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TÃTULO: Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II
AUTORES: Michael Kamp; Irena Koprinska; Adrien Bibal; Tassadit Bouadi; Benoît Frénay; Luis Galárraga; José Oramas; Linara Adilova; Yamuna Krishnamurthy; Bo Kang; Christine Largeron; Jefrey Lijffijt; Tiphaine Viard; Pascal Welke; Massimiliano Ruocco; Erlend Aune; Claudio Gallicchio; Gregor Schiele; Franz Pernkopf; Michaela Blott; Holger Fröning; Günther Schindler; Riccardo Guidotti; Anna Monreale; Salvatore Rinzivillo; Przemyslaw Biecek; Eirini Ntoutsi; Mykola Pechenizkiy; Bodo Rosenhahn; Christopher L Buckley; Daniela Cialfi; Pablo Lanillos; Maxwell Ramstead; Tim Verbelen; Pedro M Ferreira; Giuseppina Andresini; Donato Malerba; Ibéria Medeiros; Philippe Fournier Viger; Saqib S Nawaz; Sebastián Ventura; Meng Sun; Min Zhou; Valerio Bitetta; Ilaria Bordino; Andrea Ferretti; Francesco Gullo; Giovanni Ponti; Lorenzo Severini; Rita P Ribeiro ; João Gama ; Ricard Gavaldà; Lee A D Cooper; Naghmeh Ghazaleh; Jonas Richiardi; Damian Roqueiro; Diego Saldana Miranda; Konstantinos Sechidis; Guilherme Graça; ...Mais
PUBLICAÇÃO: 2021, FONTE: PKDD/ECML Workshops (2), VOLUME: 1525

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102

TÃTULO: Modelling Voting Behaviour During a General Election Campaign Using Dynamic Bayesian Networks
AUTORES: Costa, Patricio; Nogueira, Ana Rita ; Gama, Joao ;
PUBLICAÇÃO: 2021, FONTE: 20th EPIA Conference on Artificial Intelligence (EPIA) in PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2021), VOLUME: 12981

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103

TÃTULO: Multi-aspect renewable energy forecasting Full Text
AUTORES: Corizzo, R; Ceci, M; Fanaee T, H; Gama, J ;
PUBLICAÇÃO: 2021, FONTE: INFORMATION SCIENCES, VOLUME: 546

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104

TÃTULO: Non-Intrusive Load Monitoring for Household Disaggregated Energy Sensing
AUTORES: Paulos, Jose Pedro ; Fidalgo, Jose Nuno ; Gama, Joao ;
PUBLICAÇÃO: 2021, FONTE: 14th IEEE Madrid PowerTech Conference (IEEE POWERTECH) in 2021 IEEE MADRID POWERTECH

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105

TÃTULO: Predictive maintenance based on anomaly detection using deep learning for air production unit in the railway industry
AUTORES: Davari, Narjes; Veloso, Bruno ; Ribeiro, Rita P. ; Pereira, Pedro Mota; Gama, Joao ;
PUBLICAÇÃO: 2021, FONTE: 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA) in 2021 IEEE 8TH INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (DSAA)

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106

TÃTULO: Spatiotemporal Road Traffic Anomaly Detection: A Tensor-Based Approach
AUTORES: Tisljaric, L; Fernandes, S; Caric, T; Gama, J ;
PUBLICAÇÃO: 2021, FONTE: APPLIED SCIENCES-BASEL, VOLUME: 11, NÚMERO: 24

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107