AI RESEARCH
Online learning of smooth functions on $\mathbb{R}$
arXiv CS.LG
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ArXi:2604.03525v1 Announce Type: new We study adversarial online learning of real-valued functions on $\mathbb{R}$. In each round the learner is queried at $x_t\in\mathbb{R}$, predicts $\hat y_t$, and then observes the true value $f(x_t)$; performance is measured by cumulative $p$-loss $\sum_{t\ge 1}|\hat y_t-f(x_t)|^p