On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons

5 December 2021

Papers citing "On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons"

13 / 13 papers shown

Title
Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable? Maxime Méloux Silviu Maniu François Portet Maxime Peyrard 42 0 0 28 Feb 2025
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity Kai Yi Nidham Gazagnadou Peter Richtárik Lingjuan Lyu 79 11 0 15 Apr 2024
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat Erdong Hu Yu-Shuen Tang Anastasios Kyrillidis C. Jermaine FedML 36 10 0 06 Sep 2023
Towards a Better Theoretical Understanding of Independent Subnetwork Training Egor Shulgin Peter Richtárik AI4CE 28 6 0 28 Jun 2023
MIRACLE: Multi-task Learning based Interpretable Regulation of Autoimmune Diseases through Common Latent Epigenetics Pengcheng Xu Jinpu Cai Yulin Gao Ziqi Rong AI4CE 18 0 0 24 Jun 2023
Xtreme Margin: A Tunable Loss Function for Binary Classification Problems Rayan Wali MQ 20 3 0 31 Oct 2022
LOFT: Finding Lottery Tickets through Filter-wise Training Qihan Wang Chen Dun Fangshuo Liao C. Jermaine Anastasios Kyrillidis 27 3 0 28 Oct 2022
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout Chen Dun Mirian Hipolito Garcia C. Jermaine Dimitrios Dimitriadis Anastasios Kyrillidis 64 20 0 28 Oct 2022
On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks Hongru Yang Zhangyang Wang MLT 32 8 0 27 Mar 2022
Masked Training of Neural Networks with Partial Gradients Amirkeivan Mohtashami Martin Jaggi Sebastian U. Stich 15 22 0 16 Jun 2021
GIST: Distributed Training for Large-Scale Graph Convolutional Networks Cameron R. Wolfe Jingkang Yang Arindam Chowdhury Chen Dun Artun Bayer Santiago Segarra Anastasios Kyrillidis BDL GNN LRM 51 9 0 20 Feb 2021
On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths Quynh N. Nguyen 43 48 0 24 Jan 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015