ما معنى Online learning, recursive least squares, forgetting factor؟

Online learning updates a model with each new observation, in constant time and memory, and is scored prequentially: each observation is predicted before it is learned from. Recursive least squares (RLS) updates the weighted least-squares solution $\hat\beta_t = \arg\min_b\sum_{s\le t}\lambda^{t-s}(y_s - x_s^\top b)^2$ by

where the forgetting factor $\lambda\in(0,1]$ discounts old observations; their weights sum to about $1/(1-\lambda)$, the estimator’s effective memory.