Following the great success of the Finnish-French Workshops in Helsinki 2018 and Annecy 2019, the third Edition of the Statistical Learning for Signal and Image Processing Workshop is dedicated both to methodological aspects and applications challenges. Due to the COVID-19 pandemia, the SLSIP Workshop is postponed to October 6th - Octoboer 8th 2021.

New statistical learning approaches, methods, theory and tools are urgently required to account for modern complex, dynamic and large-scale settings. For example, the transformation of our energy and communication networks necessitate the reliable extraction of information from large-scale dynamic sensor network settings. Further, biomedical signal processing and analysis, image reconstruction, detection and classification require advanced learning methods that provide reliable results with statistical guarantees and high robustness requirements.

The main topics of this workshop concern machine learning for robust signal processing and control, biomedical signal and image processing, statistical modelling of sparse, complex and multi-sensor data, graph theory for signal processing in dynamic and large-scale networks, and distributed optimization for smart systems with applications, such as, neuroscience, electric systems, array signal processing.