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We investigate the properties of a sequential Monte Carlo method where the particle weight that appears in the algorithm is estimated by a positive, unbiased estimator. We present broadly-applicable convergence results, including a central…

Methodology · Statistics 2022-08-26 Paul B. Rohrbach , Robert L. Jack

Random walk sampling methods have been widely used in graph sampling in recent years, while it has bias towards higher degree nodes in the sample. To overcome this deficiency, classical methods such as MHRW design weighted walking by…

Methodology · Statistics 2022-09-27 Xiao Qi

This paper develops an algorithmic approach for obtaining estimates of the weight enumerators of Reed-Muller (RM) codes. Our algorithm is based on a technique for estimating the partition functions of spin systems, which in turn employs a…

Information Theory · Computer Science 2024-03-12 Shreyas Jain , V. Arvind Rameshwar , Navin Kashyap

This article overviews how gradient flows, and discretizations thereof, are useful to design and analyze optimization and sampling algorithms. The interplay between optimization, sampling, and gradient flows is an active research area; our…

Computation · Statistics 2023-02-23 N. Garcia Trillos , B. Hosseini , D. Sanz-Alonso

We propose extensions and improvements of the statistical analysis of distributed multipoles (SADM) algorithm put forth by Chipot et al. in [6] for the derivation of distributed atomic multipoles from the quantum-mechanical electrostatic…

Numerical Analysis · Mathematics 2010-07-28 Nicolas Champagnat , Christophe Chipot , Erwan Faou

This thesis presents Regenerative Rejection Sampling (RRS), a novel approximate sampling algorithm inspired by classical Rejection Sampling and Markov Chain Monte Carlo methods. The method constructs a continuous-time regenerative process…

Computation · Statistics 2026-04-01 Tommaso Bozzi

Recovery of arbitrarily positioned samples that are missing in sparse signals recently attracted significant research interest. Sparse signals with heavily corrupted arbitrary positioned samples could be analyzed in the same way as…

Information Theory · Computer Science 2013-09-24 Ljubisa Stankovic , Milos Dakovic , Stefan Vujovic

We develop Monte Carlo methods for sampling random states and corresponding bit strings in qubit systems. To this end, we derive exact probability density functions that yield the Porter-Thomas distribution in the limit of large systems. We…

Quantum Physics · Physics 2025-09-05 Andreas Raab

We provide a perfect sampling algorithm for the hard-sphere model on subsets of $\mathbb{R}^d$ with expected running time linear in the volume under the assumption of strong spatial mixing. A large number of perfect and approximate sampling…

Data Structures and Algorithms · Computer Science 2024-08-22 Konrad Anand , Andreas Göbel , Marcus Pappik , Will Perkins

In this letter, we propose a sparsity promoting feedback acquisition and reconstruction scheme for sensing, encoding and subsequent reconstruction of spectrally sparse signals. In the proposed scheme, the spectral components are estimated…

Information Theory · Computer Science 2017-11-28 Mahdi Boloursaz Mashhadi , Saeed Gazor , Nazanin Rahnavard , Farokh Marvasti

Subsampling of received wireless signals is important for relaxing hardware requirements as well as the computational cost of signal processing algorithms that rely on the output samples. We propose a subsampling technique to facilitate the…

Signal Processing · Electrical Eng. & Systems 2020-05-12 Sharan Ramjee , Shengtai Ju , Diyu Yang , Xiaoyu Liu , Aly El Gamal , Yonina C. Eldar

We describe a very simple method for `consistent sampling' that allows for sampling with replacement. The method extends previous approaches to consistent sampling, which assign a pseudorandom real number to each element, and sample those…

Data Structures and Algorithms · Computer Science 2018-08-31 Ronald L. Rivest

We consider the problem of approximating the set of eigenvalues of the covariance matrix of a multivariate distribution (equivalently, the problem of approximating the "population spectrum"), given access to samples drawn from the…

Machine Learning · Computer Science 2017-07-18 Weihao Kong , Gregory Valiant

Compressive Sensing, as an emerging technique in signal processing is reviewed in this paper together with its common applications. As an alternative to the traditional signal sampling, Compressive Sensing allows a new acquisition strategy…

Information Theory · Computer Science 2017-05-16 Andjela Draganic , Irena Orovic , Srdjan Stankovic

Rejection sampling methods have recently been proposed to improve the performance of discriminator-based generative models. However, these methods are only optimal under an unlimited sampling budget, and are usually applied to a generator…

Machine Learning · Computer Science 2024-03-04 Alexandre Verine , Muni Sreenivas Pydi , Benjamin Negrevergne , Yann Chevaleyre

The limited availability of spectrum resources has been growing into a critical problem in wireless communications, remote sensing, and electronic surveillance, etc. To address the high-speed sampling bottleneck of wideband spectrum…

Signal Processing · Electrical Eng. & Systems 2023-08-15 Kaili Jiang , Dechang Wang , Kailun Tian , Hancong Feng , Yuxin Zhao , Sen Cao , Jian Gao , Xuying Zhang , Yanfei Li , Junyu Yuan , Ying Xiong , Bin Tang

Space filling designs are central to studying complex systems in various areas of science. They are used for obtaining an overall understanding of the behaviour of the response over the input space, model construction and uncertainty…

Methodology · Statistics 2016-08-10 Shirin Golchi , Jason L. Loeppky

We study the problem of recovering the phase from magnitude measurements; specifically, we wish to reconstruct a complex-valued signal x of C^n about which we have phaseless samples of the form y_r = |< a_r,x >|^2, r = 1,2,...,m (knowledge…

Information Theory · Computer Science 2016-11-17 Emmanuel Candes , Xiaodong Li , Mahdi Soltanolkotabi

We proposed and experimentally demonstrated a new hybrid code structure based on the overlapping of two light sources to produce the effect of multi-voltage amplitudes. And we also proposed an efficient polarity reversal threshold (RRT)…

Image and Video Processing · Electrical Eng. & Systems 2022-01-19 Zihao Zhou , Maolin Li , Weipeng Guan

The direct sampling method proposed by Walker et al. (JCGS 2011) can generate draws from weighted distributions possibly having intractable normalizing constants. The method may be of interest as a useful tool in situations which require…

Computation · Statistics 2024-01-19 Andrew M. Raim
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