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ORCIDJoão Vinagre
Person information
- affiliation: INESC TEC, Portugal
- affiliation (Ph.D.): University of Porto, Porto, Portugal
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2020 – today
- 2024
[c29]Paula Raissa Silva, João Vinagre, João Gama:
Federated Online Learning for Heavy Hitter Detection. ECAI 2024: 4689-4695- [c28]Daniela Lopes, Jin-Dong Dong, Pedro Medeiros, Daniel Castro, Diogo Barradas, Bernardo Portela, João Vinagre, Bernardo Ferreira, Nicolas Christin, Nuno Santos:
Flow Correlation Attacks on Tor Onion Service Sessions with Sliding Subset Sum. NDSS 2024 - 2023
- [j10]Paula Raissa Silva
, João Vinagre, João Gama:
Towards federated learning: An overview of methods and applications. WIREs Data. Mining. Knowl. Discov. 13(2) (2023) - [c27]Duarte Melo, Jessica C. Delmoral, João Vinagre:
Mining Causal Links Between TV Sports Content and Real-World Data. EPIA (1) 2023: 263-274 - [c26]Rui Ramos, Lino Oliveira, João Vinagre:
Hybrid SkipAwareRec: A Streaming Music Recommendation System. EPIA (1) 2023: 275-287 - [c25]André Tse, Lino Oliveira, João Vinagre:
Measuring Latency-Accuracy Trade-Offs in Convolutional Neural Networks. EPIA (1) 2023: 323-334 - [c24]Lorenzo Porcaro, Carlos Castillo, Emilia Gómez, João Vinagre:
Fairness and Diversity in Information Access Systems. EWAF 2023 - [c23]João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet:
ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling. RecSys 2023: 1272-1273 - [c22]Paula Raissa Silva, João Vinagre, João Gama:
A DTW Approach for Complex Data A Case Study with Network Data Streams. SAC 2023: 402-409 - [e4]João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet:
Proceedings of the 6th Workshop on Online Recommender Systems and User Modeling co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 19th, 2023. CEUR Workshop Proceedings 3549, CEUR-WS.org 2023 [contents] - [i8]Lorenzo Porcaro, Carlos Castillo, Emilia Gómez, João Vinagre:
Fairness and Diversity in Information Access Systems. CoRR abs/2305.09319 (2023) - [i7]Lorenzo Porcaro, João Vinagre, Pedro Frau, Isabelle Hupont, Emilia Gómez:
Behind Recommender Systems: the Geography of the ACM RecSys Community. CoRR abs/2309.03512 (2023) - 2022
- [j9]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet, Paolo Cremonesi:
Preface to the special issue on dynamic recommender systems and user models. User Model. User Adapt. Interact. 32(4): 503-507 (2022) - [c21]João Parente, Ana Nunes Alonso, Fábio Coelho, João Vinagre, Paulo Bastos:
Flexible Fine-grained Data Access Management for Hyperledger Fabric. BCCA 2022: 76-84 - [c20]Daniela Lopes, Pedro Medeiros, Jin-Dong Dong, Diogo Barradas, Bernardo Portela, João Vinagre, Bernardo Ferreira, Nicolas Christin, Nuno Santos:
Poster: User Sessions on Tor Onion Services: Can Colluding ISPs Deanonymize Them at Scale? CCS 2022: 3399-3401 - [c19]Klismam Pereira, João Vinagre, Ana Nunes Alonso, Fábio Coelho, Melânia Carvalho:
Privacy-Preserving Machine Learning in Life Insurance Risk Prediction. PKDD/ECML Workshops (2) 2022: 44-52 - [c18]João Vinagre, Marie Al-Ghossein, Alípio Mário Jorge, Albert Bifet, Ladislav Peska:
ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling. RecSys 2022: 661-662 - [e3]João Vinagre, Marie Al-Ghossein, Alípio Mário Jorge, Albert Bifet, Ladislav Peska:
Proceedings of the 5th Workshop on Online Recommender Systems and User Modeling co-located with the 16th ACM Conference on Recommender Systems, ORSUM@RecSys 2022, Seattle, WA, USA, September 23rd, 2022. CEUR Workshop Proceedings 3303, CEUR-WS.org 2022 [contents] - [i6]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling - ORSUM 2021. CoRR abs/2201.05156 (2022) - [i5]Paula Raissa Silva, João Vinagre, João Gama:
Federated Anomaly Detection over Distributed Data Streams. CoRR abs/2205.07829 (2022) - 2021
- [j8]Bruno Veloso, João Gama, Benedita Malheiro, João Vinagre:
Hyperparameter self-tuning for data streams. Inf. Fusion 76: 75-86 (2021) - [j7]Anna Gatzioura, João Vinagre, Alípio Mário Jorge, Miquel Sànchez-Marrè:
A Hybrid Recommender System for Improving Automatic Playlist Continuation. IEEE Trans. Knowl. Data Eng. 33(5): 1819-1830 (2021) - [j6]João Vinagre, Alípio Mário Jorge, Conceição Rocha, João Gama:
Statistically Robust Evaluation of Stream-Based Recommender Systems. IEEE Trans. Knowl. Data Eng. 33(7): 2971-2982 (2021) - [c17]Joana Trindade, João Vinagre, Kelwin Fernandes, Nuno Paiva, Alípio Jorge:
Partially Monotonic Learning for Neural Networks. IDA 2021: 12-23 - [c16]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling. RecSys 2021: 792-793 - [i4]Pedro Costa, Vítor Cerqueira, João Vinagre:
AutoFITS: Automatic Feature Engineering for Irregular Time Series. CoRR abs/2112.14806 (2021) - 2020
- [c15]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
ORSUM - Workshop on Online Recommender Systems and User Modeling. RecSys 2020: 619-620 - [e2]João Vinagre, Alípio Mário Jorge, Marie Al-Ghossein, Albert Bifet:
Proceedings of the 3rd Workshop on Online Recommender Systems and User Modeling co-located with the 14th ACM Conference on Recommender Systems (RecSys 2020), Virtual Event, September 25, 2020. CEUR Workshop Proceedings 2715, CEUR-WS.org 2020 [contents]
2010 – 2019
- 2019
- [c14]Miguel Sozinho Ramalho, João Vinagre, Alípio Mário Jorge, Rafaela Bastos:
Incremental Multi-Dimensional Recommender Systems: Co-Factorization vs Tensors. ORSUM@RecSys 2019: 21-35 - [c13]João Vinagre, Alípio Mário Jorge, Albert Bifet, Marie Al-Ghossein:
ORSUM 2019 2nd workshop on online recommender systems and user modeling. RecSys 2019: 562-563 - [e1]João Vinagre, Alípio Mário Jorge, Albert Bifet, Marie Al-Ghossein:
2nd Workshop on Online Recommender Systems and User Modeling, ORSUM@RecSys 2019, 19 September 2019, Copenhagen, Denmark. Proceedings of Machine Learning Research 109, PMLR 2019 [contents] - 2018
- [j5]João Vinagre, Alípio Mário Jorge, João Gama:
Online bagging for recommender systems. Expert Syst. J. Knowl. Eng. 35(4) (2018) - [j4]Pawel Matuszyk, João Vinagre, Myra Spiliopoulou, Alípio Mário Jorge, João Gama:
Forgetting techniques for stream-based matrix factorization in recommender systems. Knowl. Inf. Syst. 55(2): 275-304 (2018) - [c12]João Vinagre, Alípio Mário Jorge, João Gama:
Online Gradient Boosting for Incremental Recommender Systems. DS 2018: 209-223 - [c11]Bruno Veloso, João Gama, Benedita Malheiro, João Vinagre:
Self Hyper-parameter Tuning for Stream Recommendation Algorithms. DMLE/IOTSTREAMING@PKDD/ECML 2018: 91-102 - [c10]Alípio Jorge, João Vinagre, Pawel Matuszyk, Myra Spiliopoulou:
ORSUM Chairs' Welcome & Organization. WWW (Companion Volume) 2018: 1365-1366 - [c9]Susan C. Anyosa, João Vinagre, Alípio M. Jorge:
Incremental Matrix Co-factorization for Recommender Systems with Implicit Feedback. WWW (Companion Volume) 2018: 1413-1418 - 2017
- [c8]João Vinagre, Alípio Mário Jorge, João Gama:
Improving Incremental Recommenders with Online Bagging. EPIA 2017: 597-607 - 2016
- [b1]João Vinagre:
Scalable adaptive collaborative filtering. University of Porto, Portugal, 2016 - [c7]Alípio M. Jorge, João Vinagre, Marcos Aurélio Domingues, João Gama, Carlos Soares, Pawel Matuszyk, Myra Spiliopoulou:
Scalable Online Top-N Recommender Systems. EC-Web 2016: 3-20 - [c6]João Vinagre, Alípio Mário Jorge, João Gama:
Online Bagging for Recommendation with Incremental Matrix Factorization. STREAMEVOLV@ECML-PKDD 2016 - [i3]João Vinagre, Alípio Mário Jorge, João Gama:
Online bagging for recommendation with incremental matrix factorization. CoRR abs/1611.00558 (2016) - [i2]Nuno Moniz, Luís Torgo, João Vinagre:
Data-Driven Relevance Judgments for Ranking Evaluation. CoRR abs/1612.06136 (2016) - 2015
- [j3]João Vinagre, Alípio Mário Jorge, João Gama:
An overview on the exploitation of time in collaborative filtering. WIREs Data Mining Knowl. Discov. 5(5): 195-215 (2015) - [c5]Pawel Matuszyk, João Vinagre, Myra Spiliopoulou, Alípio Mário Jorge, João Gama:
Forgetting methods for incremental matrix factorization in recommender systems. SAC 2015: 947-953 - [c4]João Vinagre, Alípio Mário Jorge, João Gama:
Collaborative filtering with recency-based negative feedback. SAC 2015: 963-965 - [i1]João Vinagre, Alípio Mário Jorge, João Gama:
Evaluation of recommender systems in streaming environments. CoRR abs/1504.08175 (2015) - 2014
- [c3]Catarina Félix, Carlos Soares, Alípio Jorge, João Vinagre:
Monitoring Recommender Systems: A Business Intelligence Approach. ICCSA (6) 2014: 277-288 - [c2]João Vinagre, Alípio Mário Jorge, João Gama:
Fast Incremental Matrix Factorization for Recommendation with Positive-Only Feedback. UMAP 2014: 459-470 - 2013
- [j2]Marcos Aurélio Domingues, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, Mohamed Sordo:
Combining usage and content in an online recommendation system for music in the Long Tail. Int. J. Multim. Inf. Retr. 2(1): 3-13 (2013) - 2012
- [j1]João Vinagre, Alípio Mário Jorge:
Forgetting mechanisms for scalable collaborative filtering. J. Braz. Comput. Soc. 18(4): 271-282 (2012) - [c1]Marcos Aurélio Domingues, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, Mohamed Sordo:
Combining usage and content in an online music recommendation system for music in the long-tail. WWW (Companion Volume) 2012: 925-930
Coauthor Index
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