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Explores diverse regularization approaches, including the L0 quasi-norm and the Lasso method, discussing variable selection and efficient algorithms for optimization.
Covers the Branch & Bound algorithm for efficient exploration of feasible solutions and discusses LP relaxation, portfolio optimization, Nonlinear Programming, and various optimization problems.