Related papers: PUMA: The Positional Update and Matching Algorithm
This work presents cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the…
The Evolutionary Map of the Universe (EMU) is a proposed radio continuum survey of the Southern Hemisphere up to declination +30 deg., with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU will use an automated source…
Approximate computing frameworks configure applications so they can operate at a range of points in an accuracy-performance trade-off space. Prior work has introduced many frameworks to create approximate programs. As approximation…
We present a new particle tracking software algorithm designed to accurately track the motion of low-contrast particles against a background with large variations in light levels. The method is based on a polynomial fit of the intensity…
This paper introduces posterior mean matching (PMM), a new method for generative modeling that is grounded in Bayesian inference. PMM uses conjugate pairs of distributions to model complex data of various modalities like images and text,…
In this paper we address the problems of modeling the acoustic space generated by a full-spectrum sound source and of using the learned model for the localization and separation of multiple sources that simultaneously emit sparse-spectrum…
In this paper we present a new coherence-based performance guarantee for the Orthogonal Matching Pursuit (OMP) algorithm. An upper bound for the probability of correctly identifying the support of a sparse signal with additive white…
Beam prediction is an effective approach to reduce training overhead in massive multiple-input multiple-output (MIMO) systems. However, existing beam prediction models still exhibit limited generalization ability in diverse scenarios, which…
We present an end-to-end simulation and data-processing framework for digital beamforming experiments conducted with four stations of the 21 Centimeter Array (21CMA). Motivated by the need to characterize instrumental systematics, such as…
We participated in track 2 of the VoiceMOS Challenge 2024, which aimed to predict the mean opinion score (MOS) of singing samples. Our submission secured the first place among all participating teams, excluding the official baseline. In…
Particle production from secondary proton-proton collisions, commonly referred to as pile-up, impair the sensitivity of both new physics searches and precision measurements at LHC experiments. We propose a novel algorithm, PUMA, for…
This work presents a new algorithm for empirical risk minimization. The algorithm bridges the gap between first- and second-order methods by computing a search direction that uses a second-order-type update in one subspace, coupled with a…
This paper investigates asynchronous multiple-input multiple-output (MIMO) massive unsourced random access (URA) in an orthogonal frequency division multiplexing (OFDM) system over frequency-selective fading channels, with the presence of…
Conformal prediction has emerged as a popular technique for facilitating valid predictive inference across a spectrum of machine learning models, under minimal assumption of exchangeability. Recently, Hoff (2023) showed that full conformal…
There are many legacy databases, and related stores of information that are maintained by distinct organizations, and there are other organizations that would like to be able to access and use those disparate sources. Among the examples of…
In this work, we address the problem of automating quantum variational machine learning. We develop a multi-locality parallelizable search algorithm, called MUSE, to find the initial points and the sets of parameters that achieve the best…
Foreground removal presents a significant obstacle in both current and forthcoming intensity mapping surveys. While numerous techniques have been developed that show promise in simulated datasets, their efficacy often diminishes when…
The CLEAN algorithm, widely used in radio interferometry for the deconvolution of radio images, performs well only if the raw radio image (dirty image) is, to good approximation, a simple convolution between the instrumental point-spread…
We address the new problem of estimating a piece-wise constant signal with the purpose of detecting its change points and the levels of clusters. Our approach is to model it as a nonparametric penalized least square model selection on a…
Compact Ultramassive Antenna Array (CUMA) is a pioneering paradigm that leverages the flexibility of the Fluid Antenna System (FAS) to enable a simple multiple access scheme for massive connectivity without the need for precoding, power…