SVAG method examines biased updates in variance-reduced stochastic gradient methods.
problem Examining biased updates in variance-reduced stochastic gradient methods.
method Introduces SVAG, a SAG/SAGA-like method with adjustable bias, analyzed in a cocoercive root-finding setting.
result SVAG's step-size requirements for gradients are less restrictive compared to non-gradient cases, highlighting the need for careful analysis.