João Vinagre

According to our database, João Vinagre authored at least 46 papers between 2012 and 2024.

Collaborative distances:

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

2024

Flow Correlation Attacks on Tor Onion Service Sessions with Sliding Subset Sum.

Daniela Lopes, Jin-Dong Dong, Pedro Medeiros, Daniel Castro, Diogo Barradas, Bernardo Portela, João Vinagre, Bernardo Ferreira, Nicolas Christin, Nuno Santos

Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024

Federated Online Learning for Heavy Hitter Detection.

Paula Raissa Silva, João Vinagre, João Gama

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Towards federated learning: An overview of methods and applications.

Paula Raissa Silva, João Vinagre, João Gama

WIREs Data. Mining. Knowl. Discov., 2023

Behind Recommender Systems: the Geography of the ACM RecSys Community.

Lorenzo Porcaro, João Vinagre, Pedro Frau, Isabelle Hupont, Emilia Gómez

CoRR, 2023

A DTW Approach for Complex Data A Case Study with Network Data Streams.

Paula Raissa Silva, João Vinagre, João Gama

Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling.

João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Fairness and Diversity in Information Access Systems.

Lorenzo Porcaro, Carlos Castillo, Emilia Gómez, João Vinagre

Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Measuring Latency-Accuracy Trade-Offs in Convolutional Neural Networks.

André Tse, Lino Oliveira, João Vinagre

Proceedings of the Progress in Artificial Intelligence, 2023

Hybrid SkipAwareRec: A Streaming Music Recommendation System.

Rui Ramos, Lino Oliveira, João Vinagre

Proceedings of the Progress in Artificial Intelligence, 2023

Mining Causal Links Between TV Sports Content and Real-World Data.

Duarte Melo, Jessica C. Delmoral, João Vinagre

Proceedings of the Progress in Artificial Intelligence, 2023

2022

Preface to the special issue on dynamic recommender systems and user models.

João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet, Paolo Cremonesi

User Model. User Adapt. Interact., 2022

Federated Anomaly Detection over Distributed Data Streams.

Paula Raissa Silva, João Vinagre, João Gama

CoRR, 2022

Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling - ORSUM 2021.

João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet

CoRR, 2022

ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling.

João Vinagre, Marie Al-Ghossein, Alípio Mário Jorge, Albert Bifet, Ladislav Peska

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Privacy-Preserving Machine Learning in Life Insurance Risk Prediction.

Klismam Pereira, João Vinagre, Ana Nunes Alonso, Fábio Coelho, Melânia Carvalho

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

Poster: User Sessions on Tor Onion Services: Can Colluding ISPs Deanonymize Them at Scale?

Daniela Lopes, Pedro Medeiros, Jin-Dong Dong, Diogo Barradas, Bernardo Portela, João Vinagre, Bernardo Ferreira, Nicolas Christin, Nuno Santos

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

Flexible Fine-grained Data Access Management for Hyperledger Fabric.

João Parente, Ana Nunes Alonso, Fábio Coelho, João Vinagre, Paulo Bastos

Proceedings of the Fourth International Conference on Blockchain Computing and Applications, 2022

2021

Statistically Robust Evaluation of Stream-Based Recommender Systems.

João Vinagre, Alípio Mário Jorge, Conceição Rocha, João Gama

IEEE Trans. Knowl. Data Eng., 2021

A Hybrid Recommender System for Improving Automatic Playlist Continuation.

Anna Gatzioura, João Vinagre, Alípio Mário Jorge, Miquel Sànchez-Marrè

IEEE Trans. Knowl. Data Eng., 2021

Hyperparameter self-tuning for data streams.

Bruno Veloso, João Gama, Benedita Malheiro, João Vinagre

Inf. Fusion, 2021

AutoFITS: Automatic Feature Engineering for Irregular Time Series.

Pedro Costa, Vítor Cerqueira, João Vinagre

CoRR, 2021

ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling.

João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Partially Monotonic Learning for Neural Networks.

Joana Trindade, João Vinagre, Kelwin Fernandes, Nuno Paiva, Alípio Jorge

Proceedings of the Advances in Intelligent Data Analysis XIX, 2021

2020

ORSUM - Workshop on Online Recommender Systems and User Modeling.

João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

2019

ORSUM 2019 2nd workshop on online recommender systems and user modeling.

João Vinagre, Alípio Mário Jorge, Albert Bifet, Marie Al-Ghossein

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

Incremental Multi-Dimensional Recommender Systems: Co-Factorization vs Tensors.

Miguel Sozinho Ramalho, João Vinagre, Alípio Mário Jorge, Rafaela Bastos

Proceedings of the 2nd Workshop on Online Recommender Systems and User Modeling, 2019

2018

Forgetting techniques for stream-based matrix factorization in recommender systems.

Pawel Matuszyk, João Vinagre, Myra Spiliopoulou, Alípio Mário Jorge, João Gama

Knowl. Inf. Syst., 2018

Online bagging for recommender systems.

João Vinagre, Alípio Mário Jorge, João Gama

Expert Syst. J. Knowl. Eng., 2018

ORSUM Chairs' Welcome & Organization.

Alípio Jorge, João Vinagre, Pawel Matuszyk, Myra Spiliopoulou

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Incremental Matrix Co-factorization for Recommender Systems with Implicit Feedback.

Susan C. Anyosa, João Vinagre, Alípio M. Jorge

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Self Hyper-parameter Tuning for Stream Recommendation Algorithms.

Bruno Veloso, João Gama, Benedita Malheiro, João Vinagre

Proceedings of the ECML PKDD 2018 Workshops, 2018

Online Gradient Boosting for Incremental Recommender Systems.

João Vinagre, Alípio Mário Jorge, João Gama

Proceedings of the Discovery Science - 21st International Conference, 2018

2017

Improving Incremental Recommenders with Online Bagging.

João Vinagre, Alípio Mário Jorge, João Gama

Proceedings of the Progress in Artificial Intelligence, 2017

2016

Scalable adaptive collaborative filtering

João Vinagre

PhD thesis, 2016

Data-Driven Relevance Judgments for Ranking Evaluation.

Nuno Moniz, Luís Torgo, João Vinagre

CoRR, 2016

Online Bagging for Recommendation with Incremental Matrix Factorization.

João Vinagre, Alípio Mário Jorge, João Gama

Proceedings of the Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV 2016) co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2016), 2016

Scalable Online Top-N Recommender Systems.

Alípio M. Jorge, João Vinagre, Marcos Aurélio Domingues, João Gama, Carlos Soares, Pawel Matuszyk, Myra Spiliopoulou

Proceedings of the E-Commerce and Web Technologies - 17th International Conference, 2016

2015

An overview on the exploitation of time in collaborative filtering.

João Vinagre, Alípio Mário Jorge, João Gama

WIREs Data Mining Knowl. Discov., 2015

Evaluation of recommender systems in streaming environments.

João Vinagre, Alípio Mário Jorge, João Gama

CoRR, 2015

Collaborative filtering with recency-based negative feedback.

João Vinagre, Alípio Mário Jorge, João Gama

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

Forgetting methods for incremental matrix factorization in recommender systems.

Pawel Matuszyk, João Vinagre, Myra Spiliopoulou, Alípio Mário Jorge, João Gama

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

2014

Fast Incremental Matrix Factorization for Recommendation with Positive-Only Feedback.

João Vinagre, Alípio Mário Jorge, João Gama

Proceedings of the User Modeling, Adaptation, and Personalization, 2014

Monitoring Recommender Systems: A Business Intelligence Approach.

Catarina Félix, Carlos Soares, Alípio Jorge, João Vinagre

Proceedings of the Computational Science and Its Applications - ICCSA 2014 - 14th International Conference, Guimarães, Portugal, June 30, 2014

2013

Combining usage and content in an online recommendation system for music in the Long Tail.

Marcos Aurélio Domingues, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, Mohamed Sordo

Int. J. Multim. Inf. Retr., 2013

2012

Forgetting mechanisms for scalable collaborative filtering.

João Vinagre, Alípio Mário Jorge

J. Braz. Comput. Soc., 2012

Combining usage and content in an online music recommendation system for music in the long-tail.

Marcos Aurélio Domingues, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, Mohamed Sordo

Proceedings of the 21st World Wide Web Conference, 2012