201 citations · 718 across the 30 of their papers we have counts for
32 papers
Population-Based Multi-Objective Training of Discriminators for Semi-Supervised GANs
Francisco Sedeño, Francisco Chicano, Jamal Toutouh
Semi-supervised generative adversarial networks (SSL-GANs) can exploit large unlabeled datasets while retaining a classifier in the discriminator, but their training is often unsta…
Robust Multi-Objective Optimization for Bicycle Rebalancing in Shared Mobility Systems
Diego Daniel Pedroza-Perez, Gabriel Luque, Sergio Nesmachnow +1
Dock-based bike-sharing systems exhibit spatial imbalances between bicycle supply and user demand, often addressed through overnight truck-based rebalancing. This work studies stat…
Adversarial attacks to image classification systems using evolutionary algorithms
Sergio Nesmachnow, Jamal Toutouh
Image classification currently faces significant security challenges due to adversarial attacks, which consist of intentional alterations designed to deceive classification models…
Guiding Evolutionary AutoEncoder Training with Activation-Based Pruning Operators
Steven Jorgensen, Erik Hemberg, Jamal Toutouh +1
This study explores a novel approach to neural network pruning using evolutionary computation, focusing on simultaneously pruning the encoder and decoder of an autoencoder. We intr…
Generate more than one child in your co-evolutionary semi-supervised learning GAN
Francisco Sedeño, Jamal Toutouh, Francisco Chicano
Generative Adversarial Networks (GANs) are very useful methods to address semi-supervised learning (SSL) datasets, thanks to their ability to generate samples similar to real data.…
Performance Analysis of Optimized VANET Protocols in Real World Tests
Jamal Toutouh, Enrique Alba
Vehicular ad hoc networks (VANETs) provide the communications required to deploy Intelligent Transportation Systems (ITS). In the current state of the art in this field there is a…
Evolutionary Power-Aware Routing in VANETs using Monte-Carlo Simulation
J. Toutouh, S. Nesmachnow, E. Alba
This work addresses the reduction of power consumption of the AODV routing protocol in vehicular networks as an optimization problem. Nowadays, network designers focus on energy-aw…
Light commodity devices for building vehicular ad hoc networks: An experimental study
Jamal Toutouh, Enrique Alba
Vehicular communication networks represent both an opportunity and a challenge for providing smart mobility services by using a hybrid solution that relies on cellular connectivity…
QoS-Aware Radio Access Technology (RAT) Selection in Hybrid Vehicular Networks
Zeeshan Hameed Mir, Jamal Toutouh, Fethi Filali +1
The increasing number of wireless communication technologies and standards bring immense opportunities and challenges to provide seamless connectivity in Hybrid Vehicular Networks…
Infrastructure Deployment in Vehicular Communication Networks Using a Parallel Multiobjective Evolutionary Algorithm
Renzo Massobrio, Jamal Toutouh, Sergio Nesmachniw +1
This article describes the application of a multiobjective evolutionary algorithm for locating roadside infrastructure for vehicular communication networks over realistic urban are…
A swarm algorithm for collaborative traffic in vehicular networks
Jamal Toutouh, Enrique Alba
Vehicular ad hoc networks (VANETs) allow vehicles to exchange warning messages with each other. These specific kinds of networks help reduce hazardous traffic situations and improv…
Fast energy-aware OLSR routing in VANETs by means of a parallel evolutionary algorithm
Jamal Toutouh, Sergio Nesmachnow, Enrique Alba
This work tackles the problem of reducing the power consumption of the OLSR routing protocol in vehicular networks. Nowadays, energy-aware and green communication protocols are imp…
Parallel multi-objective metaheuristics for smart communications in vehicular networks
Jamal Toutouh, Enrique Alba
This article analyzes the use of two parallel multi-objective soft computing algorithms to automatically search for high-quality settings of the Ad hoc On Demand Vector routing pro…
Intelligent OLSR Routing Protocol Optimization for VANETs
Jamal Toutouh, José García-Nieto, Enrique Alba
Recent advances in wireless technologies have given rise to the emergence of vehicular ad hoc networks (VANETs). In such networks, the limited coverage of WiFi and the high mobilit…
Automatic tuning of communication protocols for vehicular ad hoc networks using metaheuristics
José García-Nieto, Jamal Toutouh, Enrique Alba
The emerging field of vehicular ad hoc networks (VANETs) deals with a set of communicating vehicles which are able to spontaneously interconnect without any pre-existing infrastruc…
Evolutionary latent space search for driving human portrait generation
Benjamín Machín, Sergio Nesmachnow, Jamal Toutouh
This article presents an evolutionary approach for synthetic human portraits generation based on the latent space exploration of a generative adversarial network. The idea is to pr…
Citizen centric optimal electric vehicle charging stations locations in a full city: case of Malaga
Christian Cintrano, Jamal Toutouh, Enrique Alba
This article presents the problem of locating electric vehicle (EV) charging stations in a city by defining the Electric Vehicle Charging Stations Locations (EV-CSL) problem. The i…
Reliable and Fast Recurrent Neural Network Architecture Optimization
Andrés Camero, Jamal Toutouh, Enrique Alba
This article introduces Random Error Sampling-based Neuroevolution (RESN), a novel automatic method to optimize recurrent neural network architectures. RESN combines an evolutionar…
Fostering Diversity in Spatial Evolutionary Generative Adversarial Networks
Jamal Toutouh, Erik Hemberg, Una-May O'Reilly
Generative adversary networks (GANs) suffer from training pathologies such as instability and mode collapse, which mainly arise from a lack of diversity in their adversarial intera…
Exact and heuristic approaches for multi-objective garbage accumulation points location in real scenarios
Diego Gabriel Rossit, Jamal Toutouh, Sergio Nesmachnow
Municipal solid waste management is a major challenge for nowadays urban societies, because it accounts for a large proportion of public budget and, when mishandled, it can lead to…
Signal Propagation in a Gradient-Based and Evolutionary Learning System
Jamal Toutouh, Una-May O'Reilly
Generative adversarial networks (GANs) exhibit training pathologies that can lead to convergence-related degenerative behaviors, whereas spatially-distributed, coevolutionary algor…
Conditional Generative Adversarial Networks to Model Urban Outdoor Air Pollution
Jamal Toutouh
This is a relevant problem because the design of most cities prioritizes the use of motorized vehicles, which has degraded air quality in recent years, having a negative effect on…
Analyzing the Components of Distributed Coevolutionary GAN Training
Jamal Toutouh, Erik Hemberg, Una-May O'Reilly
Distributed coevolutionary Generative Adversarial Network (GAN) training has empirically shown success in overcoming GAN training pathologies. This is mainly due to diversity maint…
Adversarial Genetic Programming for Cyber Security: A Rising Application Domain Where GP Matters
Una-May O'Reilly, Jamal Toutouh, Marcos Pertierra +5
Cyber security adversaries and engagements are ubiquitous and ceaseless. We delineate Adversarial Genetic Programming for Cyber Security, a research topic that, by means of genetic…