Where to Pay Attention in Sparse Training for Feature Selection?

26 November 2022

Papers citing "Where to Pay Attention in Sparse Training for Feature Selection?"

8 / 8 papers shown

Title
SAND: One-Shot Feature Selection with Additive Noise Distortion P. Pad Hadi Hammoud Mohamad Dia Nadim Maamari L. A. Dunbar 28 0 0 06 May 2025
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation Boqian Wu Q. Xiao Shiwei Liu Lu Yin Mykola Pechenizkiy D. Mocanu M. V. Keulen Elena Mocanu MedIm 53 4 0 20 Feb 2025
RelChaNet: Neural Network Feature Selection using Relative Change Scores Felix Zimmer 24 0 0 03 Oct 2024
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness Boqian Wu Q. Xiao Shunxin Wang N. Strisciuglio Mykola Pechenizkiy M. V. Keulen D. Mocanu Elena Mocanu OOD 3DH 52 0 0 03 Oct 2024
Joint Feature and Differentiable $k$ -NN Graph Learning using Dirichlet Energy Lei Xu Lei Chen Rong Wang Feiping Nie Xuelong Li 27 1 0 21 May 2023
Truly Sparse Neural Networks at Scale Selima Curci D. Mocanu Mykola Pechenizkiy 25 19 0 02 Feb 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 141 684 0 31 Jan 2021
Survey on Feature Selection T. Abdallah B. Iglesia 60 229 0 10 Oct 2015