activity
20142023
most citedDeep Learning in Multi-Layer Architectures of Dense Nuclei

16 citations · 27 across the 8 of their papers we have counts for

collaborators

8 papers

cs.NI20231 cited

Associated Random Neural Networks for Collective Classification of Nodes in Botnet Attacks

Erol Gelenbe, Mert Nakıp

Botnet attacks are a major threat to networked systems because of their ability to turn the network nodes that they compromise into additional attackers, leading to the spread of h…

cs.CR2023

Real-Time Cyberattack Detection with Offline and Online Learning

Erol Gelenbe, Mert Nakıp

This paper presents several novel algorithms for real-time cyberattack detection using the Auto-Associative Deep Random Neural Network, which were developed in the HORIZON 2020 IoT…

cs.LG20167 cited

Nonnegative autoencoder with simplified random neural network

Yonghua Yin, Erol Gelenbe

This paper proposes new nonnegative (shallow and multi-layer) autoencoders by combining the spiking Random Neural Network (RNN) model, the network architecture typical used in deep…

cs.NE201616 cited

Deep Learning in Multi-Layer Architectures of Dense Nuclei

Yonghua Yin, Erol Gelenbe

We assume that, within the dense clusters of neurons that can be found in nuclei, cells may interconnect via soma-to-soma interactions, in addition to conventional synaptic connect…

cs.DC20153 cited

Adaptive Dispatching of Tasks in the Cloud

Lan Wang, Erol Gelenbe

The increasingly wide application of Cloud Computing enables the consolidation of tens of thousands of applications in shared infrastructures. Thus, meeting the quality of service…

cs.OH2015

Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation

Huibo Bi, Erol Gelenbe

State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory da…