A Gradient Flow Framework For Analyzing Network Pruning

24 September 2020

Papers citing "A Gradient Flow Framework For Analyzing Network Pruning"

8 / 8 papers shown

Title
Neuroplasticity in Artificial Intelligence -- An Overview and Inspirations on Drop In & Out Learning Yupei Li M. Milling Björn Schuller AI4CE 107 0 0 27 Mar 2025
Straightforward Layer-wise Pruning for More Efficient Visual Adaptation Ruizi Han Jinglei Tang 45 1 0 19 Jul 2024
Always-Sparse Training by Growing Connections with Guided Stochastic Exploration Mike Heddes Narayan Srinivasa T. Givargis Alexandru Nicolau 91 0 0 12 Jan 2024
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers Chen Liang Haoming Jiang Zheng Li Xianfeng Tang Bin Yin Tuo Zhao VLM 24 24 0 19 Feb 2023
Zeroth-Order Topological Insights into Iterative Magnitude Pruning Aishwarya H. Balwani J. Krzyston 24 2 0 14 Jun 2022
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning Sanghoon Myung I. Huh Wonik Jang Jae Myung Choe Jisu Ryu Daesin Kim Kee-Eung Kim C. Jeong 22 13 0 12 Jun 2022
Rare Gems: Finding Lottery Tickets at Initialization Kartik K. Sreenivasan Jy-yong Sohn Liu Yang Matthew Grinde Alliot Nagle Hongyi Wang Eric P. Xing Kangwook Lee Dimitris Papailiopoulos 16 42 0 24 Feb 2022
Decomposable-Net: Scalable Low-Rank Compression for Neural Networks A. Yaguchi Taiji Suzuki Shuhei Nitta Y. Sakata A. Tanizawa 17 9 0 29 Oct 2019