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1506.02617
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Path-SGD: Path-Normalized Optimization in Deep Neural Networks
Neural Information Processing Systems (NeurIPS), 2015
8 June 2015
Behnam Neyshabur
Ruslan Salakhutdinov
Nathan Srebro
ODL
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Papers citing
"Path-SGD: Path-Normalized Optimization in Deep Neural Networks"
50 / 195 papers shown
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Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings
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The Empirical Impact of Reducing Symmetries on the Performance of Deep Ensembles and MoE
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An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models
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Difan Zou
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Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problems
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Liang Zhang
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Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm
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Robert D. Nowak
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Tong Zhang
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Cédric Gerbelot
Avetik G. Karagulyan
Stefani Karp
Kavya Ravichandran
Menachem Stern
Nathan Srebro
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Nonparametric regression using over-parameterized shallow ReLU neural networks
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347
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Hidden symmetries of ReLU networks
International Conference on Machine Learning (ICML), 2023
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David Rolnick
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Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks
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Atli Kosson
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Improving Convergence and Generalization Using Parameter Symmetries
International Conference on Learning Representations (ICLR), 2023
Bo Zhao
Robert Mansel Gower
Robin Walters
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MoMe
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Exploring the Complexity of Deep Neural Networks through Functional Equivalence
International Conference on Machine Learning (ICML), 2023
Guohao Shen
372
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Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks
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Jianfeng Lu
197
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Solving Regularized Exp, Cosh and Sinh Regression Problems
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Rethinking White-Box Watermarks on Deep Learning Models under Neural Structural Obfuscation
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International Conference on Machine Learning (ICML), 2023
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Instance-Dependent Generalization Bounds via Optimal Transport
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Songyan Hou
Parnian Kassraie
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I. Ganev
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Nima Dehmamy
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