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Identifiability of Model Properties in Over-Parameterized Model Classes
[chapter]
2013
Lecture Notes in Computer Science
Classical learning theory is based on a tight linkage between hypothesis space (a class of function on a domain X), data space (function-value examples (x, f (x))), and the space of queries for the learned model (predicting function values for new examples x). However, in many learning scenarios the 3-way association between hypotheses, data, and queries can really be much looser. Model classes can be overparameterized, i.e., different hypotheses may be equivalent with respect to the data
doi:10.1007/978-3-642-40994-3_8
fatcat:7mqtsmxjqnhqleh5b2kb2ifctu