Fig. 4: Bias-variance decomposition of generalization error. a Average estimator for kernel regression with \(K(x,x^{\prime} )=\mathop{\sum }\nolimits_{k = 1}^{N}\cos (k(x-x^{\prime} ))\) on target function \(\
Since the constant DC component is embedded in noise, we need to come up with an estimator function to estimate the DC component from the received samples. The goal of our estimator function is to estimate the DC component so that the mean of the estimate should be equal to the actual DC...
One popular framework is the Partial Information Decomposition (PID) method, introduced in 2010 by William and Beer [10], which postulates that information can be decomposed into unique, redundant, and synergistic information atoms [11]. However, no measure that satisfies the axioms, or similar ...
SMORMS3 is particularly useful in Deep Neural Networks (DNNs), where the gradients have a high variance and it might prevent the learning rate from becoming too small, which could potentially slow down the optimization process [174]. Another optimizer that has also been proposed in the ...