · Statistics 2025-10-10 Gitte Kremling , Gerhard Dikta

In many statistical modeling frameworks, goodness-of-fit tests are typically administered to the estimated residuals. In the time series setting, whiteness of the residuals is assessed using the sample autocorrelation function. For many…

Statistics Theory · Mathematics 2019-03-05 Phyllis Wan , Richard A. Davis

Simulation-based inference methods that feature correct conditional coverage of confidence sets based on observations that have been compressed to a scalar test statistic require accurate modeling of either the p-value function or the…

Machine Learning · Statistics 2025-08-18 Ali Al Kadhim , Harrison B. Prosper

Despite their successful application to a variety of tasks, neural networks remain limited, like other machine learning methods, by their sensitivity to shifts in the data: their performance can be severely impacted by differences in…

We have presented a new and alternative algorithm for noise reduction using the methods of discrete wavelet transform and numerical differentiation of the data. In our method the threshold for reducing noise comes out automatically. The…

We present a theoretical model that fully supports the recently disclosed generalized droop formula (GDF) for calculating the signal-to-noise ratio (SNR) of constant-output power (COP) amplified dispersion-uncompensated coherent links…

Signal Processing · Electrical Eng. & Systems 2019-08-30 Alberto Bononi , Jean-Christophe Antona , Matteo Lonardi , Alexis Carbo-Méseguer , Paolo Serena

We propose a Bayesian method to detect change points for functional data. We extract the features of a sequence of functional data by the discrete wavelet transform (DWT), and treat each sequence of feature independently. We believe there…

Methodology · Statistics 2018-08-06 Xiuqi Li , Subhashis Ghosal

Millimeter-wave multi-input multi-output (mm-Wave MIMO) systems are one of the candidate schemes for 5G wireless standardization efforts. In this context, the main contributions of this article are three-fold. 1) We describe parallel sets…

A natural (yet unconventional) test for goodness-of-fit measures the discrepancy between the model and empirical distributions via their Euclidean distance (or, equivalently, via its square). The present paper characterizes the statistical…

Computation · Statistics 2012-06-28 William Perkins , Gary Simon , Mark Tygert

Multiple speckle diffusing wave spectroscopy (MSDWS) can be applied to measure spatially heterogeneous mechanical behavior in soft solids, with high sensitivity to deformation and both spatial and temporal resolution. In this paper, we…

Soft Condensed Matter · Physics 2022-11-23 Jianzhu Ju , Luca Cipelletti , Stephan Zoellner , Tetsuharu Narita , Costantino Creton

Distributed multi-target tracking (DMTT) is addressed for sensors having different fields of view (FoVs). The proposed approach is based on the idea of fusing the posterior Probability Hypotheses Densities (PHDs) generated by the sensors on…

Systems and Control · Computer Science 2019-08-28 Guchong Li , Giorgio Battistelli , Wei Yi , Lingjiang Kong