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Recent work suggests that some auto-encoder variants do a good job of capturing the local manifold structure of the unknown data generating density. This paper contributes to the mathematical understanding of this phenomenon and helps…

Machine Learning · Computer Science 2012-07-03 Yoshua Bengio , Guillaume Alain , Salah Rifai

This work considers the problem of quickest detection of signals in a coupled system of $N$ sensors, which receive continuous sequential observations from the environment. It is assumed that the signals, which are modeled by general It\^{o}…

Optimization and Control · Mathematics 2016-03-11 Hongzhong Zhang , Olympia Hadjiliadis , Tobias Schäfer , H. Vincent Poor

A new multiscale implementation of non-local means filtering for image denoising is proposed. The proposed algorithm also introduces a modification of similarity measure for patch comparison. The standard Euclidean norm is replaced by…

Computer Vision and Pattern Recognition · Computer Science 2013-04-04 Zahid Hussain Shamsi , Dai-Gyoung Kim

An algorithm based on the interior-point methodology for solving continuous nonlinearly constrained optimization problems is proposed, analyzed, and tested. The distinguishing feature of the algorithm is that it presumes that only noisy…

Optimization and Control · Mathematics 2025-02-18 Frank E. Curtis , Shima Dezfulian , Andreas Waechter

We consider a $d$-dimensional continuous martingale $X(t)$ with quadratic variation matrix $\langle X\rangle_t=\int_0^t \Sigma(s)\,ds$ and develop tests for the rank of its spot covariance matrix $\Sigma(t)$, $t\in[0,1]$. The process $X$ is…

Statistics Theory · Mathematics 2026-01-14 Markus Reiß , Lars Winkelmann

We propose a high-dimensional white noise test that captures serial correlations within and across component series without specifying an alternative model. The test statistic is a U-statistic based on sample autocovariances. Under the…

Methodology · Statistics 2026-05-07 Yuanya Xu

To improve the off-sample generalization of classical procedures minimizing the empirical risk under potentially heavy-tailed data, new robust learning algorithms have been proposed in recent years, with generalized median-of-means…

Machine Learning · Statistics 2018-10-16 Matthew J. Holland

We adapt the smooth tests of goodness of fit developed by Rayner and Best to the study of the non-Gaussianity of interferometric observations of the cosmic microwave background (CMB). The interferometric measurements (visibilities) are…

A new bivariate partial sum process for locally stationary time series is introduced and its weak convergence to a Brownian sheet is established. This construction enables the development of a novel self-normalized CUSUM test statistic for…

Statistics Theory · Mathematics 2026-04-15 Florian Heinrichs

We suggest generalized robustness for quantifying nonlocality and derive its equivalence to the maximum violation ratio of Bell inequalities defined as vectors with non-negative elements. We investigate its properties by comparing it with…

Quantum Physics · Physics 2025-04-29 Kyunghyun Baek , Junghee Ryu , Jinhyoung Lee

We assume a second-order source separation model where the observed multivariate time series is a linear mixture of latent, temporally uncorrelated time series with some components pure white noise. To avoid the modelling of noise, we…

Methodology · Statistics 2019-05-07 Markus Matilainen , Klaus Nordhausen , Joni Virta

This paper proposes a new algorithm for linear system identification from noisy measurements. The proposed algorithm balances a data fidelity term with a norm induced by the set of single pole filters. We pose a convex optimization problem…

Optimization and Control · Mathematics 2012-04-04 Parikshit Shah , Badri Narayan Bhaskar , Gongguo Tang , Benjamin Recht

Given a quantum system $S$ entangled with another system $I$, the entanglement testing problem arises, prompting the identification of the system $S$ within a set of $m \ge 2$ identical systems. This scenario serves as a model for the…

Quantum Physics · Physics 2023-12-27 Pengcheng Liao , Quntao Zhuang

The assumption of separability is a simplifying and very popular assumption in the analysis of spatio-temporal or hypersurface data structures. It is often made in situations where the covariance structure cannot be easily estimated, for…

Methodology · Statistics 2019-01-03 Pramita Bagchi , Holger Dette

In this paper, we derive a simple method for separating topological noise from topological features using a novel measure for comparing persistence barcodes called persistent entropy.

Information Theory · Computer Science 2016-05-11 Nieves Atienza , Rocio Gonzalez-Diaz , Matteo Rucco

The classic integrated conditional moment test is a promising method for testing regression model misspecification. However, it severely suffers from the curse of dimensionality. To extend it to handle the testing problem for parametric…

Statistics Theory · Mathematics 2020-05-26 Falong Tan , Lixing Zhu

The detection of periodic signals in irregularly-sampled time series is a problem commonly encountered in astronomy. Traditional tools used for periodic searches, such as the periodogram, have poorly defined statistical properties under…

Instrumentation and Methods for Astrophysics · Physics 2025-01-13 A. Gúrpide , M. Middleton

This article is concerned with decentralized sequential testing of a normal mean $\mu$ with two-sided alternatives. It is assumed that in a single-sensor network system with limited local memory, i.i.d. normal raw observations are observed…

Statistics Theory · Mathematics 2009-01-12 Yan Wang , Yajun Mei

Recently, global pulsar timing arrays have released results from searching for a nano-Hertz gravitational wave background signal. Although there has not been any definite evidence of the presence of such a signal in residuals of pulsar…

General Relativity and Quantum Cosmology · Physics 2022-10-12 A. Samajdar , G. Shaifullah , A. Sesana , J. Antoniadis , M. Burgay , D. J. Champion , S. Chen , M. Kramer , J. W. McKee , M. B. Mickaliger , E. Van der Wateren

We demonstrate how noise can be turned into an advantage for optical sensing using a nonlinear cavity. The cavity is driven by a continuous wave laser into the regime of optical bistability. Due to the influence of fluctuations, the cavity…

Optics · Physics 2020-02-19 Said R. K. Rodriguez
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