Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Laura Balzano"'
Publikováno v:
IEEE Open Journal of Control Systems, Vol 1, Pp 335-353 (2022)
Switched systems are capable of modeling processes with underlying dynamics that may change abruptly over time. To achieve accurate modeling in practice, one may need a large number of modes, but this may in turn increase the model complexity drastic
Externí odkaz:
https://doaj.org/article/fe933cb9851f4245ba523c738ea46e2a
Autor:
Tasha Thong, Yutong Wang, Michael D. Brooks, Christopher T. Lee, Clayton Scott, Laura Balzano, Max S. Wicha, Justin A. Colacino
Publikováno v:
Frontiers in Cell and Developmental Biology, Vol 8 (2020)
Similarities between stem cells and cancer cells have implicated mammary stem cells in breast carcinogenesis. Recent evidence suggests that normal breast stem cells exist in multiple phenotypic states: epithelial, mesenchymal, and hybrid epithelial/m
Externí odkaz:
https://doaj.org/article/3d368196c177406e9f920e93f3e5ca04
Publikováno v:
SIAM Journal on Mathematics of Data Science. 5:222-250
Modern data are increasingly both high-dimensional and heteroscedastic. This paper considers the challenge of estimating underlying principal components from high-dimensional data with noise that is heteroscedastic across samples, i.e., some samples
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::75a12d927563a11039456a595489c834
https://doi.org/10.1137/22m1470244
https://doi.org/10.1137/22m1470244
Publikováno v:
IEEE Open Journal of Control Systems. 1:335-353
Switched systems are capable of modeling processes with underlying dynamics that may change abruptly over time. To achieve accurate modeling in practice, one may need a large number of modes, but this may in turn increase the model complexity drastic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9006b5fa7c41a8531232363b4a081bd2
https://doi.org/10.1109/ojcsys.2022.3212613
https://doi.org/10.1109/ojcsys.2022.3212613
Publikováno v:
2022 30th European Signal Processing Conference (EUSIPCO).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2ee1627f94853831dda4dff36cc9dd5
https://doi.org/10.23919/eusipco55093.2022.9909952
https://doi.org/10.23919/eusipco55093.2022.9909952
Publikováno v:
2022 American Control Conference (ACC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f1c4f2b75826271d9a9add2d18f3db9
https://doi.org/10.23919/acc53348.2022.9867863
https://doi.org/10.23919/acc53348.2022.9867863
Publikováno v:
SIAM Journal on Mathematics of Data Science. 3:253-279
In the low-rank matrix completion (LRMC) problem, the low-rank assumption means that the columns (or rows) of the matrix to be completed are points on a low-dimensional linear algebraic variety. This paper extends this thinking to cases where the col
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::193ffbb8f2e623622ffc606fb7bf9d4e
https://doi.org/10.1137/20m1323448
https://doi.org/10.1137/20m1323448
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 12:1575-1588
Subspace clustering is a powerful generalization of clustering for high-dimensional data analysis, where low-rank cluster structure is leveraged for accurate inference. $K$ -Subspaces (KSS), an alternating algorithm that mirrors $K$ -means, is a clas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0aa599acd02980a97aebc199969183c
https://doi.org/10.1109/jstsp.2018.2869363
https://doi.org/10.1109/jstsp.2018.2869363
Principal component analysis (PCA) is a classical and ubiquitous method for reducing data dimensionality, but it is suboptimal for heterogeneous data that are increasingly common in modern applications. PCA treats all samples uniformly so degrades wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f01efae45b22434a3bbf5ccc834dc04b
Real-world control applications often involve complex dynamics subject to abrupt changes or variations. Markov jump linear systems (MJS) provide a rich framework for modeling such dynamics. Despite an extensive history, theoretical understanding of p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6198e3a9206395736f81ba9d24bfd4b