Learning Theory
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Learning Guarantees Recovered with Data Simulators for Dependent Processes
This work introduces "simulatable processes" as a framework to bridge the gap in learning theory between independent and dependent data. By providing a simulator of the data-generating process, classical PAC learning guarantees, notably VC dimension-dependent error bounds, can be achieved even for c…