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Article
Open AccessPSO + FL = PAASO: particle swarm optimization + federated learning = privacy-aware agent swarm optimization
In this paper, we present an unified framework that encompasses both particle swarm optimization (PSO) and federated learning (FL). This unified framework shows that we can understand both PSO and FL in terms ...
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Chapter and Conference Paper
PSOwp: Particle Swarm Optimisation Without Panopticon to Evaluate Private Social Choice
In a recent paper we introduced differentially private random dictatorship as a private mechanism for social choice. Differentially private mechanisms are evaluated in terms of their utility and information lo...
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Article
On the analysis of hyper-parameter space for a genetic programming system with iterated F-Race
Evolutionary algorithms (EAs) have been with us for several decades and are highly popular given that they have proved competitive in the face of challenging problems’ features such as deceptiveness, multiple ...
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Chapter and Conference Paper
Explaining Recurrent Machine Learning Models: Integral Privacy Revisited
We have recently introduced a privacy model for statistical and machine learning models called integral privacy. A model extracted from a database or, in general, the output of a function satisfies integral pr...
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Article
Performance assessment of a multi-objective parametric optimization algorithm with application to a multi-physical engineering system
Engineers routinely perform parameter studies to investigate how system response changes over a range of parameter values. This can provide engineering insight into the importance of an exogenous variable, the...
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Chapter and Conference Paper
Locality in Continuous Fitness-Valued Cases and Genetic Programming Difficulty
It is commonly accepted that a map** is local if it preserves neighbourhood. In Evolutionary Computation, locality is generally described as the property that neighbouring genotypes correspond to neighbourin...
