57 papers with code • 1 benchmarks • 1 datasets

Deep Learning on EDGE devices


Latest papers without code

Physical Side-Channel Attacks on Embedded Neural Networks: A Survey

no code yet • 21 Oct 2021

Neural Networks (NN) are expected to become ubiquitous in IoT systems by transforming all sorts of real-world applications, including applications in the safety-critical and security-sensitive domains.


Distributed Reinforcement Learning for Privacy-Preserving Dynamic Edge Caching

no code yet • 20 Oct 2021

In this paper, a privacy-preserving distributed deep deterministic policy gradient (P2D3PG) algorithm is proposed to maximize the cache hit rates of devices in the MEC networks.

Edge-computing Federated Learning

Energon: Towards Efficient Acceleration of Transformers Using Dynamic Sparse Attention

no code yet • 18 Oct 2021

To enable such an algorithm with lower latency and better energy-efficiency, we also propose an Energon co-processor architecture.


Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing

no code yet • 18 Oct 2021

Federated Learning (FL) over wireless multi-hop edge computing networks, i. e., multi-hop FL, is a cost-effective distributed on-device deep learning paradigm.

Edge-computing Federated Learning +1

BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers

no code yet • 18 Oct 2021

As a promising distributed learning technology, analog aggregation based federated learning over the air (FLOA) provides high communication efficiency and privacy provisioning in edge computing paradigm.

Edge-computing Federated Learning

A Deep Learning-based Approach for Real-time Facemask Detection

no code yet • 17 Oct 2021

Several experiments are conducted and show good performances of the proposed approach (99% for training and testing accuracy).


Nothing Wasted: Full Contribution Enforcement in Federated Edge Learning

no code yet • 15 Oct 2021

In particular, federated edge learning (FEL) becomes prominent in securing the privacy of data owners by keeping the data locally used to train ML models.

Edge-computing Fairness

Predicting Solar Flares with Remote Sensing and Machine Learning

no code yet • 14 Oct 2021

High energy solar flares and coronal mass ejections have the potential to destroy Earth's ground and satellite infrastructures, causing trillions of dollars in damage and mass human suffering.


DeepEdge: A Deep Reinforcement Learning based Task Orchestrator for Edge Computing

no code yet • 5 Oct 2021

The improvements in the edge computing technology pave the road for diversified applications that demand real-time interaction.