Sparse Modeling textbook by Irina Rish resurfaces as a classic intro to sparsity theory
FrnkNlsn · x · 2026-11-12
A shared link to Sparse Modeling: Theory, Algorithms, and Applications (Irina Rish & Genady Grabarnik, CRC Press, 2015, 254 pp), part of the Chapman & Hall ML & Pattern Recognition series.
The book covers:
- Motivating applications like biomarker discovery in genetic/neuroimaging data, where interpretability matters
- Optimization formulations with sparsity-enforcing tools, core sparse recovery theory, and state-of-the-art algorithms
- Extensions to structured sparsity, different loss functions, sparse graphical models, dictionary learning, and sparse matrix factorizations
Still a solid entry point for sparse regression and compressed sensing fundamentals.
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