Loss Landscape
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Preliminaries
VC TheoryReproducing Kernel Hilbert Space (RKHS)Hilbert-Schmidt independence criterion (HSIC)
Methmatic Tools
Centered Kernel Alignment (CKA)Mode Connectivity (MC)Hessian MatrixHeavy Tail Self-regression (HT-SR)
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Taxonomizing local versus global structure in neural network loss landscapesEvaluating natural language processing models with generalization metrics that do not need access to any training or testing dataA Three-regime Model of Network PruningTemperature Balancing, Layer-wise Weight Analysis, and Neural Network TrainingWhen are ensembles really effective
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Updated on: 2024-05-15

Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data

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Taxonomizing local versus global structure in neural network loss landscapes
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A Three-regime Model of Network Pruning

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