DropNet: Reducing Neural Network Complexity via Iterative Pruning

14 July 2022

Papers citing "DropNet: Reducing Neural Network Complexity via Iterative Pruning"

29 / 29 papers shown

Title
An Efficient Training Algorithm for Models with Block-wise Sparsity Ding Zhu Zhiqun Zuo Mohammad Mahdi Khalili 37 0 0 27 Mar 2025
Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Models Xubin Wang Zhiqing Tang Jianxiong Guo Tianhui Meng Chenhao Wang Tian-sheng Wang Weijia Jia 50 0 0 08 Mar 2025
Security and Real-time FPGA integration for Learned Image Compression Alaa Mazouz Carl De Sousa Tria Sumanta Chaudhuri A. Fiandrotti Marco Cagnanzzo Mihai P. Mitrea Enzo Tartaglione 43 1 0 06 Mar 2025
Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies Xubin Wang Weijia Jia 36 0 0 08 Jan 2025
Reassessing Layer Pruning in LLMs: New Insights and Methods Yao Lu Hao Cheng Yujie Fang Zeyu Wang Jiaheng Wei Dongwei Xu Qi Xuan Xiaoniu Yang Zhaowei Zhu 63 0 0 23 Nov 2024
FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning Boyu Fan Chenrui Wu Xiang Su Pan Hui FedML 40 2 0 06 Jul 2024
HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator Zhewen Yu Sudarshan Sreeram Krish Agrawal Junyi Wu Alexander Montgomerie-Corcoran Cheng Zhang Jianyi Cheng C. Bouganis Yiren Zhao 24 1 0 05 Jun 2024
Pruning for Robust Concept Erasing in Diffusion Models Tianyun Yang Juan Cao Chang Xu 27 13 0 26 May 2024
Advancing IIoT with Over-the-Air Federated Learning: The Role of Iterative Magnitude Pruning Fazal Muhammad Ali Khan Hatem Abou-Zeid Aryan Kaushik Syed Ali Hassan 19 1 0 21 Mar 2024
Dependable Distributed Training of Compressed Machine Learning Models F. Malandrino G. Giacomo Marco Levorato C. Chiasserini 24 0 0 22 Feb 2024
Fluctuation-based Adaptive Structured Pruning for Large Language Models Yongqi An Xu Zhao Tao Yu Ming Tang Jinqiao Wang 31 42 0 19 Dec 2023
Relationship between Model Compression and Adversarial Robustness: A Review of Current Evidence Svetlana Pavlitska Hannes Grolig J. Marius Zöllner AAML 16 3 0 27 Nov 2023
Mixture-of-Linguistic-Experts Adapters for Improving and Interpreting Pre-trained Language Models Raymond Li Gabriel Murray Giuseppe Carenini MoE 41 2 0 24 Oct 2023
Equitable-FL: Federated Learning with Sparsity for Resource-Constrained Environment Indrajeet Kumar Sinha Shekhar Verma Krishna Pratap Singh FedML 32 0 0 02 Sep 2023
Benchmarking Adversarial Robustness of Compressed Deep Learning Models Brijesh Vora Kartik Patwari Syed Mahbub Hafiz Zubair Shafiq Chen-Nee Chuah AAML 19 2 0 16 Aug 2023
Understanding Activation Patterns in Artificial Neural Networks by Exploring Stochastic Processes S. Lehmler Muhammad Saif-ur-Rehman Tobias Glasmachers Ioannis Iossifidis 19 0 0 01 Aug 2023
Approximate Computing Survey, Part II: Application-Specific & Architectural Approximation Techniques and Applications Vasileios Leon Muhammad Abdullah Hanif Giorgos Armeniakos Xun Jiao Muhammad Shafique K. Pekmestzi Dimitrios Soudris 29 3 0 20 Jul 2023
A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services Dewant Katare Diego Perino J. Nurmi M. Warnier Marijn Janssen Aaron Yi Ding 34 36 0 13 Apr 2023
Structured Pruning for Deep Convolutional Neural Networks: A survey Yang He Lingao Xiao 3DPC 28 116 0 01 Mar 2023
When Layers Play the Lottery, all Tickets Win at Initialization Artur Jordão George Correa de Araujo H. Maia Hélio Pedrini 13 3 0 25 Jan 2023
Optimizing Learning Rate Schedules for Iterative Pruning of Deep Neural Networks Shiyu Liu Rohan Ghosh John Tan Chong Min Mehul Motani 29 0 0 09 Dec 2022
COST-EFF: Collaborative Optimization of Spatial and Temporal Efficiency with Slenderized Multi-exit Language Models Bowen Shen Zheng Lin Yuanxin Liu Zhengxiao Liu Lei Wang Weiping Wang VLM 33 4 0 27 Oct 2022
Neural Networks Reduction via Lumping Dalila Ressi Riccardo Romanello S. Rossi Carla Piazza 30 4 0 15 Sep 2022
FedPrune: Towards Inclusive Federated Learning Muhammad Tahir Munir Muhammad Mustansar Saeed Mahad Ali Z. Qazi I. Qazi FedML 13 18 0 27 Oct 2021
S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks Shiyu Liu Chong Min John Tan Mehul Motani CLL 21 4 0 17 Oct 2021
Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values Zhenquan Lin K. Guo Xiaofen Xing Xiangmin Xu ODL 24 1 0 09 Oct 2021
On the Effect of Pruning on Adversarial Robustness Artur Jordão Hélio Pedrini AAML 32 22 0 10 Aug 2021
AdaptCL: Efficient Collaborative Learning with Dynamic and Adaptive Pruning Guangmeng Zhou Ke Xu Qi Li Yang Liu Yi Zhao 16 8 0 27 Jun 2021
Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not? Ning Liu Geng Yuan Zhengping Che Xuan Shen Xiaolong Ma Qing Jin Jian Ren Jian Tang Sijia Liu Yanzhi Wang 26 30 0 19 Feb 2021