380 citations · 848 across the 35 of their papers we have counts for
3 papers · 1 filter
STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods
Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha
Neural networks (NNs) have been successfully deployed in many applications. However, architectural design of these models is still a challenging problem. Moreover, neural networks…
Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks
Xiaoliang Dai, Hongxu Yin, Niraj K. Jha
Deep neural networks (DNNs) have become a widely deployed model for numerous machine learning applications. However, their fixed architecture, substantial training cost, and signif…
NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm
Xiaoliang Dai, Hongxu Yin, Niraj K. Jha
Deep neural networks (DNNs) have begun to have a pervasive impact on various applications of machine learning. However, the problem of finding an optimal DNN architecture for large…