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cs.LG2022
Manifold Characteristics That Predict Downstream Task Performance
Ruan van der Merwe, Gregory Newman, Etienne Barnard
Pretraining methods are typically compared by evaluating the accuracy of linear classifiers, transfer learning performance, or visually inspecting the representation manifold's (RM…
cs.LG2020
DNNs as Layers of Cooperating Classifiers
Marelie H. Davel, Marthinus W. Theunissen, Arnold M. Pretorius +1
A robust theoretical framework that can describe and predict the generalization ability of deep neural networks (DNNs) in general circumstances remains elusive. Classical attempts…