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The Representer Theorem is a fundamental result in the field of machine learning and functional analysis, particularly in the context of regularized empirical risk minimization problems. It provides a bridge between high-dimensional data and solutions in a reproducing kernel Hilbert space (RKHS). ### Key Concepts: 1. **Empirical Risk Minimization:** This is the process of minimizing the empirical risk (or training error) over a dataset.

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