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This lecture covers the truncated conjugate gradients algorithm for solving positive definite linear maps. It explains the iterative process, the computation of conjugate directions, and the minimization of a quadratic function subject to constraints. The instructor discusses the trust-region method and the local and global behavior of the algorithm, providing theoretical insights and practical applications.