Jesus L. Lobo

Orcid: 0000-0002-6283-5148

According to our database1, Jesus L. Lobo authored at least 48 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Managing the unknown in machine learning: Definitions, related areas, recent advances, and prospects.
Neurocomputing, 2024

AiGAS-dEVL: An Adaptive Incremental Neural Gas Model for Drifting Data Streams under Extreme Verification Latency.
CoRR, 2024

Balancing Performance, Efficiency and Robustness in Open-World Machine Learning via Evolutionary Multi-objective Model Compression.
Proceedings of the International Joint Conference on Neural Networks, 2024

Resilience to the Flowing Unknown: An Open Set Recognition Framework for Data Streams.
Proceedings of the Hybrid Artificial Intelligent Systems - 19th International Conference, 2024

2023
A novel Out-of-Distribution detection approach for Spiking Neural Networks: Design, fusion, performance evaluation and explainability.
Inf. Fusion, December, 2023

Effective air pollution prediction by combining time series decomposition with stacking and bagging ensembles of evolving spiking neural networks.
Environ. Model. Softw., December, 2023

Understanding the challenges and novel architectural models of multi-cloud native applications - a systematic literature review.
J. Cloud Comput., 2023

Managing the unknown: a survey on Open Set Recognition and tangential areas.
CoRR, 2023

On the Connection between Concept Drift and Uncertainty in Industrial Artificial Intelligence.
CoRR, 2023

IEM: A Unified Lifecycle Orchestrator for Multilingual IaC Deployments.
Proceedings of the Companion of the 2023 ACM/SPEC International Conference on Performance Engineering, 2023

Evolutionary Multi-Objective Quantization of Randomization-Based Neural Networks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Multiobjective Optimization Analysis for Finding Infrastructure-as-Code Deployment Configurations.
Proceedings of the 2023 11th International Conference on Computer and Communications Management, 2023

Optimizing IaC Configurations: a Case Study Using Nature-inspired Computing.
Proceedings of the 2023 6th International Conference on Computational Intelligence and Intelligent Systems, 2023

2022
A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural Networks.
CoRR, 2022

PIACERE project: description and prototype for optimizing infrastructure as code deployment configurations.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

A Multifactorial Cellular Genetic Algorithm for Multimodal Multitask Optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2021
Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks.
Neural Networks, 2021

AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking.
Inf. Sci., 2021

LUNAR: Cellular automata for drifting data streams.
Inf. Sci., 2021

Optimization and Prediction Techniques for Self-Healing and Self-Learning Applications in a Trustworthy Cloud Continuum.
Inf., 2021

CURIE: a cellular automaton for concept drift detection.
Data Min. Knowl. Discov., 2021

MO-MFCGA: Multiobjective Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Rank Aggregation for Non-stationary Data Streams.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

SLAYER: A Semi-supervised Learning Approach for Drifting Data Streams under Extreme Verification Latency.
Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), 2021

Lightweight Alternatives for Hyper-parameter Tuning in Drifting Data Streams.
Proceedings of the 2021 International Conference on Data Mining, 2021

2020
Spiking Neural Networks and online learning: An overview and perspectives.
Neural Networks, 2020

Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning.
Neural Networks, 2020

Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks.
Evol. Syst., 2020

Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

On the Transferability of Knowledge among Vehicle Routing Problems by using Cellular Evolutionary Multitasking.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

New Perspectives on the Use of Online Learning for Congestion Level Prediction over Traffic Data.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Multifactorial Cellular Genetic Algorithm (MFCGA): Algorithmic Design, Performance Comparison and Genetic Transferability Analysis.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019
Online Ranking with Concept Drifts in Streaming Data.
CoRR, 2019

Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning.
CoRR, 2019

Real-time Electrical Power Prediction in a Combined Cycle Power Plant.
CoRR, 2019

2018
Evolving Spiking Neural Networks for online learning over drifting data streams.
Neural Networks, 2018

DRED: An evolutionary diversity generation method for concept drift adaptation in online learning environments.
Appl. Soft Comput., 2018

Drift Detection over Non-stationary Data Streams Using Evolving Spiking Neural Networks.
Proceedings of the Intelligent Distributed Computing XII, 2018

Road Traffic Forecasting Using NeuCube and Dynamic Evolving Spiking Neural Networks.
Proceedings of the Intelligent Distributed Computing XII, 2018

Concept Tracking and Adaptation for Drifting Data Streams under Extreme Verification Latency.
Proceedings of the Intelligent Distributed Computing XII, 2018

2017
On the Creation of Diverse Ensembles for Nonstationary Environments Using Bio-inspired Heuristics.
Proceedings of the Harmony Search Algorithm, 2017

Multi-objective heuristics applied to robot task planning for inspection plants.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016
Identifying recommendation opportunities for computer-supported collaborative environments.
Expert Syst. J. Knowl. Eng., 2016

A Probabilistic Sample Matchmaking Strategy for Imbalanced Data Streams with Concept Drift.
Proceedings of the Intelligent Distributed Computing X - Proceedings of the 10th International Symposium on Intelligent Distributed Computing, 2016

Cognitive workload classification using eye-tracking and EEG data.
Proceedings of the International Conference on Human-Computer Interaction in Aerospace, 2016

Community detection in graphs based on surprise maximization using firefly heuristics.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2014
Towards a Transferable and Domain-Independent Reputation Indicator to Group Students in the Collaborative Logical Framework Approach.
Proceedings of the Posters, 2014

2013
Towards Semantic Descriptions of Collaboration Indicators to Support Collaboration Models Transferability.
Proceedings of the Workshops at the 16th International Conference on Artificial Intelligence in Education AIED 2013, 2013


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