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2020 – today
- 2024
[j41]Joel Ribeiro
, Tânia Fontes, Carlos Soares, José Luís Borges:
Multidimensional subgroup discovery on event logs. Expert Syst. Appl. 246: 123205 (2024)- [j40]Hajar Baghcheband, Carlos Soares, Luís Paulo Reis:
Machine Learning Data Market Based on Multiagent Systems. IEEE Internet Comput. 28(4): 7-13 (2024) - [j39]Vítor Cerqueira, Nuno Moniz, Carlos Soares:
VEST: automatic feature engineering for forecasting. Mach. Learn. 113(7): 4523-4545 (2024) - [j38]Yassine Baghoussi, Carlos Soares, João Mendes-Moreira:
Corrector LSTM: built-in training data correction for improved time-series forecasting. Neural Comput. Appl. 36(26): 16213-16231 (2024) - [j37]Carlos Soares, Stephan G. Grimmelikhuijsen, Albert Meijer:
Screen-level bureaucrats in the age of algorithms: An ethnographic study of algorithmically supported public service workers in the Netherlands Police. Inf. Polity 29(3): 277-292 (2024) - [c128]Rodrigo Tuna, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira:
Kernel Corrector LSTM. IDA (2) 2024: 3-14 - [c127]Hajar Baghcheband, Carlos Soares, Luís Paulo Reis:
Shapley-Based Data Valuation Method for the Machine Learning Data Markets (MLDM). ISMIS 2024: 170-177 - [c126]Luis Roque, Carlos Soares, Luís Torgo:
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. KDD 2024: 2491-2499 - [c125]Lucas Martins, João Bravo, Ana Sofia Gomes, Carlos Soares, Pedro Bizarro:
RIFF: Inducing Rules for Fraud Detection from Decision Trees. RuleML+RR 2024: 50-58 - [c124]Thales R. S. Lopes, Guilherme Freire Roberto, Carlos Soares, Thaína A. A. Tosta, Adriano Barbosa-Silva, Adriano M. Loyola, Sérgio V. Cardoso, Paulo Rogério de Faria, Marcelo Zanchetta do Nascimento, Leandro Alves Neves:
Association of Grad-CAM, LIME and Multidimensional Fractal Techniques for the Classification of H&E Images. VISIGRAPP (2): VISAPP 2024: 441-447 - [i39]Vítor Cerqueira, Moisés Rocha dos Santos, Yassine Baghoussi, Carlos Soares:
On-the-fly Data Augmentation for Forecasting with Deep Learning. CoRR abs/2404.16918 (2024) - [i38]Rodrigo Tuna, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira:
Kernel Corrector LSTM. CoRR abs/2404.18273 (2024) - [i37]Vítor Cerqueira, Nuno Moniz, Ricardo Inácio, Carlos Soares:
Time Series Data Augmentation as an Imbalanced Learning Problem. CoRR abs/2404.18537 (2024) - [i36]José Leites, Vítor Cerqueira, Carlos Soares:
Lag Selection for Univariate Time Series Forecasting using Deep Learning: An Empirical Study. CoRR abs/2405.11237 (2024) - [i35]Vítor Cerqueira, Luis Roque, Carlos Soares:
Forecasting with Deep Learning: Beyond Average of Average of Average Performance. CoRR abs/2406.16590 (2024) - [i34]Ricardo Inácio, Vítor Cerqueira, Marília Barandas, Carlos Soares:
Meta-learning and Data Augmentation for Stress Testing Forecasting Models. CoRR abs/2406.17008 (2024) - [i33]Luis Roque, Carlos Soares, Luís Torgo:
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. CoRR abs/2408.03399 (2024) - [i32]Inês Gomes, Luís F. Teixeira, Jan N. van Rijn, Carlos Soares, André Restivo, Luís Cunha, Moisés Santos:
Finding Patterns in Ambiguity: Interpretable Stress Testing in the Decision~Boundary. CoRR abs/2408.06302 (2024) - [i31]João Lucas Martins, João Bravo, Ana Sofia Gomes, Carlos Soares, Pedro Bizarro:
RIFF: Inducing Rules for Fraud Detection from Decision Trees. CoRR abs/2408.12989 (2024) - 2023
- [j36]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes. Mach. Learn. 112(11): 4409-4430 (2023) - [j35]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Model Selection for Time Series Forecasting An Empirical Analysis of Multiple Estimators. Neural Process. Lett. 55(7): 10073-10091 (2023) - [c123]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
Symbolic Data Analysis to Improve Completeness of Model Combination Methods. AI (2) 2023: 107-119 - [c122]Inês Oliveira e Silva, Carlos Soares, Inês Sousa, Rayid Ghani:
Systematic Analysis of the Impact of Label Noise Correction on ML Fairness. AI (2) 2023: 173-184 - [c121]Guilherme Freire Roberto, Danilo Cesar Pereira, Alessandro Santana Martins, Thaína A. A. Tosta, Carlos Soares, Alessandra Lumini, Guilherme Botazzo Rozendo, Leandro Alves Neves, Marcelo Zanchetta do Nascimento:
Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification. CIARP 2023: 163-177 - [c120]Fernando Freitas, Pavel Brazdil, Carlos Soares:
Exploring the Reduction of Configuration Spaces of Workflows. DS 2023: 33-47 - [c119]Hajar Baghcheband, Carlos Soares, Luís Paulo Reis:
Machine Learning Data Markets: Evaluating the Impact of Data Exchange on the Agent Learning Performance. EPIA (1) 2023: 337-348 - [c118]Luís Cunha, Carlos Soares, André Restivo, Luís F. Teixeira:
GASTeN: Generative Adversarial Stress Test Networks. IDA 2023: 91-102 - [i30]Inês Oliveira e Silva, Carlos Soares, Inês Sousa, Rayid Ghani:
Systematic analysis of the impact of label noise correction on ML Fairness. CoRR abs/2306.15994 (2023) - [i29]Moisés Rocha dos Santos, André C. P. L. F. de Carvalho, Carlos Soares:
tsMorph: generation of semi-synthetic time series to understand algorithm performance. CoRR abs/2312.01344 (2023) - 2022
- [j34]Miriam Seoane Santos, Pedro Henriques Abreu, Nathalie Japkowicz, Alberto Fernández, Carlos Soares, Szymon Wilk, João A. M. Santos:
On the joint-effect of class imbalance and overlap: a critical review. Artif. Intell. Rev. 55(8): 6207-6275 (2022) - [j33]Vítor Cerqueira, Luís Torgo, Carlos Soares:
A case study comparing machine learning with statistical methods for time series forecasting: size matters. J. Intell. Inf. Syst. 59(2): 415-433 (2022) - [j32]Adriano Rivolli, Luís Paulo F. Garcia, Carlos Soares, Joaquin Vanschoren, André C. P. L. F. de Carvalho:
Meta-features for meta-learning. Knowl. Based Syst. 240: 108101 (2022) - [c117]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
Density Estimation in High-Dimensional Spaces: A Multivariate Histogram Approach. ADMA (2) 2022: 266-278 - [c116]Dusan Hetlerovic, Lubos Popelínský, Pavel Bradi, Carlos Soares, Fernando Freitas:
On Usefulness of Outlier Elimination in Classification Tasks: Extended Abstract. Meta-Knowledge Transfer @ ECML/PKDD 2022: 78-80 - [c115]Dusan Hetlerovic, Lubos Popelínský, Pavel Brazdil, Carlos Soares, Fernando Freitas:
On Usefulness of Outlier Elimination in Classification Tasks. IDA 2022: 143-156 - [c114]Hajar Baghcheband, Carlos Soares, Luís Paulo Reis:
Machine Learning Data Markets: Trading Data using a Multi-Agent System. WI/IAT 2022: 450-457 - 2021
- [j31]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
Inmplode: A framework to interpret multiple related rule-based models. Expert Syst. J. Knowl. Eng. 38(6) (2021) - [j30]André Luis Debiaso Rossi, Carlos Soares, Bruno Feres de Souza, André Carlos Ponce de Leon Ferreira de Carvalho:
Micro-MetaStream: Algorithm selection for time-changing data. Inf. Sci. 565: 262-277 (2021) - [c113]Bernardo Leite, Amr Abdalrahman, João Castro, Julieta Frade, João Moreira, Carlos Soares:
Novelty Detection in Physical Activity. ICAART (2) 2021: 859-865 - [c112]André Ferreira Cruz, Pedro Saleiro, Catarina G. Belém, Carlos Soares, Pedro Bizarro:
Promoting Fairness through Hyperparameter Optimization. ICDM 2021: 1036-1041 - [c111]Filipa Barros, Vítor Cerqueira, Carlos Soares:
Empirical Study on the Impact of Different Sets of Parameters of Gradient Boosting Algorithms for Time-Series Forecasting with LightGBM. PRICAI (1) 2021: 454-465 - [e7]Carlos Soares, Luís Torgo:
Discovery Science - 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings. Lecture Notes in Computer Science 12986, Springer 2021, ISBN 978-3-030-88941-8 [contents] - [i28]Tomas Sousa Pereira, Tiago Cunha, Carlos Soares:
u-cf2vec: Representation Learning for Personalized Algorithm Selection in Recommender Systems. CoRR abs/2103.05673 (2021) - [i27]André Ferreira Cruz, Pedro Saleiro, Catarina G. Belém, Carlos Soares, Pedro Bizarro:
Promoting Fairness through Hyperparameter Optimization. CoRR abs/2103.12715 (2021) - [i26]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators. CoRR abs/2104.00584 (2021) - [i25]Vítor Cerqueira, Luís Torgo, Carlos Soares, Albert Bifet:
Model Compression for Dynamic Forecast Combination. CoRR abs/2104.01830 (2021) - [i24]André Baptista, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira, Miguel Arantes:
Pastprop-RNN: improved predictions of the future by correcting the past. CoRR abs/2106.13881 (2021) - [i23]Tarsicio Lucas, Teresa Bernarda Ludermir, Ricardo B. C. Prudêncio, Carlos Soares:
Meta-aprendizado para otimizacao de parametros de redes neurais. CoRR abs/2109.13745 (2021) - 2020
- [j29]Adriano Rivolli, Jesse Read, Carlos Soares, Bernhard Pfahringer, André C. P. L. F. de Carvalho:
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning. Mach. Learn. 109(8): 1509-1563 (2020) - [c110]David Ribeiro, João Costa, Inês Lopes, Telmo Barbosa, Carlos Soares, Filipe Sousa, Jorge Ribeiro, Duarte Rocha, Marlos Silva:
FILLET - Platform for Intelligent Nutrition. AICCSA 2020: 1-8 - [c109]João Costa, Inês Lopes, André V. Carreiro, David Ribeiro, Carlos Soares:
Fraunhofer AICOS at CLEF eHealth 2020 Task 1: Clinical Code Extraction From Textual Data Using Fine-Tuned BERT Models. CLEF (Working Notes) 2020 - [c108]Tomas Sousa Pereira, Tiago Cunha, Carlos Soares:
$\mu-\text{cf}2\text{vec}$: Representation Learning for Personalized Algorithm Selection in Recommender Systems. ICDM (Workshops) 2020: 181-188 - [c107]Bernardo Leite, Henrique Lopes Cardoso, Luís Paulo Reis, Carlos Soares:
Factual Question Generation for the Portuguese Language. INISTA 2020: 1-7 - [c106]Yassine Baghoussi, João Mendes-Moreira, Nuno Moniz, Carlos Soares:
Underground Train Tracking using Mobile Phone Accelerometer Data. ITSC 2020: 1-6 - [i22]André Ferreira Cruz, Pedro Saleiro, Catarina G. Belém, Carlos Soares, Pedro Bizarro:
A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization. CoRR abs/2010.03665 (2020) - [i21]Vítor Cerqueira, Nuno Moniz, Carlos Soares:
VEST: Automatic Feature Engineering for Forecasting. CoRR abs/2010.07137 (2020) - [i20]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes. CoRR abs/2010.11595 (2020)
2010 – 2019
- 2019
- [j28]Alvaro Neuenfeldt Júnior, Elsa Silva, Antonio Miguel Gomes, Carlos Soares, José Fernando Oliveira:
Data mining based framework to assess solution quality for the rectangular 2D strip-packing problem. Expert Syst. Appl. 118: 365-380 (2019) - [j27]Vítor Cerqueira, Luís Torgo, Fábio Pinto, Carlos Soares:
Arbitrage of forecasting experts. Mach. Learn. 108(6): 913-944 (2019) - [c105]André Correia, Carlos Soares, Alípio Jorge:
Dataset Morphing to Analyze the Performance of Collaborative Filtering. DS 2019: 29-39 - [c104]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. DS 2019: 445-459 - [c103]Adriano Rivolli, Catarina Amaral, Luís Guardão, Cláudio Rebelo de Sá, Carlos Soares:
KnowBots: Discovering Relevant Patterns in Chatbot Dialogues. DS 2019: 481-492 - [c102]Cláudio Rebelo de Sá, Arvind Kumar Shekar, Hugo M. Ferreira, Carlos Soares:
Building Robust Prediction Models for Defective Sensor Data Using Artificial Neural Networks. SOCO 2019: 142-153 - [i19]Cláudio Rebelo de Sá, Paulo J. Azevedo, Carlos Soares, Alípio Mário Jorge, Arno J. Knobbe:
Preference rules for label ranking: Mining patterns in multi-target relations. CoRR abs/1903.08504 (2019) - [i18]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters. CoRR abs/1909.13316 (2019) - 2018
- [j26]Adriano Rivolli, Carlos Soares, André C. P. L. F. de Carvalho:
Enhancing multilabel classification for food truck recommendation. Expert Syst. J. Knowl. Eng. 35(4) (2018) - [j25]Cláudio Rebelo de Sá, Paulo J. Azevedo, Carlos Soares, Alípio Mário Jorge, Arno J. Knobbe:
Preference rules for label ranking: Mining patterns in multi-target relations. Inf. Fusion 40: 112-125 (2018) - [j24]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
Metalearning and Recommender Systems: A literature review and empirical study on the algorithm selection problem for Collaborative Filtering. Inf. Sci. 423: 128-144 (2018) - [j23]Cláudio Rebelo de Sá, Wouter Duivesteijn, Paulo J. Azevedo, Alípio Mário Jorge, Carlos Soares, Arno J. Knobbe:
Discovering a taste for the unusual: exceptional models for preference mining. Mach. Learn. 107(11): 1775-1807 (2018) - [c101]Silvia Cristina Nunes das Dores, Carlos Soares, Duncan D. Ruiz:
Bandit-Based Automated Machine Learning. BRACIS 2018: 121-126 - [c100]Adriano Rivolli, Carlos Soares, André C. P. L. F. de Carvalho:
Label Expansion for Multi-label Classification. BRACIS 2018: 414-419 - [c99]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
CF4CF-META: Hybrid Collaborative Filtering Algorithm Selection Framework. DS 2018: 114-128 - [c98]Marta Mercier, Miriam Seoane Santos, Pedro H. Abreu, Carlos Soares, Jastin Pompeu Soares, João A. M. Santos:
Analysing the Footprint of Classifiers in Overlapped and Imbalanced Contexts. IDA 2018: 200-212 - [c97]Pedro Oliveira da Silva, Adriano Rivolli, Pedro Rocha, Francisco Correia, Carlos Soares:
Machine Learning for Drugs Prescription. IDEAL (1) 2018: 548-555 - [c96]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
Generalizing Knowledge in Decentralized Rule-Based Models. DMLE/IOTSTREAMING@PKDD/ECML 2018: 29-36 - [c95]Vítor Cerqueira, Fábio Pinto, Luís Torgo, Carlos Soares, Nuno Moniz:
Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles. ECML/PKDD (1) 2018: 620-636 - [c94]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
CF4CF: recommending collaborative filtering algorithms using collaborative filtering. RecSys 2018: 357-361 - [c93]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
A label ranking approach for selecting rankings of collaborative filtering algorithms. SAC 2018: 1393-1395 - [c92]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
A Framework for Analytical Approaches to Combine Interpretable Models. SIMBig 2018: 182-197 - [i17]Dylan te Lindert, Cláudio Rebelo de Sá, Carlos Soares, Arno J. Knobbe:
Smart energy management as a means towards improved energy efficiency. CoRR abs/1802.04128 (2018) - [i16]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
CF4CF: Recommending Collaborative Filtering algorithms using Collaborative Filtering. CoRR abs/1803.02250 (2018) - [i15]Arvind Kumar Shekar, Cláudio Rebelo de Sá, Hugo Ferreira, Carlos Soares:
Building robust prediction models for defective sensor data using Artificial Neural Networks. CoRR abs/1804.05544 (2018) - [i14]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
Algorithm Selection for Collaborative Filtering: the influence of graph metafeatures and multicriteria metatargets. CoRR abs/1807.09097 (2018) - [i13]Adriano Rivolli, Luís Paulo F. Garcia, Carlos Soares, Joaquin Vanschoren, André C. P. L. F. de Carvalho:
Towards Reproducible Empirical Research in Meta-Learning. CoRR abs/1808.10406 (2018) - [i12]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
cf2vec: Collaborative Filtering algorithm selection using graph distributed representations. CoRR abs/1809.06120 (2018) - [i11]Pedro Saleiro, Natasa Milic-Frayling, Eduarda Mendes Rodrigues, Carlos Soares:
Entity-Relationship Search over the Web. CoRR abs/1810.03235 (2018) - 2017
- [j22]Cláudio Rebelo de Sá, Carlos Soares, Arno J. Knobbe, Paulo Cortez:
Label Ranking Forests. Expert Syst. J. Knowl. Eng. 34(1) (2017) - [j21]André Luis Debiaso Rossi, Bruno Feres de Souza, Carlos Soares, André Carlos Ponce de Leon Ferreira de Carvalho:
A guidance of data stream characterization for meta-learning. Intell. Data Anal. 21(4): 1015-1035 (2017) - [j20]Pedro Saleiro, Eduarda Mendes Rodrigues, Carlos Soares, Eugénio Oliveira:
TexRep: A Text Mining Framework for Online Reputation Monitoring. New Gener. Comput. 35(4): 365-389 (2017) - [c91]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
Recommending Collaborative Filtering Algorithms Using Subsampling Landmarkers. DS 2017: 189-203 - [c90]Pedro Saleiro, Luís Sarmento, Eduarda Mendes Rodrigues, Carlos Soares, Eugénio C. Oliveira:
Learning Word Embeddings from the Portuguese Twitter Stream: A Study of Some Practical Aspects. EPIA 2017: 880-891 - [c89]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Arbitrated Ensemble for Solar Radiation Forecasting. IWANN (1) 2017: 720-732 - [c88]Fábio Pinto, Vítor Cerqueira, Carlos Soares, João Mendes-Moreira:
autoBagging: Learning to Rank Bagging Workflows with Metalearning. AutoML@PKDD/ECML 2017: 21-27 - [c87]Silvia Nunes das Dôres, Carlos Soares, Duncan D. A. Ruiz:
Effect of Metalearning on Feature Selection Employment. AutoML@PKDD/ECML 2017: 84-90 - [c86]Vítor Cerqueira, Luís Torgo, Fábio Pinto, Carlos Soares:
Arbitrated Ensemble for Time Series Forecasting. ECML/PKDD (2) 2017: 478-494 - [c85]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
Metalearning for Context-aware Filtering: Selection of Tensor Factorization Algorithms. RecSys 2017: 14-22 - [c84]Pedro Saleiro, Eduarda Mendes Rodrigues, Carlos Soares, Eugénio C. Oliveira:
FEUP at SemEval-2017 Task 5: Predicting Sentiment Polarity and Intensity with Financial Word Embeddings. SemEval@ACL 2017: 904-908 - [c83]Pedro Saleiro, Natasa Milic-Frayling, Eduarda Mendes Rodrigues, Carlos Soares:
Early Fusion Strategy for Entity-Relationship Retrieval. KG4IR@SIGIR 2017: 49-54 - [c82]Pedro Saleiro, Natasa Milic-Frayling, Eduarda Mendes Rodrigues, Carlos Soares:
RELink: A Research Framework and Test Collection for Entity-Relationship Retrieval. SIGIR 2017: 1273-1276 - [r5]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares:
Inductive Transfer. Encyclopedia of Machine Learning and Data Mining 2017: 666-671 - [r4]Pavel Brazdil, Ricardo Vilalta, Christophe G. Giraud-Carrier, Carlos Soares:
Metalearning. Encyclopedia of Machine Learning and Data Mining 2017: 818-823 - [i10]Pedro Saleiro, Eduarda Mendes Rodrigues, Carlos Soares, Eugénio C. Oliveira:
FEUP at SemEval-2017 Task 5: Predicting Sentiment Polarity and Intensity with Financial Word Embeddings. CoRR abs/1704.05091 (2017) - [i9]Pedro Saleiro, Natasa Milic-Frayling, Eduarda Mendes Rodrigues, Carlos Soares:
RELink: A Research Framework and Test Collection for Entity-Relationship Retrieval. CoRR abs/1706.03960 (2017) - [i8]Fábio Pinto, Vítor Cerqueira, Carlos Soares, João Mendes-Moreira:
autoBagging: Learning to Rank Bagging Workflows with Metalearning. CoRR abs/1706.09367 (2017) - [i7]Pedro Saleiro, Natasa Milic-Frayling, Eduarda Mendes Rodrigues, Carlos Soares:
Early Fusion Strategy for Entity-Relationship Retrieval. CoRR abs/1707.09075 (2017) - [i6]Pedro Saleiro, Luís Sarmento, Eduarda Mendes Rodrigues, Carlos Soares, Eugénio C. Oliveira:
Learning Word Embeddings from the Portuguese Twitter Stream: A Study of some Practical Aspects. CoRR abs/1709.00947 (2017) - 2016
- [j19]Arthur F. M. Sousa, Ricardo B. C. Prudêncio, Teresa Bernarda Ludermir, Carlos Soares:
Active learning and data manipulation techniques for generating training examples in meta-learning. Neurocomputing 194: 45-55 (2016) - [j18]Jorge Y. Kanda, André C. P. L. F. de Carvalho, Eduardo R. Hruschka, Carlos Soares, Pavel Brazdil:
Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: A comparison of meta-features. Neurocomputing 205: 393-406 (2016) - [j17]Cláudio Rebelo de Sá, Carlos Soares, Arno J. Knobbe:
Entropy-based discretization methods for ranking data. Inf. Sci. 329: 921-936 (2016) - [c81]Pedro Saleiro, Luís Gomes, Carlos Soares:
Sentiment Aggregate Functions for Political Opinion Polling using Microblog Streams. C3S2E 2016: 44-50 - [c80]Cláudio Rebelo de Sá, Wouter Duivesteijn, Carlos Soares, Arno J. Knobbe:
Exceptional Preferences Mining. DS 2016: 3-18 - [c79]Pedro Saleiro, Jorge Teixeira, Carlos Soares, Eugénio C. Oliveira:
TimeMachine: Entity-Centric Search and Visualization of News Archives. ECIR 2016: 845-848 - [c78]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 - [c77]Catarina Félix, Carlos Soares, Alípio Jorge:
Can Metalearning Be Applied to Transfer on Heterogeneous Datasets? HAIS 2016: 332-343 - [c76]André Costa, Tiago Cunha, Carlos Soares:
AToMRS: A Tool to Monitor Recommender Systems. KDIR 2016: 133-140 - [c75]Pedro Saleiro, Carlos Soares:
Learning from the News: Predicting Entity Popularity on Twitter. IDA 2016: 171-182 - [c74]Vítor Cerqueira, Fábio Pinto, Cláudio Rebelo de Sá, Carlos Soares:
Combining Boosted Trees with Metafeature Engineering for Predictive Maintenance. IDA 2016: 393-397 - [c73]Mohammad Nozari Zarmehri, Carlos Soares:
Collaborative Data Analysis in Hyperconnected Transportation Systems. PRO-VE 2016: 13-23