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ORCIDJoão Gama 0001
João Manuel Portela da Gama
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- affiliation: University of Porto, Laboratory of Artificial Intelligence and Decision Support (LIAAD)
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2020 – today
- 2021
[j111]Roberto Corizzo
, Michelangelo Ceci, Hadi Fanaee-T, João Gama:
Multi-aspect renewable energy forecasting. Inf. Sci. 546: 701-722 (2021)- 2020
- [j110]Albert Bifet, João Gama:
IoT data stream analytics. Ann. des Télécommunications 75(9-10): 491-492 (2020) - [j109]Thiago Andrade, Brais Cancela, João Gama:
Discovering locations and habits from human mobility data. Ann. des Télécommunications 75(9-10): 505-521 (2020) - [j108]Shazia Tabassum, Muhammad Ajmal Azad, João Gama:
Profiling high leverage points for detecting anomalous users in telecom data networks. Ann. des Télécommunications 75(9-10): 573-581 (2020) - [j107]Bruno Veloso, Shazia Tabassum, Carlos Martins, Raphael Espanha, Raul Azevedo, João Gama:
Interconnect bypass fraud detection: a case study. Ann. des Télécommunications 75(9-10): 583-596 (2020) - [j106]Felipe Azevedo Pinage, Eulanda Miranda dos Santos, João Gama:
A drift detection method based on dynamic classifier selection. Data Min. Knowl. Discov. 34(1): 50-74 (2020) - [j105]Sofia da Silva Fernandes, Hadi Fanaee-T, João Gama:
NORMO: A new method for estimating the number of components in CP tensor decomposition. Eng. Appl. Artif. Intell. 96: 103926 (2020) - [j104]Thiago Andrade, Brais Cancela, João Gama:
From mobility data to habits and common pathways. Expert Syst. J. Knowl. Eng. 37(6) (2020) - [j103]Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Gama:
A scalable saliency-based feature selection method with instance-level information. Knowl. Based Syst. 192: 105326 (2020) - [j102]Shazia Tabassum, Bruno Veloso, João Gama:
On fast and scalable recurring link's prediction in evolving multi-graph streams. Netw. Sci. 8(S1): S65-S81 (2020) - [j101]Amal Saadallah, Luís Moreira-Matias, Ricardo Sousa, Jihed Khiari, Erik Jenelius, João Gama:
BRIGHT - Drift-Aware Demand Predictions for Taxi Networks. IEEE Trans. Knowl. Data Eng. 32(2): 234-245 (2020) - [c187]Saulo Ruiz, Pedro Gomes, Luís Rodrigues, João Gama:
Assembled Feature Selection for Credit Scoring in Microfinance with Non-traditional Features. DS 2020: 207-216 - [c186]Leo Tisljaric, Sofia da Silva Fernandes, Tonci Caric, João Gama:
Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method. DS 2020: 674-688 - [c185]Paulo Paraíso, Pedro Gomes, Saulo Ruiz, Luís Rodrigues, João Gama:
Using Network Features for Credit Scoring in MicroFinance: Extended Abstract. DSAA 2020: 783-784 - [c184]Ana Rita Nogueira, João Gama, Carlos Abreu Ferreira:
Improving Prediction with Causal Probabilistic Variables. IDA 2020: 379-390 - [c183]Bruno Veloso, Benedita Malheiro, Juan-Carlos Burguillo, João Gama:
Impact of Trust and Reputation Based Brokerage on the CloudAnchor Platform. PAAMS 2020: 303-314 - [c182]Bruno Veloso, Carlos Martins, Raphael Espanha, Raul Azevedo, João Gama:
Fraud detection using heavy hitters: a case study. SAC 2020: 482-489 - [e21]Albert Bifet, Michele Berlingerio, João Gama, Jesse Read, Ana Rita Nogueira:
Proceedings of the 8th International Workshop on Big Data, IoT Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications co-located with 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska, August 4-8, 2019. CEUR Workshop Proceedings 2579, CEUR-WS.org 2020 [contents] - [i15]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. CoRR abs/2004.05785 (2020) - [i14]Ricardo Cerri, Joel David Costa Júnior, Elaine Ribeiro de Faria Paiva, João Manuel Portela da Gama:
Multi-label Stream Classification with Self-Organizing Maps. CoRR abs/2004.09397 (2020) - [i13]Sónia Teixeira, João Gama, Pedro Amorim, Gonçalo Figueira:
Trustability in Algorithmic Systems Based on Artificial Intelligence in the Public and Private Sectors. ERCIM News 2020(122) (2020)
2010 – 2019
- 2019
- [j100]Guoliang Li, João Gama, Jun Yang:
Special Issue of DASFAA 2019. Data Sci. Eng. 4(3): 177-178 (2019) - [j99]Eduarda Portela, Rita P. Ribeiro, João Gama:
The search of conditional outliers. Intell. Data Anal. 23(1): 23-39 (2019) - [j98]Saulo Ruiz, Pedro Gomes, Luís Rodrigues, João Gama:
Credit scoring for microfinance using behavioral data in emerging markets. Intell. Data Anal. 23(6): 1355-1378 (2019) - [j97]Jakub Zgraja, Richard Hugh Moulton, João Gama, Andrzej Kasprzak, Michal Wozniak:
Adapting ClusTree for more challenging data stream environments. J. Intell. Fuzzy Syst. 37(6): 7679-7688 (2019) - [j96]Carlos Abreu Ferreira, João Gama, Vítor Santos Costa:
Contrasting logical sequences in multi-relational learning. Prog. Artif. Intell. 8(4): 487-503 (2019) - [j95]Wesllen Sousa Lima, Eduardo Souto, Khalil El-Khatib, Roozbeh Jalali, João Gama:
Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview. Sensors 19(14): 3213 (2019) - [j94]Heitor Murilo Gomes, Jesse Read, Albert Bifet, Jean Paul Barddal, João Gama:
Machine learning for streaming data: state of the art, challenges, and opportunities. SIGKDD Explor. 21(2): 6-22 (2019) - [j93]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. IEEE Trans. Knowl. Data Eng. 31(12): 2346-2363 (2019) - [c181]Joel D. Costa Júnior, Elaine Ribeiro de Faria, Jonathan de Andrade Silva, João Gama, Ricardo Cerri:
Novelty Detection for Multi-Label Stream Classification. BRACIS 2019: 144-149 - [c180]Mário Cordeiro, Rui Portocarrero Sarmento, Pavel Brazdil, Masahiro Kimura, João Gama:
Identifying, Ranking and Tracking Community Leaders in Evolving Social Networks. COMPLEX NETWORKS (1) 2019: 198-210 - [c179]Andreia Conceição, João Gama:
Main Factors Driving the Open Rate of Email Marketing Campaigns. DS 2019: 145-154 - [c178]Sofia da Silva Fernandes, Hadi Fanaee-T, João Gama:
Evolving Social Networks Analysis via Tensor Decompositions: From Global Event Detection Towards Local Pattern Discovery and Specification. DS 2019: 385-395 - [c177]Thiago Andrade, Brais Cancela, João Gama:
Discovering Common Pathways Across Users' Habits in Mobility Data. EPIA (2) 2019: 410-421 - [c176]Douglas Castilho, João Gama, Leandro Resende Mundim, André C. P. L. F. de Carvalho:
Improving Portfolio Optimization Using Weighted Link Prediction in Dynamic Stock Networks. ICCS (3) 2019: 340-353 - [c175]Amal Saadallah, Luís Moreira-Matias, Ricardo Sousa, Jihed Khiari, Erik Jenelius, João Gama:
BRIGHT - Drift-Aware Demand Predictions for Taxi Networks (Extended Abstract). ICDE 2019: 2145-2146 - [c174]Joel D. Costa Júnior, Elaine R. Faria, Jonathan de Andrade Silva, João Gama, Ricardo Cerri:
Pruned Sets for Multi-Label Stream Classification without True Labels. IJCNN 2019: 1-8 - [c173]Bruno Veloso, Carlos Martins, Raphael Espanha, Raul Azevedo, João Gama:
Detecting Bursts of Activity in Telecommunications. BigMine@KDD 2019 - [c172]Ehsan Aminian, Rita P. Ribeiro, João Gama:
A Study on Imbalanced Data Streams. PKDD/ECML Workshops (2) 2019: 380-389 - [c171]Thiago Andrade, Brais Cancela, João Gama:
Mining Human Mobility Data to Discover Locations and Habits. PKDD/ECML Workshops (2) 2019: 390-401 - [c170]Guilherme Londres, Nuno Filipe, João Gama:
Optimizing Waste Collection: A Data Mining Approach. PKDD/ECML Workshops (1) 2019: 570-578 - [e20]Guoliang Li, Jun Yang, João Gama, Juggapong Natwichai, Yongxin Tong:
Database Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22-25, 2019, Proceedings, Part I. Lecture Notes in Computer Science 11446, Springer 2019, ISBN 978-3-030-18575-6 [contents] - [e19]Guoliang Li, Jun Yang, João Gama, Juggapong Natwichai, Yongxin Tong:
Database Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22-25, 2019, Proceedings, Part II. Lecture Notes in Computer Science 11447, Springer 2019, ISBN 978-3-030-18578-7 [contents] - [e18]Guoliang Li, Jun Yang, João Gama, Juggapong Natwichai, Yongxin Tong:
Database Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22-25, 2019, Proceedings, Part III, and DASFAA 2019 International Workshops: BDMS, BDQM, and GDMA, Chiang Mai, Thailand, April 22-25, 2019, Proceedings. Lecture Notes in Computer Science 11448, Springer 2019, ISBN 978-3-030-18589-3 [contents] - [e17]Anna Monreale, Carlos Alzate, Michael Kamp, Yamuna Krishnamurthy, Daniel Paurat, Moamar Sayed Mouchaweh, Albert Bifet, João Gama, Rita P. Ribeiro:
ECML PKDD 2018 Workshops - DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers. Communications in Computer and Information Science 967, Springer 2019, ISBN 978-3-030-14879-9 [contents] - [i12]Thiago Andrade, João Gama:
Identifying Points of Interest and Similar Individuals from Raw GPS Data. CoRR abs/1904.09357 (2019) - [i11]Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Gama:
A scalable saliency-based Feature selection method with instance level information. CoRR abs/1904.13127 (2019) - [i10]Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Contextual One-Class Classification in Data Streams. CoRR abs/1907.04233 (2019) - [i9]Thiago Andrade, Brais Cancela, João Gama:
Mining Human Mobility Data to Discover Locations and Habits. CoRR abs/1909.11406 (2019) - 2018
- [j92]Sofia da Silva Fernandes, Hadi Fanaee-T, João Gama:
Dynamic graph summarization: a tensor decomposition approach. Data Min. Knowl. Discov. 32(5): 1397-1420 (2018) - [j91]João Vinagre, Alípio Mário Jorge, João Gama:
Online bagging for recommender systems. Expert Syst. J. Knowl. Eng. 35(4) (2018) - [j90]Ana Rita Nogueira, Carlos Abreu Ferreira, João Gama:
Improving acute kidney injury detection with conditional probabilities. Intell. Data Anal. 22(6): 1355-1374 (2018) - [j89]Pedro Pereira Rodrigues, João Araújo, João Gama, Luís M. B. Lopes:
A local algorithm to approximate the global clustering of streams generated in ubiquitous sensor networks. Int. J. Distributed Sens. Networks 14(10) (2018) - [j88]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) - [j87]Juan Gabriel Colonna, João Gama, Eduardo Freire Nakamura:
A comparison of hierarchical multi-output recognition approaches for anuran classification. Mach. Learn. 107(11): 1651-1671 (2018) - [j86]Fabiola S. F. Pereira, João Gama, Sandra de Amo, Gina M. B. Oliveira:
On analyzing user preference dynamics with temporal social networks. Mach. Learn. 107(11): 1745-1773 (2018) - [j85]Ricardo Sousa, João Gama:
Multi-label classification from high-speed data streams with adaptive model rules and random rules. Prog. Artif. Intell. 7(3): 177-187 (2018) - [j84]Luís Moreira-Matias, João Manuel Portela da Gama, Cristina Olaverri-Monreal, Rahul Nair, Roberto Trasarti:
Guest Editorial Special Issue on Knowledge Discovery From Mobility Data for Intelligent Transportation Systems. IEEE Trans. Intell. Transp. Syst. 19(11): 3626-3629 (2018) - [j83]Shazia Tabassum, Fabiola S. F. Pereira, Sofia da Silva Fernandes, João Gama:
Cover Image, Volume 8, Issue 5. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 8(5) (2018) - [j82]Shazia Tabassum, Fabiola S. F. Pereira, Sofia da Silva Fernandes, João Gama:
Social network analysis: An overview. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 8(5) (2018) - [c169]Carlos Fernandes, Luis Fonseca, Flora Ferreira, Miguel F. Gago, Luís Costa, Nuno Sousa, Carlos Abreu Ferreira, João Gama, Wolfram Erlhagen, Estela Bicho:
Artificial Neural Networks Classification of Patients with Parkinsonism based on Gait. BIBM 2018: 2024-2030 - [c168]Shazia Tabassum, João Gama:
Biased Dynamic Sampling for Temporal Network Streams. COMPLEX NETWORKS (1) 2018: 512-523 - [c167]João Vinagre, Alípio Mário Jorge, João Gama:
Online Gradient Boosting for Incremental Recommender Systems. DS 2018: 209-223 - [c166]Bruno Veloso, João Gama, Benedita Malheiro:
Self Hyper-Parameter Tuning for Data Streams. DS 2018: 241-255 - [c165]Rui Portocarrero Sarmento, Mário Cordeiro, Pavel Brazdil, João Gama:
Incremental TextRank - Automatic Keyword Extraction for Text Streams. ICEIS (1) 2018: 363-370 - [c164]Jakub Zgraja, João Gama, Michal Wozniak:
Active Learning by Clustering for Drifted Data Stream Classification. DMLE/IOTSTREAMING@PKDD/ECML 2018: 80-90 - [c163]Bruno Veloso, João Gama, Benedita Malheiro, João Vinagre:
Self Hyper-parameter Tuning for Stream Recommendation Algorithms. DMLE/IOTSTREAMING@PKDD/ECML 2018: 91-102 - [c162]Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Clustering in the Presence of Concept Drift. ECML/PKDD (1) 2018: 339-355 - [c161]Ricardo Sousa, João Gama:
Co-training study for online regression. SAC 2018: 529-531 - [c160]Bruno Veloso, Benedita Malheiro, Juan-Carlos Burguillo, Jeremy D. Foss, João Gama:
Personalised Dynamic Viewer Profiling for Streamed Data. WorldCIST (2) 2018: 501-510 - [e16]M. Arif Wani, Mehmed M. Kantardzic, Moamar Sayed Mouchaweh, João Gama, Edwin Lughofer:
17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018, Orlando, FL, USA, December 17-20, 2018. IEEE 2018, ISBN 978-1-5386-6805-4 [contents] - [e15]Moamar Sayed Mouchaweh, Hamid Bouchachia, João Gama, Rita Paula Ribeiro:
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. CEUR Workshop Proceedings 2069, CEUR-WS.org 2018 [contents] - [i8]Mário Cordeiro, Rui Portocarrero Sarmento, Pavel Brazdil, João Gama:
Dynamic Laplace: Efficient Centrality Measure for Weighted or Unweighted Evolving Networks. CoRR abs/1808.02960 (2018) - 2017
- [j81]Jonathan de Andrade Silva, Eduardo Raul Hruschka, João Gama:
An evolutionary algorithm for clustering data streams with a variable number of clusters. Expert Syst. Appl. 67: 228-238 (2017) - [j80]Raquel Sebastião, João Gama, Teresa Mendonça:
Fading histograms in detecting distribution and concept changes. Int. J. Data Sci. Anal. 3(3): 183-212 (2017) - [j79]Bartosz Krawczyk, Leandro L. Minku, João Gama, Jerzy Stefanowski, Michal Wozniak:
Ensemble learning for data stream analysis: A survey. Inf. Fusion 37: 132-156 (2017) - [j78]Douglas de O. Cardoso, João Gama, Felipe M. G. França:
Weightless neural networks for open set recognition. Mach. Learn. 106(9-10): 1547-1567 (2017) - [j77]João Gama, Eugénio C. Oliveira, Henrique Lopes Cardoso:
Computational Models for Social and Technical Interactions. New Gener. Comput. 35(4): 307-310 (2017) - [j76]Douglas de O. Cardoso, Felipe M. G. França, João Gama:
WCDS: A Two-Phase Weightless Neural System for Data Stream Clustering. New Gener. Comput. 35(4): 391-416 (2017) - [c159]Rui Portocarrero Sarmento, Mário Cordeiro, Pavel Brazdil, João Gama:
Efficient Incremental Laplace Centrality Algorithm for Dynamic Networks. COMPLEX NETWORKS 2017: 341-352 - [c158]Sofia da Silva Fernandes, Hadi Fanaee Tork, João Manuel Portela da Gama:
The Initialization and Parameter Setting Problem in Tensor Decomposition-Based Link Prediction. DSAA 2017: 99-108 - [c157]Hamid Eslami Nosratabadi, Hadi Fanaee-T, João Gama:
Mobility Mining Using Nonnegative Tensor Factorization. EPIA 2017: 321-330 - [c156]Saulo Ruiz, Pedro Gomes, Luís Rodrigues, João Gama:
Credit Scoring in Microfinance Using Non-traditional Data. EPIA 2017: 447-458 - [c155]João Vinagre, Alípio Mário Jorge, João Gama:
Improving Incremental Recommenders with Online Bagging. EPIA 2017: 597-607 - [c154]Ana Rita Nogueira, Carlos Abreu Ferreira, João Gama:
Acute Kidney Injury Detection: An Alarm System to Improve Early Treatment. ISMIS 2017: 57-63 - [c153]Ricardo Sousa, João Gama:
Co-training Semi-supervised Learning for Single-Target Regression in Data Streams Using AMRules. ISMIS 2017: 499-508 - [c152]Eduarda Portela, Rita P. Ribeiro, João Gama:
Outliers and the Simpson's Paradox. MICAI (1) 2017: 267-278 - [c151]Ricardo Sousa, João Gama:
Comparison Between Co-training and Self-training for Single-target Regression in Data Streams using AMRules. IOTSTREAMING@PKDD/ECML 2017 - [c150]João Duarte, João Gama:
Feature ranking in hoeffding algorithms for regression. SAC 2017: 836-841 - [e14]Eugénio C. Oliveira, João Gama, Zita A. Vale, Henrique Lopes Cardoso:
Progress in Artificial Intelligence - 18th EPIA Conference on Artificial Intelligence, EPIA 2017, Porto, Portugal, September 5-8, 2017, Proceedings. Lecture Notes in Computer Science 10423, Springer 2017, ISBN 978-3-319-65339-6 [contents] - [e13]Ricard Gavaldà, Indre Zliobaite, João Gama:
Proceedings of the First Workshop on Data Science for Social Good co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Dicovery in Databases, SoGood@ECML-PKDD 2016, Riva del Garda, Italy, September 19, 2016. CEUR Workshop Proceedings 1831, CEUR-WS.org 2017 [contents] - [e12]Moamar Sayed Mouchaweh, Albert Bifet, Hamid Bouchachia, João Gama, Rita Paula Ribeiro:
Proceedings of the Workshop on IoT Large Scale Learning from Data Streams co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18-22, 2017. CEUR Workshop Proceedings 1958, CEUR-WS.org 2017 [contents] - [r4]João Gama:
Clustering from Data Streams. Encyclopedia of Machine Learning and Data Mining 2017: 226-231 - 2016
- [j75]Elaine R. Faria, Isabel J. C. R. Gonçalves, André C. P. L. F. de Carvalho, João Gama:
Novelty detection in data streams. Artif. Intell. Rev. 45(2): 235-269 (2016) - [j74]Luís Moreira-Matias, Oded Cats, João Gama, João Mendes-Moreira, Jorge Freire de Sousa:
An online learning approach to eliminate Bus Bunching in real-time. Appl. Soft Comput. 47: 460-482 (2016) - [j73]F. E. Correa, Márcia D. B. Oliveira, João Gama, Pedro Luiz Pizzigatti Corrêa, J. Rady:
Analyzing the behavior dynamics of grain price indexes using Tucker tensor decomposition and spatio-temporal trajectories. Comput. Electron. Agric. 120: 72-78 (2016) - [j72]Elaine Ribeiro de Faria, André Carlos Ponce de Leon Ferreira de Carvalho, João Gama:
MINAS: multiclass learning algorithm for novelty detection in data streams. Data Min. Knowl. Discov. 30(3): 640-680 (2016) - [j71]Luís Moreira-Matias, João Gama, Michel Ferreira, João Mendes-Moreira, Luís Damas:
Time-evolving O-D matrix estimation using high-speed GPS data streams. Expert Syst. Appl. 44: 275-288 (2016) - [j70]Maria Rocha Sousa, João Gama, Elísio Brandão:
A new dynamic modeling framework for credit risk assessment. Expert Syst. Appl. 45: 341-351 (2016) - [j69]Hanen Borchani, Pedro Larrañaga, João Gama, Concha Bielza:
Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers. Intell. Data Anal. 20(2): 257-280 (2016) - [j68]Hadi Fanaee-T, João Gama:
Event detection from traffic tensors: A hybrid model. Neurocomputing 203: 22-33 (2016) - [j67]Hadi Fanaee-T, João Gama:
Tensor-based anomaly detection: An interdisciplinary survey. Knowl. Based Syst. 98: 130-147 (2016) - [j66]Rita P. Ribeiro, Pedro Mota Pereira, João Gama:
Sequential anomalies: a study in the Railway Industry. Mach. Learn. 105(1): 127-153 (2016) - [j65]Mário Cordeiro, Rui Sarmento, João Gama:
Dynamic community detection in evolving networks using locality modularity optimization. Soc. Netw. Anal. Min. 6(1): 15:1-15:20 (2016) - [j64]João Duarte, João Gama, Albert Bifet:
Adaptive Model Rules From High-Speed Data Streams. ACM Trans. Knowl. Discov. Data 10(3): 30:1-30:22 (2016) - [j63]Felipe Azevedo Pinage, Eulanda Miranda dos Santos, João Manuel Portela da Gama:
Classification systems in dynamic environments: an overview. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 6(5): 156-166 (2016) - [c149]Mário Cordeiro, João Gama:
Online Social Networks Event Detection: A Survey. Solving Large Scale Learning Tasks 2016: 1-41 - [c148]Juan Gabriel Colonna, Tanel Peet, Carlos Abreu Ferreira, Alípio Mário Jorge, Elsa Ferreira Gomes, João Gama:
Automatic Classification of Anuran Sounds Using Convolutional Neural Networks. C3S2E 2016: 73-78 - [c147]Juan Gabriel Colonna, João Gama, Eduardo Freire Nakamura:
How to Correctly Evaluate an Automatic Bioacoustics Classification Method. CAEPIA 2016: 37-47 - [c146]Ricardo Sousa, João Gama:
Online Multi-label Classification with Adaptive Model Rules. CAEPIA 2016: 58-67 - [c145]Juan Gabriel Colonna, João Gama, Eduardo Freire Nakamura:
Recognizing Family, Genus, and Species of Anuran Using a Hierarchical Classification Approach. DS 2016: 198-212 - [c144]Shazia Tabassum, João Gama:
Evolution Analysis of Call Ego-Networks. DS 2016: 213-225 - [c143]Fabiola S. F. Pereira, Sandra de Amo, João Gama:
On Using Temporal Networks to Analyze User Preferences Dynamics. DS 2016: 408-423 - [c142]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 - [c141]Rita P. Ribeiro, Ricardo Oliveira, João Gama:
Detection of Fraud Symptoms in the Retail Industry. IBERAMIA 2016: 189-200 - [c140]Ricardo Sousa, João Gama:
Online Semi-supervised Learning for Multi-target Regression in Data Streams Using AMRules. IDA 2016: 123-133 - [c139]