Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Luca Baldassarre"'
Autor:
Luca BALDASSARRE
Publikováno v:
Polis: Revista de Stiinte Politice, Vol IV, Iss 4(14), Pp 111-123 (2016)
n this article the author highlights some issues about Adorno’s thought that are fundamental to be acquired in the present age. It focuses on the questions most criticized in the postwar period: cultural industry, managed world, presumed snobbery a
Externí odkaz:
https://doaj.org/article/62e8a8133a2f41cc9c53157e64de5e7c
Publikováno v:
Annals of Actuarial Science. 16:1-5
AI has had many summers and winters. Proponents have overpromised, and there has been hype and disappointment. In recent years, however, we have watched with awe, surprise, and hope at the successes: Better than human capabilities of image-recognitio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83aa4f3c34966ae5221588eff8d909c3
https://doi.org/10.1017/s1748499521000245
https://doi.org/10.1017/s1748499521000245
Autor:
Catherine Dehollain, Yusuf Leblebici, Cosimo Aprile, Mahsa Shoaran, Franco Maloberti, Luca Baldassarre, Kerim Ture, Gurkan Yilmaz, Volkan Cevher
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers
Implantable systems are nowadays being used to interface the human brain with external devices, in order to understand and potentially treat neurological disorders. The most predominant design constraints are the system’s area and power. In this pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ef904754c06c4314929ca110775ae91
https://doi.org/10.1109/tcsi.2018.2853983
https://doi.org/10.1109/tcsi.2018.2853983
Publikováno v:
IEEE Transactions on Information Theory. 62:6508-6534
Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these models is the recovery of "interpretable" signals throu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d899b6a243a1fa074614d1038842b7d
https://doi.org/10.1109/tit.2016.2602222
https://doi.org/10.1109/tit.2016.2602222
Publikováno v:
IEEE Signal Processing Magazine
Source separation or demixing is the process of extracting multiple components entangled within a signal. Contemporary signal processing presents a host of difficult source separation problems, from interference cancellation to background subtraction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cee87f5b96ed04ad0ea22766f2f05eb
https://doi.org/10.1109/msp.2013.2296605
https://doi.org/10.1109/msp.2013.2296605
Publikováno v:
Machine Learning. 87:259-301
In this paper we study a class of regularized kernel methods for multi-output learning which are based on filtering the spectrum of the kernel matrix. The considered methods include Tikhonov regularization as a special case, as well as interesting al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::390e5678a580a8abf57ea6b6ec2df58f
https://doi.org/10.1007/s10994-012-5282-y
https://doi.org/10.1007/s10994-012-5282-y
Publikováno v:
EUSIPCO
Effectively solving many inverse problems in engineering requires to leverage all possible prior information about the structure of the signal to be estimated. This often leads to tackling constrained optimization problems with mixtures of regularize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3cb1f568630d876b9f5726b9d18b2df
https://doi.org/10.1109/eusipco.2015.7362381
https://doi.org/10.1109/eusipco.2015.7362381
Publikováno v:
Measures of Complexity ISBN: 9783319218519
We give lower bounds on the reconstruction error for PCA , k-means clustering, and various sparse coding methods. It is shown that the two objectives of good data approximation and sparsity of the solution are incompatible if the data distribution is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf8c9f499757aeb1a50282d456173b13
https://doi.org/10.1007/978-3-319-21852-6_24
https://doi.org/10.1007/978-3-319-21852-6_24
Autor:
Jonathan Scarlett, Baran Gozcu, Luca Baldassarre, Volkan Cevher, Yen-Huan Li, Ilija Bogunovic
Publikováno v:
Journal on Selected Topics in Signal Processing
IEEE Journal on Selected Topics in Signal Processing
IEEE Journal on Selected Topics in Signal Processing
The problem of recovering a structured signal $\mathbf{x} \in \mathbb{C}^p$ from a set of dimensionality-reduced linear measurements $\mathbf{b} = \mathbf {A}\mathbf {x}$ arises in a variety of applications, such as medical imaging, spectroscopy, Fou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16a968a70c38725419005374cf92a277
Publikováno v:
Compressed Sensing and its Applications ISBN: 9783319160412
During the past decades, sparsity has been shown to be of significant importance in fields such as compression, signal sampling and analysis, machine learning, and optimization. In fact, most natural data can be sparsely represented, i.e., a small se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23e1d131c51c313c057981e93303e5a6
https://doi.org/10.1007/978-3-319-16042-9_12
https://doi.org/10.1007/978-3-319-16042-9_12