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This lecture covers the Recursive Least-Squares (RLS) algorithm, focusing on the exponentially weighted formulation with 2-regularization. The algorithm enables real-time updating of the minimizer, making it suitable for streaming data. The lecture also discusses the derivation of the RLS algorithm, including the recursive update steps and the weighted least-squares problem. The presentation emphasizes the importance of forgetting factors, regularization parameters, and sample averaging in the algorithm's efficiency.