579 citations · 630 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 39 cited
Practical Quasi-Newton Methods for Training Deep Neural Networks
Donald Goldfarb, Yi Ren, Achraf Bahamou
We consider the development of practical stochastic quasi-Newton, and in particular Kronecker-factored block-diagonal BFGS and L-BFGS methods, for training deep neural networks (DN…
cs.LG2019★ 12 cited
Efficient Subsampled Gauss-Newton and Natural Gradient Methods for Training Neural Networks
Yi Ren, Donald Goldfarb
We present practical Levenberg-Marquardt variants of Gauss-Newton and natural gradient methods for solving non-convex optimization problems that arise in training deep neural netwo…
cs.CL2019★ 579 cited
FastSpeech: Fast, Robust and Controllable Text to Speech
Yi Ren, Yangjun Ruan, Xu Tan +4
Neural network based end-to-end text to speech (TTS) has significantly improved the quality of synthesized speech. Prominent methods (e.g., Tacotron 2) usually first generate mel-s…