Learning Compressed Transforms with Low Displacement Rank

4 October 2018

Papers citing "Learning Compressed Transforms with Low Displacement Rank"

8 / 8 papers shown

Title
Block Circulant Adapter for Large Language Models Xinyu Ding Meiqi Wang Siyu Liao Zhongfeng Wang 36 0 0 01 May 2025
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks Ashwin Samudre Mircea Petrache Brian D. Nord Shubhendu Trivedi 44 2 0 18 Sep 2024
Reducing Memory Requirements for the IPU using Butterfly Factorizations S. Shekofteh Christian Alles Holger Fröning 22 0 0 16 Sep 2023
Monarch: Expressive Structured Matrices for Efficient and Accurate Training Tri Dao Beidi Chen N. Sohoni Arjun D Desai Michael Poli Jessica Grogan Alexander Liu Aniruddh Rao Atri Rudra Christopher Ré 22 87 0 01 Apr 2022
Sparse Linear Networks with a Fixed Butterfly Structure: Theory and Practice Nir Ailon Omer Leibovitch Vineet Nair 13 14 0 17 Jul 2020
Understanding and Training Deep Diagonal Circulant Neural Networks Alexandre Araujo Benjamin Négrevergne Y. Chevaleyre Jamal Atif 19 4 0 29 Jan 2019
Equivariant Transformer Networks Kai Sheng Tai Peter Bailis Gregory Valiant ViT 17 68 0 25 Jan 2019
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 250 3,236 0 24 Nov 2016