306 citations · 682 across the 25 of their papers we have counts for
4 papers · 1 filter
Stein Variational Gradient Descent With Matrix-Valued Kernels
Dilin Wang, Ziyang Tang, Chandrajit Bajaj +1
Stein variational gradient descent (SVGD) is a particle-based inference algorithm that leverages gradient information for efficient approximate inference. In this work, we enhance…
Splitting Steepest Descent for Growing Neural Architectures
Qiang Liu, Lemeng Wu, Dilin Wang
We develop a progressive training approach for neural networks which adaptively grows the network structure by splitting existing neurons to multiple off-springs. By leveraging a f…
Energy-Aware Neural Architecture Optimization with Fast Splitting Steepest Descent
Dilin Wang, Meng Li, Lemeng Wu +2
Designing energy-efficient networks is of critical importance for enabling state-of-the-art deep learning in mobile and edge settings where the computation and energy budgets are h…
Improving Neural Language Modeling via Adversarial Training
Dilin Wang, Chengyue Gong, Qiang Liu
Recently, substantial progress has been made in language modeling by using deep neural networks. However, in practice, large scale neural language models have been shown to be pron…