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On the Implicit Bias of initialization Shape Beyond Infinitesimal Mirror Descent
OntheImplicitBiasofinitializationShape:BeyondInﬁnitesimalMirrorDescentShaharAzulay1EdwardMoroshko2MorShpigelNacson2BlakeWoodworth3NathanSrebro3AmirGloberson1DanielSoudry2Abstractparameterizedmodel...
of on the Shape Implicit
2023-11-16 19:15:461926783.44 KB14
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On the Explicit Role of initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
OntheExplicitRoleofinitializationontheConvergenceandImplicitBiasofOverparametrizedLinearNetworksHanchengMin12SalmaTarmoun13Rene´Vidal14EnriqueMallada12Abstractwithoutexplicitregularization,enjoysg...
of on on the Explicit
2023-11-16 19:15:46660520.57 KB9
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Improving Transformer Optimization Through Better initialization
ImprovingTransformerOptimizationThroughBetterinitializationXiaoShiHuang12FelipePe´rez1JimmyBa32MaksimsVolkovs1Abstractetal.,2019;Sunetal.,2019).Despitethebroadapplications,optimizationintheTransfo...
Optimization through Improving Better initialization
2023-11-14 21:44:3612743.62 MB9
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Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
GradientdescentwithidentityinitializationefﬁcientlylearnspositivedeﬁnitelineartransformationsbydeepresidualnetworksPeterL.Bartlett1DavidP.Helmbold2PhilipM.Long3Abstract1.IntroductionWeanalyzealgo...
with Gradient Descent Efficiently Identity
2023-11-13 11:59:40697280.82 KB4
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On the Implicit Bias of initialization Shape Beyond Infinitesimal Mirror Descent

On the Explicit Role of initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks

Improving Transformer Optimization Through Better initialization

Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks