Following the great success of the Finnish-French Workshops in Helsinki 2018, Annecy 2019, and the German Edition in Rüdesheim 2021 and Spanish edition in Cadaques 2022, of the Statistical Learning for Signal and Image Processing (SLSIP) Workshop, we have decided to organize a new edition in the beautiful island of Porquerolles, France. This workshop is dedicated both to methodological aspects and application challenges. 

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 statistical 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.