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Found 2 papers, 2 papers with code
Tom: Leveraging trend of the observed gradients for faster convergence
To eliminate the dependency of learning rate schedulers, adaptive gradient optimizers such as AdaGrad, AdaDelta, RMSProp, Adam employ a parameter-wise scaling term for learning rate which is a function of the gradient itself.
Estimation and Applications of Quantiles in Deep Binary Classification
We quantify the uncertainty of the class probabilities in terms of prediction intervals, and develop individualized confidence scores that can be used to decide whether a prediction is reliable or not at scoring time.
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