Loss Landscape
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VC TheoryReproducing Kernel Hilbert Space (RKHS)Hilbert-Schmidt independence criterion (HSIC)
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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

When are ensembles really effective

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Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training

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