most citedLearning to Prune Deep Neural Networks via Reinforcement Learning

7 citations · 7 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2022

PaRT: Parallel Learning Towards Robust and Transparent AI

Mahsa Paknezhad, Hamsawardhini Rengarajan, Chenghao Yuan +4

This paper takes a parallel learning approach for robust and transparent AI. A deep neural network is trained in parallel on multiple tasks, where each task is trained only on a su…

cs.AI2020★ 7 cited

Learning to Prune Deep Neural Networks via Reinforcement Learning

Manas Gupta, Siddharth Aravindan, Aleksandra Kalisz +2

This paper proposes PuRL - a deep reinforcement learning (RL) based algorithm for pruning neural networks. Unlike current RL based model compression approaches where feedback is gi…