Enhancing IoT Malware Detection through Adaptive Model Parallelism and Resource Optimization

12 April 2024

Papers citing "Enhancing IoT Malware Detection through Adaptive Model Parallelism and Resource Optimization"

8 / 8 papers shown

Title
A Comparison of Static, Dynamic, and Hybrid Analysis for Malware Detection Anusha Damodaran Fabio Di Troia C. A. Visaggio Thomas H. Austin Mark Stamp 51 381 0 13 Mar 2022
Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models Daniel Bogdoll Johannes Jestram Jonas Rauch Christin Scheib Moritz Wittig J. Marius Zöllner 50 9 0 05 Nov 2021
Maximizing Parallelism in Distributed Training for Huge Neural Networks Zhengda Bian Qifan Xu Boxiang Wang Yang You MoE 53 47 0 30 May 2021
A Novel Malware Detection Mechanism based on Features Extracted from Converted Malware Binary Images Abhijitt Dhavlle Sanket Shukla 24 7 0 14 Apr 2021
A Linear Algebraic Approach to Model Parallelism in Deep Learning Russell J. Hewett Thomas J. Grady FedML 42 16 0 04 Jun 2020
A Survey on Distributed Machine Learning Joost Verbraeken Matthijs Wolting Jonathan Katzy Jeroen Kloppenburg Tim Verbelen Jan S. Rellermeyer OOD 105 713 0 20 Dec 2019
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism Mohammad Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 343 1,920 0 17 Sep 2019
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision Sorin Grigorescu GAN VLM 54 13 0 19 Dec 2018