Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Dror Baron"'
Publikováno v:
IEEE Transactions on Information Theory. 69:3989-4013
A common goal in many research areas is to reconstruct an unknown signal x from noisy linear measurements. Approximate message passing (AMP) is a class of low-complexity algorithms that can be used for efficiently solving such high-dimensional regres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12b2634429999d6eb195e98a7dd87cfa
https://doi.org/10.1109/tit.2022.3220046
https://doi.org/10.1109/tit.2022.3220046
Autor:
Priyank Kashyap, Archit Gajjar, Yongjin Choi, Chau-Wai Wong, Dror Baron, Tianfu Wu, Chris Cheng, Paul Franzon
Publikováno v:
Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b50f29d2b3bc34f1e8df0bc5d1505af
https://doi.org/10.1145/3551901.3556480
https://doi.org/10.1145/3551901.3556480
Autor:
Priyank Kashyap, Yongjin Choi, Sumon Dey, Dror Baron, Chau-Wai Wong, Tianfu Wu, Chris Cheng, Paul D. Franzon
Publikováno v:
2022 IEEE 72nd Electronic Components and Technology Conference (ECTC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b64fd748569f0e892d148fcfe64af2bd
https://doi.org/10.1109/ectc51906.2022.00307
https://doi.org/10.1109/ectc51906.2022.00307
Publikováno v:
2021 IEEE 30th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::47d8254cedeac317fcc881bef22ae663
https://doi.org/10.1109/epeps51341.2021.9609124
https://doi.org/10.1109/epeps51341.2021.9609124
Publikováno v:
ISIT
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83a9e4e067faee37386406bbb63f29b0
http://arxiv.org/abs/2007.09299
http://arxiv.org/abs/2007.09299
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5445b9ce8e1fc7dd2f8481b0d5938917
https://doi.org/10.1101/2020.04.06.20055384
https://doi.org/10.1101/2020.04.06.20055384
Publikováno v:
ICASSP
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16c961034f4c25f2b6cec8ae8400fb06
Publikováno v:
Allerton
Nonlinear function estimation is core to modern machine learning applications. In this paper, to perform nonlinear function estimation, we reduce a nonlinear inverse problem to a linear one using a polynomial kernel expansion. These kernels increase
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::868e788f3d4bb698479414971fddbc54
https://doi.org/10.1109/allerton.2019.8919961
https://doi.org/10.1109/allerton.2019.8919961
Publikováno v:
GLOBECOM
In this paper, we tackle channel estimation in millimeter-wave hybrid multiple-input multiple- output systems by considering off-grid effects. In particular, we assume that spatial parameters can take any value in the angular domain, and need not fal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6007c0099c6a3bd54937384292a3c72e
http://arxiv.org/abs/1907.04427
http://arxiv.org/abs/1907.04427
Publikováno v:
ISIT
A common goal in many research areas is to reconstruct an unknown signal x from noisy linear measurements. Approximate message passing (AMP) is a class of low-complexity algorithms for efficiently solving such high-dimensional regression tasks. Often
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5100768027663b6ea3b7b3f02a61658d
https://doi.org/10.1109/isit.2019.8849735
https://doi.org/10.1109/isit.2019.8849735