activity
20182022
most citedTopological Insights into Sparse Neural Networks

4 citations · 6 across the 3 of their papers we have counts for

collaborators

8 papers

cs.NE2022

Online Distributed Evolutionary Optimization of Time Division Multiple Access Protocols

Anil Yaman, Tim van der Lee, Giovanni Iacca

With the advent of cheap, miniaturized electronics, ubiquitous networking has reached an unprecedented level of complexity, scale and heterogeneity, becoming the core of several mo…

cs.NE20212 cited

A Framework for Knowledge Integrated Evolutionary Algorithms

Ahmed Hallawa, Anil Yaman, Giovanni Iacca +1

One of the main reasons for the success of Evolutionary Algorithms (EAs) is their general-purposeness, i.e., the fact that they can be applied straightforwardly to a broad range of…

cs.LG20204 cited

Topological Insights into Sparse Neural Networks

Shiwei Liu, Tim Van der Lee, Anil Yaman +5

Sparse neural networks are effective approaches to reduce the resource requirements for the deployment of deep neural networks. Recently, the concept of adaptive sparse connectivit…

cs.NE2020

Distributed Embodied Evolution over Networks

Anil Yaman, Giovanni Iacca

In several network problems the optimum behavior of the agents (i.e., the nodes of the network) is not known before deployment. Furthermore, the agents might be required to adapt,…

cs.NE2020

Novelty Producing Synaptic Plasticity

Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu +2

A learning process with the plasticity property often requires reinforcement signals to guide the process. However, in some tasks (e.g. maze-navigation), it is very difficult (or i…

cs.NE2019

Learning with Delayed Synaptic Plasticity

Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu +2

The plasticity property of biological neural networks allows them to perform learning and optimize their behavior by changing their configuration. Inspired by biology, plasticity c…