31
TÍTULO: Forgetting techniques for stream-based matrix factorization in recommender systems  Full Text
AUTORES: Pawel Matuszyk; Joao Vinagre ; Myra Spiliopoulou; Alipio Mario Jorge ; Joao Gama ;
PUBLICAÇÃO: 2018, FONTE: KNOWLEDGE AND INFORMATION SYSTEMS, VOLUME: 55, NÚMERO: 2
INDEXADO EM: Scopus WOS DBLP CrossRef: 17
32
TÍTULO: Incremental Matrix Co-factorization for Recommender Systems with Implicit Feedback
AUTORES: Susan C Anyosa ; João Vinagre ; Alípio M Jorge ;
PUBLICAÇÃO: 2018, FONTE: 27th International World Wide Web, WWW 2018 in Companion of the The Web Conference 2018 on The Web Conference 2018, WWW 2018, Lyon , France, April 23-27, 2018
INDEXADO EM: Scopus DBLP CrossRef: 13
33
TÍTULO: Online bagging for recommender systems  Full Text
AUTORES: Joao Vinagre ; Alipio Mario Jorge ; Joao Gama ;
PUBLICAÇÃO: 2018, FONTE: EXPERT SYSTEMS, VOLUME: 35, NÚMERO: 4
INDEXADO EM: Scopus WOS DBLP CrossRef: 9
34
TÍTULO: Online Gradient Boosting for Incremental Recommender Systems
AUTORES: João Vinagre ; Alípio Mário Jorge ; João Gama ;
PUBLICAÇÃO: 2018, FONTE: 21st International Conference on Discovery Science, DS 2018 in Discovery Science - 21st International Conference, DS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings, VOLUME: 11198
INDEXADO EM: Scopus DBLP CrossRef: 1
35
TÍTULO: ORSUM Chairs' Welcome & Organization
AUTORES: Alípio Jorge ; João Vinagre ; Pawel Matuszyk; Myra Spiliopoulou;
PUBLICAÇÃO: 2018, FONTE: Companion of the The Web Conference 2018 on The Web Conference 2018, WWW 2018, Lyon , France, April 23-27, 2018
INDEXADO EM: DBLP CrossRef: 4
36
TÍTULO: Self Hyper-parameter Tuning for Stream Recommendation Algorithms
AUTORES: Bruno Veloso ; João Gama ; Benedita Malheiro ; João Vinagre ;
PUBLICAÇÃO: 2018, FONTE: Workshops Nemesis, UrbReas, SoGood, IWAISe, and Green Data Mining, held at the 18th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018 in ECML PKDD 2018 Workshops - DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers, VOLUME: 967
INDEXADO EM: Scopus DBLP CrossRef: 7 Unpaywall Handle
NO MEU: ORCID | DBLP
37
TÍTULO: Improving Incremental Recommenders with Online Bagging
AUTORES: Joao Vinagre ; Alipio Mario Jorge ; Joao Gama ;
PUBLICAÇÃO: 2017, FONTE: 18th EPIA Conference on Artificial Intelligence (EPIA) in PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2017), VOLUME: 10423
INDEXADO EM: Scopus WOS DBLP CrossRef
38
TÍTULO: Scalable Online Top-N Recommender Systems
AUTORES: Alipio M Jorge ; Joao Vinagre ; Marcos Domingues; Joao Gama ; Carlos Soares ; Pawel Matuszyk; Myra Spiliopoulou;
PUBLICAÇÃO: 2017, FONTE: 17th International Conference on E-Commerce and Web Technologies (EC-Web) in E-COMMERCE AND WEB TECHNOLOGIES, EC-WEB 2016, VOLUME: 278
INDEXADO EM: Scopus WOS DBLP CrossRef: 6
39
TÍTULO: Data-Driven Relevance Judgments for Ranking Evaluation PDF
AUTORES: Nuno Moniz ; Luís Torgo ; João Vinagre ;
PUBLICAÇÃO: 2016, FONTE: CoRR, VOLUME: abs/1612.06136
INDEXADO EM: DBLP arXiv
NO MEU: ORCID | DBLP
40
TÍTULO: Online Bagging for Recommendation with Incremental Matrix Factorization PDF
AUTORES: João Vinagre ; Alípio Mário Jorge ; João Gama ;
PUBLICAÇÃO: 2016, FONTE: 2016 Workshop on Large-Scale Learning from Data Streams in Evolving Environments, STREAMEVOLV 2016 in 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), Riva del Garda, Italy, September 23, 2016., VOLUME: 2069
INDEXADO EM: Scopus DBLP
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