Gabriel de Oliveira Ramos

According to our database, Gabriel de Oliveira Ramos authored at least 47 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

An encoder-decoder deep neural network for binary segmentation of seismic facies.

Gefersom Lima, Felipe André Zeiser, Ariane da Silveira, Sandro José Rigo, Gabriel de Oliveira Ramos

Comput. Geosci., January, 2024

Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.

Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers

CoRR, 2024

2023

A machine-learning based data-oriented pipeline for Prognosis and Health Management Systems.

Marcos Leandro Hoffmann Souza, Cristiano André da Costa, Gabriel de Oliveira Ramos

Comput. Ind., June, 2023

Multi-Objective Decision-Making Meets Dynamic Shortest Path: Challenges and Prospects.

Juarez Machado da Silva, Gabriel de Oliveira Ramos, Jorge Luis Victória Barbosa

Algorithms, March, 2023

Pleural Effusion Classification on Chest X-Ray Images with Contrastive Learning.

Felipe André Zeiser, Ismael Santos, Henrique Bohn, Cristiano André da Costa, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi, Andreas Maier, José Rodrigo M. Andrade, Alexandre Bacelar

Proceedings of the 19th International Conference on Web Information Systems and Technologies, 2023

A Brief Guide to Multi-Objective Reinforcement Learning and Planning.

Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Scalar Reward is Not Enough.

Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Friedrik Hentz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

ELFpm: A machine learning framework for industrial machines prediction of remaining useful life.

Jovani Dalzochio, Rafael Kunst, Jorge Luis Victória Barbosa, Henrique Damasceno Vianna, Gabriel de Oliveira Ramos, Edison Pignaton, Alécio P. D. Binotto, Jose Favilla

Neurocomputing, 2022

Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization.

Bruno Grisci, Gabriela Kuhn, Felipe Colombelli, Vítor Kehl Matter, Leomar Lima, Karine Heinen, Mauricio Pegoraro, Marcio Borges, Sandro José Rigo, Jorge L. V. Barbosa, Rodrigo da Rosa Righi, Cristiano André da Costa, Gabriel de Oliveira Ramos

CoRR, 2022

A rapid review of machine learning approaches for telemedicine in the scope of COVID-19.

Luana Carine Schünke, Blanda Mello, Cristiano André da Costa, Rodolfo Stoffel Antunes, Sandro José Rigo, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi, Juliana Nichterwitz Scherer, Bruna Donida

Artif. Intell. Medicine, 2022

Prediction of Harvest Time of Apple Trees: An RNN-Based Approach.

Tiago Boechel, Lucas Micol Policarpo, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi, Dhananjay Singh

Algorithms, 2022

Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021).

Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale

Auton. Agents Multi Agent Syst., 2022

A practical guide to multi-objective reinforcement learning and planning.

Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Auton. Agents Multi Agent Syst., 2022

MoStress: a Sequence Model for Stress Classification.

Arturo de Souza, Mateus Begnini Melchiades, Sandro José Rigo, Gabriel de Oliveira Ramos

Proceedings of the International Joint Conference on Neural Networks, 2022

On the Explainability and Expressiveness of Function Approximation Methods in RL-Based Traffic Signal Control.

Lincoln Vinicius Schreiber, Lucas Nunes Alegre, Ana L. C. Bazzan, Gabriel de Oliveira Ramos

Proceedings of the International Joint Conference on Neural Networks, 2022

DeepCADD: A Deep Learning Architecture for Automatic Detection of Coronary Artery Disease.

Samuel A. Freitas, Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos

Proceedings of the International Joint Conference on Neural Networks, 2022

The multi-objective dynamic shortest path problem.

Juarez Machado da Silva, Gabriel de Oliveira Ramos, Jorge L. V. Barbosa

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

An Interpolated Approach for Active Debris Removal.

João Batista Rodrigues Neto, Gabriel de Oliveira Ramos

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

Multi-objective prioritization for data center vulnerability remediation.

Felipe Colombelli, Vítor Kehl Matter, Bruno Iochins Grisci, Leomar Lima, Karine Heinen, Marcio Borges, Sandro José Rigo, Jorge Luis Victória Barbosa, Rodrigo da Rosa Righi, Cristiano André da Costa, Gabriel de Oliveira Ramos

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

Aiding Glaucoma Diagnosis from the Automated Classification and Segmentation of Fundus Images.

Lucas M. Ceschini, Lucas Micol Policarpo, Rodrigo da Rosa Righi, Gabriel de Oliveira Ramos

Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

On Social Consensus Mechanisms for Federated Learning Aggregation.

Igor Felipe de Camargo, Rodolfo Stoffel Antunes, Gabriel de Oliveira Ramos

Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021

A systematic mapping study of robotics in human care.

Nícolas B. Santos, Rodrigo Simon Bavaresco, João Elison da Rosa Tavares, Gabriel de Oliveira Ramos, Jorge L. V. Barbosa

Robotics Auton. Syst., 2021

<i>DeepBatch</i>: A hybrid deep learning model for interpretable diagnosis of breast cancer in whole-slide images.

Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos, Henrique Bohn, Ismael Santos, Adriana Vial Roehe

Expert Syst. Appl., 2021

A feature identification method to explain anomalies in condition monitoring.

Marcos Leandro Hoffmann Souza, Cristiano André da Costa, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi

Comput. Ind., 2021

HealthMon: An approach for monitoring machines degradation using time-series decomposition, clustering, and metaheuristics.

Miromar José de Lima, César David Paredes Crovato, Rodrigo Ivan Goytia Mejia, Rodrigo da Rosa Righi, Gabriel de Oliveira Ramos, Cristiano André da Costa, Giovani Pesenti

Comput. Ind. Eng., 2021

Fuzzy time series for predicting phenological stages of apple trees.

Tiago Boechel, Lucas Micol Policarpo, Gabriel de Oliveira Ramos, Rodrigo da Rosa Righi

Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021

Evaluation of Convolutional Neural Networks for COVID-19 Classification on Chest X-Rays.

Felipe André Zeiser, Cristiano André da Costa, Gabriel de Oliveira Ramos, Henrique Bohn, Ismael Santos, Rodrigo da Rosa Righi

Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

An Enhanced TSP-Based Approach for Active Debris Removal Mission Planning.

João Batista Rodrigues Neto, Gabriel de Oliveira Ramos

Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

2020

Toll-based reinforcement learning for efficient equilibria in route choice.

Gabriel de Oliveira Ramos, Bruno C. da Silva, Roxana Radulescu, Ana L. C. Bazzan, Ann Nowé

Knowl. Eng. Rev., 2020

ElHealth: Using Internet of Things and data prediction for elastic management of human resources in smart hospitals.

Gabriel Souto Fischer, Rodrigo da Rosa Righi, Gabriel de Oliveira Ramos, Cristiano André da Costa, Joel J. P. C. Rodrigues

Eng. Appl. Artif. Intell., 2020

Binary Segmentation of Seismic Facies Using Encoder-Decoder Neural Networks.

Gefersom Lima, Gabriel de Oliveira Ramos, Sandro Rigo, Felipe André Zeiser, Ariane da Silveira

CoRR, 2020

On the Role of Reward Functions for Reinforcement Learning in the Traffic Assignment Problem.

Ricardo Grunitzki, Gabriel de Oliveira Ramos

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Toll-Based Learning for Minimising Congestion under Heterogeneous Preferences.

Gabriel de Oliveira Ramos, Roxana Radulescu, Ann Nowé, Anderson R. Tavares

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Experience Sharing Between Cooperative Reinforcement Learning Agents.

Lucas Oliveira Souza, Gabriel de Oliveira Ramos, Célia Ghedini Ralha

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

Self-Adaptive Appearance-Based Eye-Tracking with Online Transfer Learning.

Bruno Klein Salvalaio, Gabriel de Oliveira Ramos

Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2017

Learning to Minimise Regret in Route Choice.

Gabriel de Oliveira Ramos, Bruno Castro da Silva, Ana L. C. Bazzan

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Minimising Regret in Route Choice.

Gabriel de Oliveira Ramos

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

2016

On Estimating Action Regret and Learning From It in Route Choice.

Gabriel de Oliveira Ramos, Ana L. C. Bazzan

Proceedings of the Ninth International Workshop on Agents in Traffic and Transportation (ATT 2016) co-located with the 25th International Joint Conference On Artificial Intelligence (IJCAI 2016), 2016

Efficient local search in traffic assignment.

Gabriel de Oliveira Ramos, Ana L. C. Bazzan

Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015

A self-adapting similarity-based coalition formation approach for plug-in electric vehicles in smart grids.

Gabriel de Oliveira Ramos, Juan C. Burguillo, Ana L. C. Bazzan

Multiagent Grid Syst., 2015

Forming Coalitions of Electric Vehicles in Constrained Scenarios.

Ana L. C. Bazzan, Gabriel de Oliveira Ramos

Proceedings of the Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability - The PAAMS Collection, 2015

Towards the User Equilibrium in Traffic Assignment Using GRASP with Path Relinking.

Gabriel de Oliveira Ramos, Ana Lúcia Cetertich Bazzan

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2014

Dynamic constrained coalition formation among electric vehicles.

Gabriel de Oliveira Ramos, Juan C. Burguillo, Ana L. C. Bazzan

J. Braz. Comput. Soc., 2014

Individual versus Difference Rewards on Reinforcement Learning for Route Choice.

Ricardo Grunitzki, Gabriel de Oliveira Ramos, Ana Lúcia C. Bazzan

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

An Improved Learning Automata Approach for the Route Choice Problem.

Gabriel de Oliveira Ramos, Ricardo Grunitzki

Proceedings of the Agent Technology for Intelligent Mobile Services and Smart Societies, 2014

2013

Self-Adapting Coalition Formation Among Electric Vehicles in Smart Grids.

Gabriel de Oliveira Ramos, Juan C. Burguillo-Rial, Ana L. C. Bazzan

Proceedings of the 7th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2013

Towards a Platform for Testing and Developing Privacy-Preserving Data Mining Applications for Smart Grids.

Andrew Koster, Gabriel de Oliveira Ramos, Ana L. C. Bazzan, Fernando Koch

Proceedings of the Multiagent System Technologies - 11th German Conference, 2013