Zobrazeno 1 - 10
of 158
pro vyhledávání: '"Baron, Dror"'
Quantum error mitigation is an important technique to reduce the impact of noise in quantum computers. With more and more qubits being supported on quantum computers, there are two emerging fundamental challenges. First, the number of shots required
Externí odkaz:
http://arxiv.org/abs/2402.11830
Group testing can help maintain a widespread testing program using fewer resources amid a pandemic. In a group testing setup, we are given n samples, one per individual. Each individual is either infected or uninfected. These samples are arranged int
Externí odkaz:
http://arxiv.org/abs/2211.03731
We investigate mismatched estimation in the context of the distance geometry problem (DGP). In the DGP, for a set of points, we are given noisy measurements of pairwise distances between the points, and our objective is to determine the geometric loc
Externí odkaz:
http://arxiv.org/abs/2206.05727
Federated learning has been proposed as a privacy-preserving machine learning framework that enables multiple clients to collaborate without sharing raw data. However, client privacy protection is not guaranteed by design in this framework. Prior wor
Externí odkaz:
http://arxiv.org/abs/2206.04055
Federated learning (FL) is a privacy-preserving paradigm where multiple participants jointly solve a machine learning problem without sharing raw data. Unlike traditional distributed learning, a unique characteristic of FL is statistical heterogeneit
Externí odkaz:
http://arxiv.org/abs/2110.03681
Group testing can help maintain a widespread testing program using fewer resources amid a pandemic. In group testing, we are given $n$ samples, one per individual. These samples are arranged into $m < n$ pooled samples, where each pool is obtained by
Externí odkaz:
http://arxiv.org/abs/2106.02699
Publikováno v:
ICASSP 2021, Toronto, ON, Canada, 2021, pp. 8168-8172
Group testing can save testing resources in the context of the ongoing COVID-19 pandemic. In group testing, we are given $n$ samples, one per individual, and arrange them into $m < n$ pooled samples, where each pool is obtained by mixing a subset of
Externí odkaz:
http://arxiv.org/abs/2011.14186
A common sparse linear regression formulation is the l1 regularized least squares, which is also known as least absolute shrinkage and selection operator (LASSO). Approximate message passing (AMP) has been proved to asymptotically achieve the LASSO s
Externí odkaz:
http://arxiv.org/abs/2007.09299
This work considers millimeter-wave channel estimation in a setting where parameters of the underlying mmWave channels are varying dynamically over time and there is a single drifting path. In this setting, channel estimates at time block $k$ can be
Externí odkaz:
http://arxiv.org/abs/2005.02244
Fast testing can help mitigate the coronavirus disease 2019 (COVID-19) pandemic. Despite their accuracy for single sample analysis, infectious diseases diagnostic tools, like RT-PCR, require substantial resources to test large populations. We develop
Externí odkaz:
http://arxiv.org/abs/2004.02689