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IEEE Signal Processing Magazine

CURRENT ISSUE

CURRENT ISSUE
July 2022
Reproducibility in Matrix and Tensor Decompositions: Focus on model match, interpretability, and uniqueness
Data-driven solutions are playing an increasingly important role in numerous practical problems across multiple disciplines. The shift from the traditional model-driven approaches to those that are data driven naturally emphasizes the importance of the explainability of solutions, as, in this case, the connection to a physical model is often not obvious. Explainability is a broad umbrella and includes interpretability, but it also implies that the solutions need to be complete, in that one should be able to “audit” them, ask appropriate questions, and hence gain further insight about their inner workings.
Trusting in the Sciences Requires Explainability
The July issue of IEEE Signal Processing Magazine (SPM) is a special issue focused on “Explainability in Data Science: Interpretability, Reproducibility, and Replicability.” With increased enthusiasm for machine learning, it is a very timely topic, and I invite every IEEE Signal Processing Society (SPS) member to read these very instructive papers.
Explainability in Graph Data Science: Interpretability, replicability, and reproducibility of community detection
In many modern data science problems, data are represented by a graph (network), e.g., social, biological, and communication networks. Over the past decade, numerous signal processing and machine learning (ML) algorithms have been introduced for analyzing graph structured data. With the growth of interest in graphs and graph-based learning tasks in a variety of applications, there is a need to explore explainability in graph data science.
Interpretability, Reproducibility, and Replicability
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.
May 2022
Ethical Dilemmas in the Sciences
“Science without conscience is only ruin of the soul” said François Rabelais. This centuries-old quote still resonates, today maybe louder than ever. I began to write this editorial at the end of February when Russian tanks and soldiers invaded Ukraine and waves of bombers began dropping their bombs on Ukrainian cities, targeting civilian buildings, hospitals, and schools. This dramatic event was a shock to Europeans, since most of them have lived in relative peace for more than 70 years.