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João Mendes-Moreira 0001
João Mendes Moreira 0001 – João Pedro Carvalho Leal Mendes Moreira
Person information
- affiliation: University of Porto, Faculty of Engineering, Porto, Portugal
Other persons with the same name
- João Mendes Moreira 0002
(aka: João Mendes-Moreira 0002) — FCCN - National Scientific Computation, Lisboa, Portugal
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2020 – today
- 2024
- [j22]Aníbal Silva
Map-matching methods in agriculture. Comput. Electron. Agric. 216: 108529 (2024) - [j21]Yassine Baghoussi
Corrector LSTM: built-in training data correction for improved time-series forecasting. Neural Comput. Appl. 36(26): 16213-16231 (2024) - [c72]Rodrigo Tuna
Kernel Corrector LSTM. IDA (2) 2024: 3-14 - [i11]Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira:
Estimating Player Performance in Different Contexts Using Fine-tuned Large Events Models. CoRR abs/2402.06815 (2024) - [i10]João Mendes-Moreira, Tiago Mendes-Neves:
Towards a Systematic Approach to Design New Ensemble Learning Algorithms. CoRR abs/2402.06818 (2024) - [i9]Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira:
Forecasting Events in Soccer Matches Through Language. CoRR abs/2402.06820 (2024) - [i8]Rodrigo Tuna, Yassine Baghoussi, Carlos Soares, João Mendes-Moreira:
Kernel Corrector LSTM. CoRR abs/2404.18273 (2024) - 2023
- [j20]André Sousa, Daniel T. Veloso, Henrique M. Gonçalves, João Pascoal Faria
Applying Machine Learning to Estimate the Effort and Duration of Individual Tasks in Software Projects. IEEE Access 11: 89933-89946 (2023) - [j19]Manish Bhanu
ST-AGP: Spatio-Temporal aggregator predictor model for multi-step taxi-demand prediction in cities. Appl. Intell. 53(2): 2110-2132 (2023) - [j18]Rahul Kumar, João Mendes-Moreira, Joydeep Chandra:
DyGCN-LSTM: A dynamic GCN-LSTM based encoder-decoder framework for multistep traffic prediction. Appl. Intell. 53(21): 25388-25411 (2023) - [j17]Manish Bhanu
An encoder framework for taxi-demand prediction using spatio-temporal function approximation. Eng. Appl. Artif. Intell. 126: 106760 (2023) - [c71]Pedro Strecht
Symbolic Data Analysis to Improve Completeness of Model Combination Methods. AI (2) 2023: 107-119 - [c70]Paulo J. S. Ferreira
Studying the Impact of Sampling in Highly Frequent Time Series. EPIA (1) 2023: 251-262 - [c69]Maria Pedroto
Combining Neighbor Models to Improve Predictions of Age of Onset of ATTRv Carriers. EPIA (2) 2023: 286-297 - [c68]Eduardo M. Rodrigues
Interpreting What is Important: An Explainability Approach and Study on Feature Selection. EPIA (1) 2023: 288-298 - [c67]Tiago Costa Mendes
Unsupervised Online Event Ranking for IT Operations. IDEAL 2023: 345-355 - [c66]Akilu Rilwan Muhammad
Inferring Transportation Mode Using Pooled Features from Time and Frequency Domains. ITSC 2023: 3985-3990 - [c65]Paulo J. S. Ferreira
A Study on Hyperparameters Configurations for an Efficient Human Activity Recognition System. iWOAR 2023: 11:1-11:6 - [i7]Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira:
A Survey of Advanced Computer Vision Techniques for Sports. CoRR abs/2301.07583 (2023) - [i6]Paulo J. S. Ferreira, João Mendes-Moreira, João M. P. Cardoso:
A Study on Hyperparameters Configurations for an Efficient Human Activity Recognition System. CoRR abs/2308.13314 (2023) - 2022
- [c64]Pedro Strecht
Density Estimation in High-Dimensional Spaces: A Multivariate Histogram Approach. ADMA (2) 2022: 266-278 - [c63]Maria Pedroto
Improving the Prediction of Age of Onset of TTR-FAP Patients Using Graph-Embedding Features. EPIA 2022: 183-194 - [c62]Murilo Couceiro, Inês Rito Lima
Tracking Data Visual Representations for Sports Broadcasting Enrichment. icSPORTS 2022: 125-131 - [c61]Solander Patricio Lopes Agostinho, João Mendes-Moreira:
Probabilistic Metric to measure the imbalance in multi-class problems. LIDTA 2022: 151-162 - [c60]Manish Bhanu, Rahul Kumar, Saswata Roy
Graph Multi-Head Convolution for Spatio-Temporal Attention in Origin Destination Tensor Prediction. PAKDD (1) 2022: 459-471 - [i5]Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira:
Valuing Players Over Time. CoRR abs/2209.03882 (2022) - 2021
- [j16]Pedro Strecht
Inmplode: A framework to interpret multiple related rule-based models. Expert Syst. J. Knowl. Eng. 38(6) (2021) - [j15]Kemilly Dearo Garcia, Cláudio Rebelo de Sá, Mannes Poel, Tiago Carvalho
An ensemble of autonomous auto-encoders for human activity recognition. Neurocomputing 439: 271-280 (2021) - [j14]Manish Bhanu
Embedding Traffic Network Characteristics Using Tensor for Improved Traffic Prediction. IEEE Trans. Intell. Transp. Syst. 22(6): 3359-3371 (2021) - [c59]Ahmed Fares
Predicting Predawn Leaf Water Potential up to Seven Days Using Machine Learning. EPIA 2021: 39-50 - [c58]Tiago Mendes-Neves
A Data-Driven Simulator for Assessing Decision-Making in Soccer. EPIA 2021: 687-698 - [c57]Akilu Rilwan Muhammad
Transportation Mode Detection from GPS data: A Data Science Benchmark study. ITSC 2021: 3726-3731 - [c56]André Sousa
Applying Machine Learning to Risk Assessment in Software Projects. PKDD/ECML Workshops (2) 2021: 104-118 - [c55]Pedro Miranda, João Pascoal Faria
An analysis of Monte Carlo simulations for forecasting software projects. SAC 2021: 1550-1558 - [c54]André Sousa, João Pascoal Faria
An Analysis of the State of the Art of Machine Learning for Risk Assessment in Software Projects (S). SEKE 2021: 217-222 - [c53]Diogo Seca
Benchmark of Encoders of Nominal Features for Regression. WorldCIST (1) 2021: 146-155 - [i4]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) - 2020
- [j13]Paulo J. S. Ferreira
kNN Prototyping Schemes for Embedded Human Activity Recognition with Online Learning. Comput. 9(4): 96 (2020) - [c52]João Mendes-Moreira
Reconciling Predictions in the Regression Setting: An Application to Bus Travel Time Prediction. IDA 2020: 313-325 - [c51]Tiago Mendes-Neves
Comparing State-of-the-Art Neural Network Ensemble Methods in Soccer Predictions. ISMIS 2020: 139-149 - [c50]Yassine Baghoussi
Underground Train Tracking using Mobile Phone Accelerometer Data. ITSC 2020: 1-6 - [i3]Diogo Seca
Hierarchical Qualitative Clustering - clustering mixed datasets with critical qualitative information. CoRR abs/2006.16701 (2020)
2010 – 2019
- 2019
- [j12]Diana Gomes
Eating and Drinking Recognition in Free-Living Conditions for Triggering Smart Reminders. Sensors 19(12): 2803 (2019) - [c49]Kemilly Dearo Garcia, Elaine Ribeiro de Faria
Ensemble Clustering for Novelty Detection in Data Streams. DS 2019: 460-470 - [c48]Paulo J. S. Ferreira
Automatic Switching Between Video and Audio According to User's Context. EPIA (2) 2019: 196-207 - [c47]Ricardo M. C. Magalhães
Energy Efficient Smartphone-Based Users Activity Classification. EPIA (2) 2019: 208-219 - [c46]José Carlos Coutinho, João Mendes Moreira, Cláudio Rebelo de Sá
Mining Frequent Distributions in Time Series. IDEAL (2) 2019: 271-279 - [c45]Paulo J. S. Ferreira
An Efficient Scheme for Prototyping kNN in the Context of Real-Time Human Activity Recognition. IDEAL (1) 2019: 486-493 - [c44]José Carlos Coutinho, João Mendes-Moreira, Cláudio Rebelo de Sá:
UnFOOT: Unsupervised Football Analytics Tool. ECML/PKDD (3) 2019: 786-789 - [c43]Kemilly Dearo Garcia, Tiago Carvalho
A Study on Hyperparameter Configuration for Human Activity Recognition. SOCO 2019: 47-56 - 2018
- [c42]Manish Bhanu, Shalini Priya, Sourav Kumar Dandapat, Joydeep Chandra, João Mendes-Moreira
Forecasting Traffic Flow in Big Cities Using Modified Tucker Decomposition. ADMA 2018: 119-128 - [c41]Maria Pedroto
Predicting Age of Onset in TTR-FAP Patients with Genealogical Features. CBMS 2018: 199-204 - [c40]Manish Bhanu, Joydeep Chandra, João Mendes-Moreira
Enhancing traffic model of big cities: Network skeleton & reciprocity. COMSNETS 2018: 121-128 - [c39]Yassine Baghoussi
Updating a robust optimization model for improving bus schedules. COMSNETS 2018: 619-624 - [c38]Kemilly Dearo Garcia, André C. P. L. F. de Carvalho
A Cluster-Based Prototype Reduction for Online Classification. IDEAL (1) 2018: 603-610 - [c37]Paulo Barbosa, Kemilly Dearo Garcia, João Mendes-Moreira
Unsupervised Domain Adaptation for Human Activity Recognition. IDEAL (1) 2018: 623-630 - [c36]Yassine Baghoussi
Instance-Based Stacked Generalization for Transfer Learning. IDEAL (1) 2018: 753-760 - [c35]Maria Pedroto
Impact of Genealogical Features in Transthyretin Familial Amyloid Polyneuropathy Age of Onset Prediction. PACBB 2018: 35-42 - [c34]Pedro Strecht
Generalizing Knowledge in Decentralized Rule-Based Models. DMLE/IOTSTREAMING@PKDD/ECML 2018: 29-36 - [c33]Pedro Strecht
A Framework for Analytical Approaches to Combine Interpretable Models. SIMBig 2018: 182-197 - [c32]Rosana Cavalcante de Oliveira
Agribusiness Intelligence: Grape Production Forecast Using Data Mining Techniques. WorldCIST (3) 2018: 3-8 - [i2]Kemilly Dearo Garcia, Tiago Carvalho, João Mendes-Moreira
A Preliminary Study on Hyperparameter Configuration for Human Activity Recognition. CoRR abs/1810.10956 (2018) - 2017
- [c31]Fábio Pinto, Vítor Cerqueira, Carlos Soares, João Mendes-Moreira:
autoBagging: Learning to Rank Bagging Workflows with Metalearning. AutoML@PKDD/ECML 2017: 21-27 - [i1]Fábio Pinto, Vítor Cerqueira, Carlos Soares
autoBagging: Learning to Rank Bagging Workflows with Metalearning. CoRR abs/1706.09367 (2017) - 2016
- [j11]Luís Moreira-Matias
An online learning approach to eliminate Bus Bunching in real-time. Appl. Soft Comput. 47: 460-482 (2016) - [j10]Luís Moreira-Matias
Time-evolving O-D matrix estimation using high-speed GPS data streams. Expert Syst. Appl. 44: 275-288 (2016) - [c30]Pedro Meneses Henriques, João Mendes-Moreira
Combining recommendation systems with a dynamic weighted technique. ICDIM 2016: 203-208 - [c29]Georgina Esteves, João Mendes-Moreira
Churn perdiction in the telecom business. ICDIM 2016: 254-259 - [c28]Hugo Louro Cardoso, João Mendes-Moreira
Human Activity Recognition by Means of Online Semi-supervised Learning. MDM (Workshops) 2016: 75-77 - [c27]Fábio Pinto, Carlos Soares
Towards Automatic Generation of Metafeatures. PAKDD (1) 2016: 215-226 - [c26]Hugo Louro Cardoso, João Mendes-Moreira:
Improving Human Activity Classification through Online Semi-Supervised Learning. STREAMEVOLV@ECML-PKDD 2016 - [c25]Luís Moreira-Matias, João Gama
Concept Neurons - Handling Drift Issues for Real-Time Industrial Data Mining. ECML/PKDD (3) 2016: 96-111 - [c24]Manuel Mourato, João Mendes-Moreira, Tânia Correia:
Online Failure Prevention from Connected Heating Systems. STREAMEVOLV@ECML-PKDD 2016 - [c23]Fábio Pinto, Carlos Soares
CHADE: Metalearning with Classifier Chains for Dynamic Combination of Classifiers. ECML/PKDD (1) 2016: 410-425 - [c22]Gonçalo Pereira, João Mendes-Moreira
Monitoring Clusters in the Telecom Industry. WorldCIST (2) 2016: 631-640 - 2015
- [j9]João Mendes-Moreira
Improving the accuracy of long-term travel time prediction using heterogeneous ensembles. Neurocomputing 150: 428-439 (2015) - [j8]João Mendes-Moreira
Validating the coverage of bus schedules: A Machine Learning approach. Inf. Sci. 293: 299-313 (2015) - [j7]Luís Moreira-Matias
Improving Mass Transit Operations by Using AVL-Based Systems: A Survey. IEEE Trans. Intell. Transp. Syst. 16(4): 1636-1653 (2015) - [c21]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 - [c20]Jorge Freire de Sousa
Urban Logistics Integrated in a Multimodal Mobility System. ITSC 2015: 89-94 - [c19]Fábio Pinto, Carlos Soares
Pruning Bagging Ensembles with Metalearning. MCS 2015: 64-75 - [c18]João Mendes-Moreira, Luís Moreira-Matias:
On Learning from Taxi GPS Traces (Preamble). DC@PKDD/ECML 2015 - [e1]Adolfo Martínez Usó, João Mendes-Moreira, Luís Moreira-Matias, Meelis Kull, Nicolas Lachiche:
Proceedings of the ECML/PKDD 2015 Discovery Challenges co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015), Porto, Portugal, September 7-11, 2015. CEUR Workshop Proceedings 1526, CEUR-WS.org 2015 [contents] - [d1]Luís Moreira-Matias, Michel Ferreira, João Mendes Moreira:
Taxi Service Trajectory - Prediction Challenge, ECML PKDD 2015. UCI Machine Learning Repository, 2015 - 2014
- [j6]Pedro Henriques Abreu
Improving a simulated soccer team's performance through a Memory-Based Collaborative Filtering approach. Appl. Soft Comput. 23: 180-193 (2014) - [j5]Pedro Henriques Abreu
Using model-based collaborative filtering techniques to recommend the expected best strategy to defeat a simulated soccer opponent. Intell. Data Anal. 18(5): 973-991 (2014) - [c17]Fábio Pinto, Carlos Soares
An Empirical Methodology to Analyze the Behavior of Bagging. ADMA 2014: 199-212 - [c16]Pedro Strecht
Merging Decision Trees: A Case Study in Predicting Student Performance. ADMA 2014: 535-548 - [c15]Fábio Pinto, Carlos Soares, João Mendes-Moreira:
A Framework To Decompose And Develop Metafeatures. MetaSel@ECAI 2014: 32-36 - [c14]Luís Moreira-Matias, João Gama
An Incremental Probabilistic Model to Predict Bus Bunching in Real-Time. IDA 2014: 227-238 - [c13]Luís Moreira-Matias
On Predicting a Call Center's Workload: A Discretization-Based Approach. ISMIS 2014: 548-553 - [c12]Luís Moreira-Matias
An online learning framework for predicting the taxi stand's profitability. ITSC 2014: 2009-2014 - 2013
- [j4]Pedro Henriques Abreu
Using Multivariate Adaptive Regression Splines in the Construction of Simulated Soccer Team's Behavior Models. Int. J. Comput. Intell. Syst. 6(5): 893-910 (2013) - [j3]Luís Moreira-Matias
Predicting Taxi-Passenger Demand Using Streaming Data. IEEE Trans. Intell. Transp. Syst. 14(3): 1393-1402 (2013) - [c11]Luís Moreira-Matias
On Predicting the Taxi-Passenger Demand: A Real-Time Approach. EPIA 2013: 54-65 - [c10]Luís Moreira-Matias, Ricardo Fernandes, João Gama, Michel Ferreira, João Mendes-Moreira, Luís Damas:
On Recommending Urban Hotspots to Find Our Next Passenger. UDM@IJCAI 2013: 17 - 2012
- [j2]João Mendes-Moreira
Ensemble approaches for regression: A survey. ACM Comput. Surv. 45(1): 10:1-10:40 (2012) - [j1]João Mendes-Moreira
Comparing state-of-the-art regression methods for long term travel time prediction. Intell. Data Anal. 16(3): 427-449 (2012) - [c9]Alípio Mário Jorge
Finding Interesting Contexts for Explaining Deviations in Bus Trip Duration Using Distribution Rules. IDA 2012: 139-149 - [c8]Luís Moreira-Matias
Online Predictive Model for Taxi Services. IDA 2012: 230-240 - [c7]Luís Moreira-Matias
Bus Bunching Detection by Mining Sequences of Headway Deviations. ICDM 2012: 77-91 - [c6]Luís Moreira-Matias
Text Categorization Using an Ensemble Classifier Based on a Mean Co-association Matrix. MLDM 2012: 525-539 - [c5]Luís Moreira-Matias
An online recommendation system for the taxi stand choice problem (Poster). VNC 2012: 173-180 - 2010
- [c4]Luís Matias, João Gama
Validation of both number and coverage of bus schedules using AVL data. ITSC 2010: 131-136
2000 – 2009
- 2009
- [c3]João Mendes-Moreira
Ensemble Learning: A Study on Different Variants of the Dynamic Selection Approach. MLDM 2009: 191-205 - [c2]João Mendes-Moreira
The Effect of Varying Parameters and Focusing on Bus Travel Time Prediction. PAKDD 2009: 689-696 - 2006
- [c1]João Mendes-Moreira
Improving SVM-Linear Predictions Using CART for Example Selection. ISMIS 2006: 632-641
Coauthor Index
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last updated on 2024-10-07 21:18 CEST by the dblp team
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