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Practical Applications of Sparse Modeling
Key approaches in the rapidly developing area of sparse modeling, focusing on its application in fields including neuroscience, computational biology, and computer vision. Sparse …
Sparse Modeling
Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is …
Machine Learning and Interpretation in Neuroimaging
Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, …
Machine Learning and Interpretation in Neuroimaging
This book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2014, held in Montreal, QC, …