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Parameter-free, Dynamic, and Strongly-Adaptive Online Learning
parameter-free
#23
opened Jan 15, 2021 by
nocotan
Stochastic gradient descent on Riemannian manifolds
riemannian optimization
#21
opened Jan 13, 2021 by
nocotan
Adabelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
deep learning
#19
opened Jan 7, 2021 by
nocotan
AdaScale SGD: A User-Friendly Algorithm for Distributed Training
deep learning
parameter-free
#13
opened Jan 4, 2021 by
nocotan
Augment Your Batch: Improving Generalization Through Instance Repetition
#12
opened Jan 2, 2021 by
nocotan
On the distance between two neural networks and the stability of learning
deep learning
parameter-free
#10
opened Jan 2, 2021 by
nocotan
Choosing the Sample with Lowest Loss makes SGD Robust
deep learning
#9
opened Jan 1, 2021 by
nocotan
SEVER: A Robust Meta-Algorithm for Stochastic Optimization
deep learning
meta-algorithm
#8
opened Dec 31, 2020 by
nocotan
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds
riemannian optimization
#6
opened Dec 30, 2020 by
nocotan
A Sufficient Condition for Convergences of Adam and RMSProp
deep learning
#5
opened Dec 29, 2020 by
nocotan
Sharpness-Aware Minimization for Efficiently Improving Generalization
deep learning
#4
opened Dec 29, 2020 by
nocotan
Achieving All with No Parameters: AdaNormalHedge
Parameter-free Learning with Experts
parameter-free
#3
opened Dec 28, 2020 by
nocotan
ProTip!
Exclude everything labeled
bug
with -label:bug.