Accurate Neural Network Pruning Requires Rethinking Sparse Optimization

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Accurate Neural Network Pruning Requires Rethinking Sparse Optimization

3 August 2023

Denis Kuznedelev

Eugenia Iofinova

Alexandra Peste

Dan Alistarh

ArXiv (abs)PDF HTML HuggingFace (1 upvotes)

Papers citing "Accurate Neural Network Pruning Requires Rethinking Sparse Optimization"

6 / 6 papers shown

Title
HAM: A Hyperbolic Step to Regulate Implicit Bias Tom Jacobs Advait Gadhikar Celia Rubio-Madrigal R. Burkholz 188 0 0 03 Jun 2025
Mask in the Mirror: Implicit SparsificationInternational Conference on Learning Representations (ICLR), 2024 Tom Jacobs R. Burkholz 445 6 0 19 Aug 2024
Cyclic Sparse Training: Is it Enough? Advait Gadhikar Sree Harsha Nelaturu R. Burkholz CLL 370 1 0 04 Jun 2024
FedComLoc: Communication-Efficient Distributed Training of Sparse and Quantized Models Kai Yi Georg Meinhardt Laurent Condat Peter Richtárik FedML 306 6 0 14 Mar 2024
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization T. Yasuda Kyriakos Axiotis Gang Fu M. Bateni Vahab Mirrokni 405 2 0 27 Feb 2024
A Simple and Effective Pruning Approach for Large Language ModelsInternational Conference on Learning Representations (ICLR), 2023 Mingjie Sun Zhuang Liu Anna Bair J. Zico Kolter 457 633 0 20 Jun 2023