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2020 – today
- 2025
[j42]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:
Exploring percolation features with polynomial algorithms for classifying Covid-19 in chest X-ray images. Pattern Recognit. Lett. 189: 248-255 (2025)- [c140]Luis Roque, Vítor Cerqueira, Carlos Soares, Luís Torgo:
Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine. AAAI 2025: 20192-20199 - 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) - [c139]Moisés Santos, André C. P. L. F. de Carvalho, Carlos Soares:
Enhancing Algorithm Performance Understanding through tsMorph: Generating Semi-Synthetic Time Series for Robust Forecasting Evaluation. AEQUITAS@ECAI 2024 - [c138]Hajar Baghcheband, Carlos Soares, Luís Paulo Reis:
CNP-MLDM: Contract Net Protocol for Negotiation in Machine Learning Data Market. DS (LB) 2024 - [c137]Vítor Cerqueira, Luis Roque, Carlos Soares:
Forecasting with Deep Learning: Beyond Average of Average of Average Performance. DS (1) 2024: 135-149 - [c136]Inês Oliveira e Silva, Sérgio M. Jesus, Hugo M. Ferreira, Pedro Saleiro, Inês Sousa, Pedro Bizarro, Carlos Soares:
Fair-OBNC: Correcting Label Noise for Fairer Datasets. ECAI 2024: 1003-1010 - [c135]Ricardo Urjais Gomes, Carlos Soares, Luís Paulo Reis:
An Empirical Evaluation of DeepAR for Univariate Time Series Forecasting. EPIA (3) 2024: 188-199 - [c134]Cátia Teixeira, Inês Gomes, Luís Cunha, Carlos Soares, Jan N. van Rijn:
GASTeNv2: Generative Adversarial Stress Testing Networks with Gaussian Loss. EPIA (2) 2024: 261-272 - [c133]José Leites, Vítor Cerqueira, Carlos Soares:
Lag Selection for Univariate Time Series Forecasting Using Deep Learning: An Empirical Study. EPIA (3) 2024: 321-332 - [c132]Vítor Cerqueira, Nuno Moniz, Ricardo Inácio, Carlos Soares:
Time Series Data Augmentation as an Imbalanced Learning Problem. EPIA (2) 2024: 335-346 - [c131]Inês Oliveira e Silva, Carlos Soares, Vítor Cerqueira, Arlete Rodrigues, Pedro Bastardo:
Meta-TadGAN: Time Series Anomaly Detection Using TadGAN with Meta-features. EPIA (3) 2024: 347-358 - [c130]Rodrigo Tuna, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira:
Kernel Corrector LSTM. IDA (2) 2024: 3-14 - [c129]Hajar Baghcheband, Carlos Soares, Luís Paulo Reis:
Shapley-Based Data Valuation Method for the Machine Learning Data Markets (MLDM). ISMIS 2024: 170-177 - [c128]Luis Roque, Carlos Soares, Luís Torgo:
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. KDD 2024: 2491-2499 - [c127]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches. LOD (1) 2024: 464-478 - [c126]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 - [c125]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 - [i42]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) - [i41]Rodrigo Tuna, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira:
Kernel Corrector LSTM. CoRR abs/2404.18273 (2024) - [i40]Vítor Cerqueira, Nuno Moniz, Ricardo Inácio, Carlos Soares:
Time Series Data Augmentation as an Imbalanced Learning Problem. CoRR abs/2404.18537 (2024) - [i39]José Leites, Vítor Cerqueira, Carlos Soares:
Lag Selection for Univariate Time Series Forecasting using Deep Learning: An Empirical Study. CoRR abs/2405.11237 (2024) - [i38]Vítor Cerqueira, Luis Roque, Carlos Soares:
Forecasting with Deep Learning: Beyond Average of Average of Average Performance. CoRR abs/2406.16590 (2024) - [i37]Ricardo Inácio, Vítor Cerqueira, Marília Barandas, Carlos Soares:
Meta-learning and Data Augmentation for Stress Testing Forecasting Models. CoRR abs/2406.17008 (2024) - [i36]Luis Roque, Carlos Soares, Luís Torgo:
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. CoRR abs/2408.03399 (2024) - [i35]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) - [i34]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) - [i33]Inês Oliveira e Silva, Sérgio M. Jesus, Hugo M. Ferreira, Pedro Saleiro, Inês Sousa, Pedro Bizarro, Carlos Soares:
Fair-OBNC: Correcting Label Noise for Fairer Datasets. CoRR abs/2410.06214 (2024) - [i32]Aníbal Silva, André Restivo, Moisés Santos, Carlos Soares:
Tabular data generation with tensor contraction layers and transformers. CoRR abs/2412.05390 (2024) - [i31]Luis Roque, Carlos Soares, Vítor Cerqueira, Luís Torgo:
Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine. CoRR abs/2412.14435 (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) - [c124]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
Symbolic Data Analysis to Improve Completeness of Model Combination Methods. AI (2) 2023: 107-119 - [c123]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 - [c122]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 - [c121]Fernando Freitas, Pavel Brazdil, Carlos Soares:
Exploring the Reduction of Configuration Spaces of Workflows. DS 2023: 33-47 - [c120]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 - [c119]Luís Cunha, Carlos Soares, André Restivo, Luís F. Teixeira:
GASTeN: Generative Adversarial Stress Test Networks. IDA 2023: 91-102 - [c118]Frederico Lopes, Carlos Soares, Paulo Cortez:
PrivateCTGAN: Adapting GAN for Privacy-Aware Tabular Data Sharing. PKDD/ECML Workshops (2) 2023: 169-180 - [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 Nunes das Dôres, 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 - [c72]Fábio Pinto, Carlos Soares, João Mendes-Moreira:
Towards Automatic Generation of Metafeatures. PAKDD (1) 2016: 215-226 - [c71]Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
Selecting Collaborative Filtering Algorithms Using Metalearning. ECML/PKDD (2) 2016: 393-409 - [c70]Fábio Pinto, Carlos Soares, João Mendes-Moreira:
CHADE: Metalearning with Classifier Chains for Dynamic Combination of Classifiers. ECML/PKDD (1) 2016: 410-425 - [c69]André Maia, Tiago Daniel Sá Cunha, Carlos Soares, Pedro Henriques Abreu:
TweeProfiles3: Visualization of Spatio-Temporal Patterns on Twitter. WorldCIST (1) 2016: 869-878 - [c68]Tomy Rodrigues, Tiago Daniel Sá Cunha, Dino Ienco, Pascal Poncelet, Carlos Soares:
RetweetPatterns: Detection of Spatio-Temporal Patterns of Retweets. WorldCIST (1) 2016: 879-888 - [e6]Henrik Boström, Arno J. Knobbe, Carlos Soares, Panagiotis Papapetrou:
Advances in Intelligent Data Analysis XV - 15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings. Lecture Notes in Computer Science 9897, 2016, ISBN 978-3-319-46348-3 [contents] - [i5]Pedro Saleiro, Jorge Teixeira, Carlos Soares, Eugénio C. Oliveira:
TimeMachine: Entity-centric Search and Visualization of News Archives. CoRR abs/1601.00855 (2016) - [i4]Pedro Saleiro, Luís Gomes, Carlos Soares:
Sentiment Aggregate Functions for Political Opinion Polling using Microblog Streams. CoRR abs/1606.05242 (2016) - [i3]Pedro Saleiro, Carlos Soares:
Learning from the News: Predicting Entity Popularity on Twitter. CoRR abs/1607.03057 (2016) - 2015
- [j16]Fábio Pinto, Carlos Soares, Pavel Brazdil:
Combining regression models and metaheuristics to optimize space allocation in the retail industry. Intell. Data Anal. 19(s1): S149-S162 (2015) - [j15]João Mendes-Moreira, Alípio Mário Jorge, Jorge Freire de Sousa, Carlos Soares:
Improving the accuracy of long-term travel time prediction using heterogeneous ensembles. Neurocomputing 150: 428-439 (2015) - [c67]Pedro Saleiro, Silvio Amir, Mário J. Silva, Carlos Soares:
POPmine: Tracking Political Opinion on the Web. CIT/IUCC/DASC/PICom 2015: 1521-1526 - [c66]Pedro Strecht, Luis Cruz, Carlos Soares, João Mendes-Moreira, Rui Abreu:
A Comparative Study of Regression and Classification Algorithms for Modelling Students' Academic Performance. EDM 2015: 392-395 - [c65]Cláudio Rebelo de Sá, Carla Rebelo, Carlos Soares, Arno J. Knobbe:
Distance-Based Decision Tree Algorithms for Label Ranking. EPIA 2015: 525-534 - [c64]Afonso Vilaça, Ana Aguiar, Carlos Soares:
Estimating Fuel Consumption from GPS Data. IbPRIA 2015: 672-682 - [c63]Mohammad Nozari Zarmehri, Carlos Soares:
Using Metalearning for Prediction of Taxi Trip Duration Using Different Granularity Levels. IDA 2015: 205-216 - [c62]Mohammad Nozari Zarmehri, Carlos Soares:
Metalearning to choose the level of analysis in nested data: A case study on error detection in foreign trade statistics. IJCNN 2015: 1-8 - [c61]Francisco Rebelo, Carlos Soares, Rosaldo J. F. Rossetti:
TwitterJam: Identification of mobility patterns in urban centers based on tweets. ISC2 2015: 1-6 - [c60]Fábio Pinto, Carlos Soares, João Mendes-Moreira:
Pruning Bagging Ensembles with Metalearning. MCS 2015: 64-75 - [c59]Catarina Félix, Carlos Soares, Alípio Jorge:
Metalearning for Multiple-Domain Transfer Learning. MetaSel@PKDD/ECML 2015: 67-79 - [e5]Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, Carlos Soares, João Gama, Alípio Jorge:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I. Lecture Notes in Computer Science 9284, Springer 2015, ISBN 978-3-319-23527-1 [contents] - [e4]Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, João Gama, Alípio Jorge, Carlos Soares:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II. Lecture Notes in Computer Science 9285, Springer 2015, ISBN 978-3-319-23524-0 [contents] - [i2]Pedro Saleiro, Silvio Amir, Mário J. Silva, Carlos Soares:
POPmine: Tracking Political Opinion on the Web. CoRR abs/1511.09101 (2015) - 2014
- [j14]André Luis Debiaso Rossi, André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares, Bruno Feres de Souza:
MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data. Neurocomputing 127: 52-64 (2014) - [j13]Péricles B. C. Miranda, Ricardo B. C. Prudêncio, André C. P. L. F. de Carvalho, Carlos Soares:
A hybrid meta-learning architecture for multi-objective optimization of SVM parameters. Neurocomputing 143: 27-43 (2014) - [j12]Marcos Aurélio Domingues, Carlos Soares, Alípio Mário Jorge, Solange Oliveira Rezende:
A data warehouse to support web site automation. J. Braz. Comput. Soc. 20(1): 11:1-11:16 (2014) - [c58]Tiago Daniel Sá Cunha, Carlos Soares, Eduarda Mendes Rodrigues:
TweeProfiles: Detection of Spatio-temporal Patterns on Twitter. ADMA 2014: 123-136 - [c57]Fábio Pinto, Carlos Soares, João Mendes-Moreira:
An Empirical Methodology to Analyze the Behavior of Bagging. ADMA 2014: 199-212 - [c56]Pedro Strecht, João Mendes-Moreira, Carlos Soares:
Merging Decision Trees: A Case Study in Predicting Student Performance. ADMA 2014: 535-548 - [c55]Fábio Pinto, Carlos Soares, João Mendes-Moreira:
A Framework To Decompose And Develop Metafeatures. MetaSel@ECAI 2014: 32-36 - [c54]Pedro H. Abreu, Carlos Soares, Rui Carlos Camacho:
Distributed Environment Framework for Optimization Experiments. ICCSA (Workshops/Short Papers/Posters) 2014: 256-259 - [c53]Catarina Félix, Carlos Soares, Alípio Jorge, João Vinagre:
Monitoring Recommender Systems: A Business Intelligence Approach. ICCSA (6) 2014: 277-288 - [e3]Joaquin Vanschoren, Pavel Brazdil, Carlos Soares, Lars Kotthoff:
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, MetaSel@ECAI 2014, Prague, Czech Republic, August 19, 2014. CEUR Workshop Proceedings 1201, CEUR-WS.org 2014 [contents] - 2013
- [j11]Marcos Aurélio Domingues, Alípio Mário Jorge, Carlos Soares:
Dimensions as Virtual Items: Improving the predictive ability of top-N recommender systems. Inf. Process. Manag. 49(3): 698-720 (2013) - [j10]Marcos Aurélio Domingues, Carlos Soares, Alípio Mário Jorge:
Using statistics, visualization and data mining for monitoring the quality of meta-data in web portals. Inf. Syst. E Bus. Manag. 11(4): 569-595 (2013) - [c52]Pedro Saleiro, Luis Rei, Arian Pasquali, Carlos Soares, Jorge Teixeira, Fábio Pinto, Mohammad Nozari Zarmehri, Catarina Félix, Pedro Strecht:
POPSTAR at RepLab 2013: Name Ambiguity Resolution on Twitter. CLEF (Working Notes) 2013 - [c51]Cláudio Rebelo de Sá, Carlos Soares, Arno J. Knobbe, Paulo J. Azevedo, Alípio Mário Jorge:
Multi-interval Discretization of Continuous Attributes for Label Ranking. Discovery Science 2013: 155-169 - [c50]Arthur F. M. Sousa, Ricardo B. C. Prudêncio, Carlos Soares, Teresa Bernarda Ludermir:
Active selection of training instances for a random forest meta-learner. IJCNN 2013: 1-7 - [c49]Fábio Pinto, Carlos Soares:
Space Allocation in the Retail Industry: A Decision Support System Integrating Evolutionary Algorithms and Regression Models. ECML/PKDD (3) 2013: 531-546 - 2012
- [j9]João Mendes-Moreira, Carlos Soares, Alípio Mário Jorge, Jorge Freire de Sousa:
Ensemble approaches for regression: A survey. ACM Comput. Surv. 45(1): 10:1-10:40 (2012) - [j8]João Mendes-Moreira, Alípio Mário Jorge, Jorge Freire de Sousa, Carlos Soares:
Comparing state-of-the-art regression methods for long term travel time prediction. Intell. Data Anal. 16(3): 427-449 (2012) - [j7]Taciana A. F. Gomes, Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, André L. D. Rossi, André C. P. L. F. de Carvalho:
Combining meta-learning and search techniques to select parameters for support vector machines. Neurocomputing 75(1): 3-13 (2012) - [c48]Carlos Gomes, Bernardo Almada-Lobo, José Luís Cabral de Moura Borges, Carlos Soares:
Integrating Data Mining and Optimization Techniques on Surgery Scheduling. ADMA 2012: 589-602 - [c47]Geraldina Ribeiro, Wouter Duivesteijn, Carlos Soares, Arno J. Knobbe:
Multilayer Perceptron for Label Ranking. ICANN (2) 2012: 25-32 - [c46]Péricles Barbosa C. de Miranda, Ricardo Bastos Cavalcante Prudêncio, André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares:
An Experimental Study of the Combination of Meta-Learning with Particle Swarm Algorithms for SVM Parameter Selection. ICCSA (3) 2012: 562-575 - [c45]Jorge Y. Kanda, Carlos Soares, Eduardo R. Hruschka, André Carlos Ponce de Leon Ferreira de Carvalho:
A Meta-Learning Approach to Select Meta-Heuristics for the Traveling Salesman Problem Using MLP-Based Label Ranking. ICONIP (3) 2012: 488-495 - [c44]Alípio Mário Jorge, João Mendes-Moreira, Jorge Freire de Sousa, Carlos Soares, Paulo J. Azevedo:
Finding Interesting Contexts for Explaining Deviations in Bus Trip Duration Using Distribution Rules. IDA 2012: 139-149 - [c43]Péricles B. C. Miranda, Ricardo Bastos Cavalcante Prudêncio, André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares:
Multi-objective optimization and Meta-learning for SVM parameter selection. IJCNN 2012: 1-8 - [c42]Péricles B. C. Miranda, Ricardo B. C. Prudêncio, André C. P. L. F. de Carvalho, Carlos Soares:
Combining Meta-Learning with Multi-objective Particle Swarm Algorithms for SVM Parameter Selection: An Experimental Analysis. SBRN 2012: 1-6 - [c41]André Luis Debiaso Rossi, André C. P. L. F. de Carvalho, Carlos Soares:
Meta-Learning for Periodic Algorithm Selection in Time-Changing Data. SBRN 2012: 7-12 - [c40]Péricles Barbosa C. de Miranda, Ricardo Bastos Cavalcante Prudêncio, André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares:
Combining a multi-objective optimization approach with meta-learning for SVM parameter selection. SMC 2012: 2909-2914 - 2011
- [j6]Jorge Y. Kanda, André Carlos Ponce de Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares:
Selection of algorithms to solve traveling salesman problems using meta-learning. Int. J. Hybrid Intell. Syst. 8(3): 117-128 (2011) - [c39]Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, Teresa Bernarda Ludermir:
Combining Meta-learning and Active Selection of Datasetoids for Algorithm Selection. HAIS (1) 2011: 164-171 - [c38]Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, Teresa Bernarda Ludermir:
Uncertainty Sampling-Based Active Selection of Datasetoids for Meta-learning. ICANN (2) 2011: 454-461 - [c37]Jorge Y. Kanda, André Carlos Ponce de Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares:
Using Meta-learning to Recommend Meta-heuristics for the Traveling Salesman Problem. ICMLA (1) 2011: 346-351 - [c36]Américo Lopes Azevedo, João Bastos, António Almeida, Carlos Soares, Nicola Magaletti, Enrico Del Grosso, Dieter Stellmach, Marcus Winkler, Rosanna Fornasiero, Andrea Zangiacomi, Andrea Chiodi:
Customer-Oriented and Eco-friendly Networks for Health Fashionable Goods - The CoReNet Approach. PRO-VE 2011: 69-76 - [c35]Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, Teresa Bernarda Ludermir:
Uncertainty sampling methods for selecting datasets in active meta-learning. IJCNN 2011: 1082-1089 - [c34]Cláudio Rebelo de Sá, Carlos Soares, Alípio Mário Jorge, Paulo J. Azevedo, Joaquim Pinto da Costa:
Mining Association Rules for Label Ranking. PAKDD (2) 2011: 432-443 - [c33]Marcos Aurélio Domingues, Alípio Mário Jorge, Carlos Soares:
Exploiting Additional Dimensions as Virtual Items on Top-N Recommender Systems. Web Intelligence 2011: 92-95 - [i1]Marcos Aurélio Domingues, Alípio Mário Jorge, Carlos Soares:
Using Contextual Information as Virtual Items on Top-N Recommender Systems. CoRR abs/1111.2948 (2011) - 2010
- [c32]Artur Aiguzhinov, Carlos Soares, Ana Paula Serra:
A Similarity-Based Adaptation of Naive Bayes for Label Ranking: Application to the Metalearning Problem of Algorithm Recommendation. Discovery Science 2010: 16-26 - [c31]Bruno Feres de Souza, André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares:
Empirical Evaluation of Ranking Prediction Methods for Gene Expression Data Classification. IBERAMIA 2010: 194-203 - [c30]Bruno Feres de Souza, André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares:
A comprehensive comparison of ML algorithms for gene expression data classification. IJCNN 2010: 1-8 - [c29]Carlos Soares, Miguel Calejo:
Intelligent Document Routing as a First Step towards Workflow Automation: A Case Study Implemented in SQL. ISoLA (1) 2010: 276-284 - [c28]Jorge Y. Kanda, André Carlos Ponce de Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares:
Using Meta-learning to Classify Traveling Salesman Problems. SBRN 2010: 73-78 - [c27]Taciana A. F. Gomes, Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, André L. D. Rossi, André Carlos Ponce de Leon Ferreira de Carvalho:
Combining Meta-learning and Search Techniques to SVM Parameter Selection. SBRN 2010: 79-84 - [p2]Carlos Soares, Rayid Ghani:
Data Mining for Business Applications: Introduction. Data Mining for Business Applications 2010: 1-14 - [p1]Luís Torgo, Carlos Soares:
Resource-bounded Outlier Detection using Clustering Methods. Data Mining for Business Applications 2010: 84-98 - [e2]Carlos Soares, Rayid Ghani:
Data Mining for Business Applications. Frontiers in Artificial Intelligence and Applications 218, IOS Press 2010, ISBN 978-1-60750-632-4 [contents] - [r3]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares:
Inductive Transfer. Encyclopedia of Machine Learning 2010: 545-548 - [r2]Pavel Brazdil, Ricardo Vilalta, Christophe G. Giraud-Carrier, Carlos Soares:
Metalearning. Encyclopedia of Machine Learning 2010: 662-666
2000 – 2009
- 2009
- [b1]Pavel Brazdil, Christophe G. Giraud-Carrier, Carlos Soares, Ricardo Vilalta:
Metalearning - Applications to Data Mining. Cognitive Technologies, Springer 2009, ISBN 978-3-540-73262-4, pp. I-X, 1-176 [contents] - [j5]Bruno Feres de Souza, Carlos Soares, André C. P. L. F. de Carvalho:
Meta-learning approach to gene expression data classification. Int. J. Intell. Comput. Cybern. 2(2): 285-303 (2009) - [c26]Luís Torgo, Welma Pereira, Carlos Soares:
Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data. EPIA 2009: 435-446 - [c25]Pedro H. Abreu, Carlos Soares, Jorge M. S. Valente:
Selection of Heuristics for the Job-Shop Scheduling Problem Based on the Prediction of Gaps in Machines. LION 2009: 134-147 - [c24]João Mendes-Moreira, Alípio Mário Jorge, Carlos Soares, Jorge Freire de Sousa:
Ensemble Learning: A Study on Different Variants of the Dynamic Selection Approach. MLDM 2009: 191-205 - [c23]Carlos Soares:
UCI++: Improved Support for Algorithm Selection Using Datasetoids. PAKDD 2009: 499-506 - [c22]João Mendes-Moreira, Carlos Soares, Alípio Mário Jorge, Jorge Freire de Sousa:
The Effect of Varying Parameters and Focusing on Bus Travel Time Prediction. PAKDD 2009: 689-696 - [r1]Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares, Ricardo Vilalta:
Meta-Learning. Encyclopedia of Data Warehousing and Mining 2009: 1207-1215 - 2008
- [c21]André L. D. Rossi, André C. P. L. F. de Carvalho, Carlos Soares:
Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis. HIS 2008: 435-440 - [c20]Bruno Feres de Souza, André Carlos Ponce de Leon Ferreira de Carvalho, Carlos Soares:
Metalearning for Gene Expression Data Classification. HIS 2008: 441-446 - [c19]André L. D. Rossi, Carlos Soares, André C. P. L. F. de Carvalho:
Bioinspired Parameter Tuning of MLP Networks for Gene Expression Analysis: Quality of Fitness Estimates vs. Number of Solutions Analysed. ICONIP (2) 2008: 252-259 - [c18]Marcos Aurélio Domingues, Alípio Mário Jorge, Carlos Soares:
The Impact of Contextual Information on the Accuracy of Existing Recommender Systems for Web Personalization. Web Intelligence 2008: 789-792 - [e1]Carlos Soares, Yonghong Peng, Jun Meng, Takashi Washio, Zhi-Hua Zhou:
Applications of Data Mining in E-Business and Finance. Frontiers in Artificial Intelligence and Applications 177, IOS Press 2008, ISBN 978-1-58603-890-8 [contents] - 2007
- [c17]Carmen Rebelo, Pedro Quelhas Brito, Carlos Soares, Alípio Mário Jorge, Rui Brandão:
Quantitative Evaluation of Clusterings for Marketing Applications: A Web Portal Case Study. EPIA Workshops 2007: 437-448 - [c16]Carlos Soares, Yonghong Peng, Jun Meng, Takashi Washio, Zhi-Hua Zhou:
Applications of Data Mining in E-Business Finance: Introduction. DMBiz@PAKDD 2007: 1-9 - 2006
- [j4]Rayid Ghani, Carlos Soares:
Data mining for business applications: KDD-2006 workshop. SIGKDD Explor. 8(2): 79-81 (2006) - [c15]Marcos Aurélio Domingues, Carlos Soares, Alípio Mário Jorge:
A Web-Based System to Monitor the Quality of Meta-Data in Web Portals. IAT Workshops 2006: 188-191 - [c14]João Mendes-Moreira, Alípio Mário Jorge, Carlos Soares, Jorge Freire de Sousa:
Improving SVM-Linear Predictions Using CART for Example Selection. ISMIS 2006: 632-641 - [c13]Carlos Soares, Pavel Brazdil:
Selecting parameters of SVM using meta-learning and kernel matrix-based meta-features. SAC 2006: 564-568 - [c12]Carla Carvalho, Alípio Mário Jorge, Carlos Soares:
Personalization of E-newsletters Based on Web Log Analysis and Clustering. Web Intelligence 2006: 724-727 - [c11]Carmen Rebelo, Pedro Quelhas Brito, Carlos Soares, Alípio Mário Jorge:
Factor Analysis to Support the Visualization and Interpretation of Clusters of Portal Users. Web Intelligence 2006: 987-990 - 2005
- [c10]Carlos Soares, Alípio Mário Jorge, Marcos Aurélio Domingues:
Monitoring the Quality of Meta-data in Web Portals Using Statistics, Visualization and Data Mining. EPIA 2005: 371-382 - 2004
- [j3]Ricardo Vilalta, Christophe G. Giraud-Carrier, Pavel Brazdil, Carlos Soares:
Using Meta-Learning to Support Data Mining. Int. J. Comput. Sci. Appl. 1(1): 31-45 (2004) - [j2]Carlos Soares, Pavel Brazdil, Petr Kuba:
A Meta-Learning Method to Select the Kernel Width in Support Vector Regression. Mach. Learn. 54(3): 195-209 (2004) - 2003
- [j1]Pavel Brazdil, Carlos Soares, Joaquim Pinto da Costa:
Ranking Learning Algorithms: Using IBL and Meta-Learning on Accuracy and Time Results. Mach. Learn. 50(3): 251-277 (2003) - [c9]Carlos Soares:
Is the UCI Repository Useful for Data Mining? EPIA 2003: 209-223 - 2002
- [c8]Yonghong Peng, Peter A. Flach, Carlos Soares, Pavel Brazdil:
Improved Dataset Characterisation for Meta-learning. Discovery Science 2002: 141-152 - [c7]Carlos Soares, Pavel Brazdil:
A Comparative Study of Some Issues Concerning Algorithm Recommendation Using Ranking Methods. IBERAMIA 2002: 80-89 - 2001
- [c6]Pavel Brazdil, Carlos Soares, Rui Pereira:
Reducing Rankings of Classifiers by Eliminating Redundant Classifiers. EPIA 2001: 14-21 - [c5]Carlos Soares, Johann Petrak, Pavel Brazdil:
Sampling-Based Relative Landmarks: Systematically Test-Driving Algorithms Before Choosing. EPIA 2001: 88-95 - 2000
- [c4]Pavel Brazdil, Carlos Soares:
A Comparison of Ranking Methods for Classification Algorithm Selection. ECML 2000: 63-74 - [c3]Carlos Soares, Pavel Brazdil:
Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information. PKDD 2000: 126-135
1990 – 1999
- 1998
- [c2]João Gama, Luís Torgo, Carlos Soares:
Dynamic Discretization of Continuous Attributes. IBERAMIA 1998: 160-169 - 1997
- [c1]Carlos Soares, Miguel Calejo:
From Graphical Objects to Terms and Back: an Extended Application Framework for Prolog. LPE 1997: 60-69
Coauthor Index
André C. P. L. F. de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
Tiago Cunha 0001
aka: Tiago Daniel Sá Cunha
aka: Tiago Daniel Sá Cunha
Ricardo B. C. Prudêncio
aka: Ricardo Bastos Cavalcante Prudêncio
aka: Ricardo Bastos Cavalcante Prudêncio
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