565 citations · 1.1k across the 21 of their papers we have counts for
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Optimal Linear Decay Learning Rate Schedules and Further Refinements
Aaron Defazio, Ashok Cutkosky, Harsh Mehta +1
Learning rate schedules used in practice bear little resemblance to those recommended by theory. We close much of this theory/practice gap, and as a consequence are able to derive…
Mechanic: A Learning Rate Tuner
Ashok Cutkosky, Aaron Defazio, Harsh Mehta
We introduce a technique for tuning the learning rate scale factor of any base optimization algorithm and schedule automatically, which we call \textsc{mechanic}. Our method provid…
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
Ashok Cutkosky, Harsh Mehta, Francesco Orabona
We present new algorithms for optimizing non-smooth, non-convex stochastic objectives based on a novel analysis technique. This improves the current best-known complexity for findi…