Convex Optimization for Machine Learning: The Graduate Workbook: Theory, Duality, First-Order Algorithms, Regularized Learning, Sparse Models, Kernel Methods, and Research Applications

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Pages: 444, Paperback, Independently published

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Numerical Methods for Machine Learning: Optimization, Stability, and Algorithms

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