Interpretability, Reproducibility, and Replicability
| dc.contributor.author | Adali, Tulay | |
| dc.contributor.author | Guido, Rodrigo Capobianco [UNESP] | |
| dc.contributor.author | Ho, Tin Kam | |
| dc.contributor.author | Muller, Klaus-Robert | |
| dc.contributor.author | Strother, Stephen | |
| dc.contributor.institution | University of Maryland | |
| dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
| dc.contributor.institution | Senior Artificial Intelligence Scientist | |
| dc.contributor.institution | Computer Science | |
| dc.contributor.institution | Medical Biophysics | |
| dc.date.accessioned | 2023-03-02T06:50:36Z | |
| dc.date.available | 2023-03-02T06:50:36Z | |
| dc.date.issued | 2022-07-01 | |
| dc.description.abstract | Most of the work we do in signal processing these days is data driven. The shift from the more traditional and model-driven approaches to those that are data driven has also underlined the importance of explainability of our solutions. Because most traditional signal processing approaches start with a number of modeling assumptions, they are comprehensible by the very nature of their construction. However, this is not necessarily the case when we choose to rely more heavily on the data and minimize modeling assumptions. | en |
| dc.description.affiliation | University of Maryland Department of Computer Science and Electrical Engineering, Baltimore County | |
| dc.description.affiliation | São Paulo State University (UNESP), São Paulo | |
| dc.description.affiliation | Ibm Watson Health Senior Artificial Intelligence Scientist, Yorktown Heights | |
| dc.description.affiliation | Tu Berlin Computer Science | |
| dc.description.affiliation | University of Toronto Medical Biophysics | |
| dc.description.affiliationUnesp | São Paulo State University (UNESP), São Paulo | |
| dc.format.extent | 5-7 | |
| dc.identifier | http://dx.doi.org/10.1109/MSP.2022.3170665 | |
| dc.identifier.citation | IEEE Signal Processing Magazine, v. 39, n. 4, p. 5-7, 2022. | |
| dc.identifier.doi | 10.1109/MSP.2022.3170665 | |
| dc.identifier.issn | 1558-0792 | |
| dc.identifier.issn | 1053-5888 | |
| dc.identifier.scopus | 2-s2.0-85133739377 | |
| dc.identifier.uri | http://hdl.handle.net/11449/242024 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | IEEE Signal Processing Magazine | |
| dc.source | Scopus | |
| dc.title | Interpretability, Reproducibility, and Replicability | en |
| dc.type | Editorial |