Decomposes excess risk in nonstationary weighted ERM into learning and drift terms, then proves oracle inequalities under mixing that recover minimax rates in stationary cases.
Trade-off between dependence and complexity for non- parametric learning – an empirical process approach.arXiv preprint arXiv:2401.08978
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Fast Rates for Nonstationary Weighted Risk Minimization
Decomposes excess risk in nonstationary weighted ERM into learning and drift terms, then proves oracle inequalities under mixing that recover minimax rates in stationary cases.