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A novel algorithm for the recovery of low-rank matrices acquired via compressive linear measurements is proposed and analyzed. The algorithm, a variation on the iterative hard thresholding algorithm for low-rank recovery, is designed to…

Numerical Analysis · Mathematics 2018-10-30 Simon Foucart , Srinivas Subramanian

Pinching-antenna (PA) has recently attracted considerable research attention in wireless systems, realized by attaching small dielectric particles along a waveguide. Building upon which, the segmented waveguide-enabled pinching-antenna…

Signal Processing · Electrical Eng. & Systems 2026-04-02 Yue Geng , Tee Hiang Cheng , Kah Chan Teh , Zhiguo Ding

Because of the widespread existence of noise and data corruption, recovering the true regression parameters with a certain proportion of corrupted response variables is an essential task. Methods to overcome this problem often involve…

Machine Learning · Computer Science 2023-01-10 Zheyi Fan , Zhaohui Li , Jingyan Wang , Dennis K. J. Lin , Xiao Xiong , Qingpei Hu

An efficient Bayesian inference method for problems that can be mapped onto dense graphs is presented. The approach is based on message passing where messages are averaged over a large number of replicated variable systems exposed to the…

Disordered Systems and Neural Networks · Physics 2009-11-13 Juan P Neirotti , David Saad

This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is dedicatedly deployed to assist an access point (AP) to sense a target at its NLoS region. It is assumed that…

Signal Processing · Electrical Eng. & Systems 2023-07-05 Xianxin Song , Jie Xu , Fan Liu , Tony Xiao Han , Yonina C. Eldar

Knowledge about the location of licensed primary-users (PU) could enable several key features in cognitive radio (CR) networks including improved spatio-temporal sensing, intelligent location-aware routing, as well as aiding spectrum policy…

Performance · Computer Science 2016-11-18 Jun Wang , Jianshu Chen , Danijela Cabric

We propose a new analysis framework for clustering $M$ items into an unknown number of $K$ distinct groups using noisy and actively collected responses. At each time step, an agent is allowed to query pairs of items and observe bandit…

Machine Learning · Computer Science 2026-02-06 Rachel S. Y. Teo , P. N. Karthik , Ramya Korlakai Vinayak , Vincent Y. F. Tan

Assessing the quality of parameter estimates for models describing the motion of single molecules in cellular environments is an important problem in fluorescence microscopy. We consider the fundamental data model, where molecules emit…

Quantitative Methods · Quantitative Biology 2021-09-15 A. Marie d'Avigneau , S. S. Singh , R. J. Ober

We study the problem of solving strongly convex and smooth unconstrained optimization problems using stochastic first-order algorithms. We devise a novel algorithm, referred to as Recursive One-Over-T SGD (ROOT-SGD), based on an easily…

Optimization and Control · Mathematics 2024-09-19 Chris Junchi Li , Wenlong Mou , Martin J. Wainwright , Michael I. Jordan

This paper provides a unified treatment to the recovery of structured signals living in a star-shaped set from general quantized measurements $\mathcal{Q}(\mathbf{A}\mathbf{x}-\mathbf{\tau})$, where $\mathbf{A}$ is a sensing matrix,…

Information Theory · Computer Science 2025-04-29 Junren Chen , Ming Yuan

Compressed sensing is a technique for recovering a high-dimensional signal from lower-dimensional data, whose components represent partial information about the signal, utilizing prior knowledge on the sparsity of the signal. For further…

Information Theory · Computer Science 2014-02-18 Yingying Xu , Yoshiyuki Kabashima

Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present a theoretical analysis of the iterative hard thresholding…

Information Theory · Computer Science 2008-05-06 Thomas Blumensath , Mike E. Davies

Compressed sensing typically deals with the estimation of a system input from its noise-corrupted linear measurements, where the number of measurements is smaller than the number of input components. The performance of the estimation…

Information Theory · Computer Science 2016-11-17 Jin Tan , Danielle Carmon , Dror Baron

One-bit compressive sensing is concerned with the accurate recovery of an underlying sparse signal of interest from its one-bit noisy measurements. The conventional signal recovery approaches for this problem are mainly developed based on…

Signal Processing · Electrical Eng. & Systems 2022-09-23 Yiming Zeng , Shahin Khobahi , Mojtaba Soltanalian

This paper proposes block-level precoder (BLP) designs for a multi-input single-output (MISO) system that performs joint sensing and communication across multiple cells and users. The Cramer-Rao-Bound for estimating a target's azimuth angle…

Information Theory · Computer Science 2024-02-29 Nithin Babu , Christos Masouros

In this paper, we study the problem of mean estimation under 1-bit communication constraints. We propose a novel adaptive mean estimator based solely on randomized threshold queries, where each 1-bit outcome indicates whether a given sample…

Machine Learning · Statistics 2026-05-25 Ivan Lau , Jonathan Scarlett

A Cramer-Rao bound (CRB) for semi-blind channel estimators in redundant block transmission systems is derived. The derived CRB is valid for any system adopting a full-rank linear redundant precoder, including the popular cyclic-prefixed…

Information Theory · Computer Science 2012-09-20 Yen-Huan Li , Borching Su , Ping-Cheng Yeh

We consider the problem of compressed sensing and of (real-valued) phase retrieval with random measurement matrix. We derive sharp asymptotics for the information-theoretically optimal performance and for the best known polynomial algorithm…

Statistics Theory · Mathematics 2020-09-04 Benjamin Aubin , Bruno Loureiro , Antoine Baker , Florent Krzakala , Lenka Zdeborová

Integer factorization remains a significant challenge for classical computers and is fundamental to the security of RSA encryption. Adiabatic quantum algorithms present a promising solution, yet their practical implementation is limited by…

Quantum Physics · Physics 2025-05-23 Tianlai Yang , Mo Xiong , Ming Xue , Xinwei Li , Jinbin Li

Millimeter-wave (mmWave) communication is a promising solution for achieving high data rate and low latency in 5G wireless cellular networks. Since directional beamforming and antenna arrays are exploited in the mmWave networks, accurate…

Information Theory · Computer Science 2020-11-26 Jiajun He , Young Jin Chun