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1905.10018
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Momentum-Based Variance Reduction in Non-Convex SGD
24 May 2019
Ashok Cutkosky
Francesco Orabona
ODL
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Papers citing
"Momentum-Based Variance Reduction in Non-Convex SGD"
50 / 77 papers shown
Title
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Extended convexity and smoothness and their applications in deep learning
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On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy
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Gradient-Free Method for Heavily Constrained Nonconvex Optimization
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Private Zeroth-Order Nonsmooth Nonconvex Optimization
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Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum
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Random Scaling and Momentum for Non-smooth Non-convex Optimization
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Robust Decentralized Learning with Local Updates and Gradient Tracking
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Flora: Low-Rank Adapters Are Secretly Gradient Compressors
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Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
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Adaptive Stochastic Optimisation of Nonconvex Composite Objectives
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