We propose a variant of the follow the regularized leader (FTRL) algorithm called follow the moving leader (FTML).
The proposed algorithm, which will be called follow the mov- ing leader (FTML), shows strong connections with popu- lar deep learning optimizers such as RMSprop ...
Inspired by the close connection between stochastic optimization and online learning, we propose a variant of the follow the regularized leader (FTRL) algorithm ...
FTML is closely related to RMSprop and Adam. In particular, it enjoys their nice properties, but avoids their pitfalls. Experimental results on a number of ...
Nov 6, 2013 · The “Follow the Regularized Leader” algorithm stems from the online learning setting, where the learning process is sequential.
Jul 3, 2019 · Follow the moving leader in deep learning. In Proceedings of the 34th International Conference on Machine. Learning-Volume 70, pages 4110–4119.
Feb 21, 2017 · Follow-The-Leader uses a very simple approach: track the performance of all experts over all previous time steps, then select the expert/ ...
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The task of following-the-leader is implemented using a hierarchical deep neural network (DNN) end-to-end driving model to match the direction and speed of a ...
May 10, 2019 · I've been working on news recommendation problem, and I'm implementing a factorization machine optimized by FTRL.
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"Follow The Regularized Leader" (FTRL) is an optimization algorithm developed at Google for click-through rate prediction in the early 2010s.