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cs.LG2025
A Trainable Optimizer
Ruiqi Wang, Diego Klabjan
The concept of learning to optimize involves utilizing a trainable optimization strategy rather than relying on manually defined full gradient estimations such as ADAM. We present…
cs.LG2022★ 2 cited
Divergence Results and Convergence of a Variance Reduced Version of ADAM
Ruiqi Wang, Diego Klabjan
Stochastic optimization algorithms using exponential moving averages of the past gradients, such as ADAM, RMSProp and AdaGrad, have been having great successes in many applications…