Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Sophie M. Fosson"'
Publikováno v:
IFAC-PapersOnLine. 54:298-303
Sparse linear system identification can be performed through convex optimization, by the minimization of an l1-norm functional. If an errors-in-variables model is considered, the problem is more challenging as inherently non-convex. The l1-norm appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bf7e0f71dd1d6ac02a9b4d2b7f20201
https://doi.org/10.1016/j.ifacol.2021.08.375
https://doi.org/10.1016/j.ifacol.2021.08.375
Publikováno v:
Pattern recognition letters 128 (2019): 93–99. doi:10.1016/j.patrec.2019.08.014
info:cnr-pdr/source/autori:Valsesia, Diego; Fosson, Sophie M.; Ravazzi, Chiara; Bianchi, Tiziano; Magli, Enrico/titolo:Analysis of SparseHash: An efficient embedding of set-similarity via sparse projections/doi:10.1016%2Fj.patrec.2019.08.014/rivista:Pattern recognition letters/anno:2019/pagina_da:93/pagina_a:99/intervallo_pagine:93–99/volume:128
info:cnr-pdr/source/autori:Valsesia, Diego; Fosson, Sophie M.; Ravazzi, Chiara; Bianchi, Tiziano; Magli, Enrico/titolo:Analysis of SparseHash: An efficient embedding of set-similarity via sparse projections/doi:10.1016%2Fj.patrec.2019.08.014/rivista:Pattern recognition letters/anno:2019/pagina_da:93/pagina_a:99/intervallo_pagine:93–99/volume:128
Embeddings provide compact representations of signals in order to perform efficient inference in a wide variety of tasks. In particular, random projections are common tools to construct Euclidean distance-preserving embeddings, while hashing techniqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ceb362667a3b6e8655224dd70c26ad32
https://doi.org/10.1016/j.patrec.2019.08.014
https://doi.org/10.1016/j.patrec.2019.08.014
Publikováno v:
ICCA
In this paper we address the computation of the Bode plots for linear time-invariant systems affected by semi-algebraic parameteric uncertainty. The problem of computing Bode magnitude and phase bounds is formulated in terms of non-convex semialgebra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f04a1bd5aa139ecf674600b21e83dcb5
https://doi.org/10.1109/icca51439.2020.9264418
https://doi.org/10.1109/icca51439.2020.9264418
Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation, semidefinite programming relaxations (SDR’s) are proposed in the l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b54c77636858b6e6fd90091704c889c2
http://arxiv.org/abs/2003.08696
http://arxiv.org/abs/2003.08696
Autor:
Sophie M. Fosson
Publikováno v:
IEEE Signal Processing Letters. 25:1795-1799
Iterative $\ell _1$ reweighting algorithms are very popular in sparse signal recovery and compressed sensing, since in the practice they have been observed to outperform classical $\ell _1$ methods. Nevertheless, the theoretical analysis of their con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44bc710cb009ec3b906722be0d74bbd6
https://doi.org/10.1109/lsp.2018.2875251
https://doi.org/10.1109/lsp.2018.2875251
Autor:
Sophie M. Fosson
The development of online algorithms to track time-varying systems has drawn a lot of attention in the last years, in particular in the framework of online convex optimization. Meanwhile, sparse time-varying optimization has emerged as a powerful too
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02bbff47f484a4a6c6f0863a324e7d73
The problem of sparse linear regression is relevant in the context of linear system identification from large datasets. When data are collected from real-world experiments, measurements are always affected by perturbations or low-precision representa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e9e2fb27b659993f809dab38be48ce2
http://hdl.handle.net/11583/2847825
http://hdl.handle.net/11583/2847825
Publikováno v:
CDC
In this paper, a recursive identification approach to single-input single-output linear time varying (LTV) systems when both the output and the input measurements are corrupted by bounded noise is considered. First, the problem is formulated in terms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40bf03992d00af0b8b86926a710f2734
http://hdl.handle.net/11583/2846109
http://hdl.handle.net/11583/2846109
Publikováno v:
CDC
We consider the problem of the recovery of a k-sparse vector from compressed linear measurements when data are corrupted by a quantization noise. When the number of measurements is not sufficiently large, different $k$-sparse solutions may be present
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d9b571b0129c88dd9a51fe9edcc8566
https://doi.org/10.1109/cdc40024.2019.9030257
https://doi.org/10.1109/cdc40024.2019.9030257
Publikováno v:
ECC 2019-18th European Control Conference
ECC 2019-18th European Control Conference, Jun 2019, Naples, Italy. pp.2344-2349, ⟨10.23919/ECC.2019.8795699⟩
ECC
ECC 2019-18th European Control Conference, Jun 2019, Naples, Italy. pp.2344-2349, ⟨10.23919/ECC.2019.8795699⟩
ECC
Motivated by cyber-physical security applications, we face the problem of estimating the state and the input of a linear system, where the input may represent the presence of adversarial attacks. We consider the case where classical filters cannot be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34e7325e758365b14bdf0a51cc9ca019
https://hal.inria.fr/hal-02094213
https://hal.inria.fr/hal-02094213