Books
2014(1 publication)
[publication]Noel Lopes and Ribeiro, B. , "Machine Learning for Adaptive Many-Core Machines - A Practical Approach",  Studies in Big Data Series, Ed. Springer, ISBN 978-3-319-06937-1",  vol. 7, 2014
[citation][year=2015]J?drzejowicz, J., & J?drzejowicz, P. (2015). A Hybrid Distance-Based and Naive Bayes Online Classifier. In Computational Collective Intelligence (pp. 213-222). Springer International Publishing.

Journal Articles
2020(1 publication)
[publication]Uribe-Hurtado, A. and Alzate, M.O. and Noel Lopes and Ribeiro, B. , "GPU-based fast clustering via $K$-Centres and $k$-NN mode seeking for geospatial industry applications", Computers in Industry, Elsevier (in press), 2020

2017(1 publication)
[publication]Lee, W.P. and Hasan, S. and Shamsuddin, S.M. and Noel Lopes , "GPUMLib: Deep Learning SOM Library for Surface Reconstruction", International Journal of Advances in Soft Computing & Its Applications,  vol. 9,  pp. 1-16, 2017

2016(1 publication)
[publication]Mustapha, I.B. and Hasan, S. and Shamsuddin, S.M. and Noel Lopes and Leng, W.Y. , "GPU-Based Multiple Back Propagation for Big Data Problems", International Journal of Advances in Soft Computing & Its Applications,  vol. 8,  pp. 82-93, 2016

2014(2 publications)
[publication]Noel Lopes and Ribeiro, B. , "Towards Adaptive Learning with Improved Convergence of Deep Belief Networks on Graphics Processing Units", Pattern Recognition, Elsevier ,  vol. 47,  pp. 114-127, 2014
[citation][year=2016]Luo, J., & Gao, H. (2016). Deep Belief Networks for Fingerprinting Indoor Localization Using Ultrawideband Technology. International Journal of Distributed Sensor Networks, 2016.
[citation][year=2015]Xu, Q., Jiang, S., Huang, W., Duan, L., & Xu, S. Multi-feature fusion based spatial pyramid deep neural networks image classification. Computer Modelling & New Technologies, 17, 207-212 (2015).
[citation][year=2015]Li, T., Dou, Y., Jiang, J., Wang, Y., & Lv, Q. (2015, July). Optimized deep belief networks on CUDA GPUs. In Neural Networks (IJCNN), 2015 International Joint Conference on (pp. 1-8). IEEE.
[citation][year=2015]Li, Z. Z., Zhong, Z. Y., & Jin, L. W. (2015). Identifying Best Hyperparameters for Deep Architectures Using Random Forests. In Learning and Intelligent Optimization (pp. 29-42). Springer International Publishing.
[citation][year=2015]Lv, Q., Dou, Y., Niu, X., Xu, J., Xu, J., & Xia, F. (2015). Urban Land Use and Land Cover Classification Using Remotely Sensed SAR Data through Deep Belief Networks. Journal of Sensors, 2015.
[citation][year=2015]Qiu, J., Liang, W., Zhang, L., Yu, X., & Zhang, M. (2015). The early-warning model of equipment chain in gas pipeline based on DNN-HMM. Journal of Natural Gas Science and Engineering, 27, 1710-1722.
[citation][year=2015]Wlodarczak, P., Soar, J., & Ally, M. (2015, October). Multimedia data mining using deep learning. In Digital Information Processing and Communications (ICDIPC), 2015 Fifth International Conference on (pp. 190-196). IEEE.
[citation][year=2015]Gao Qiang, Yang Wu , & Li Qian . (2015). DBN image classification based on the spatial information quickly train the model . Journal of System Simulation , ( 3 ) , 549-558 .
[citation][year=2014]Fang, H., & Hu, C. (2014, July). Recognizing human activity in smart home using deep learning algorithm. In Control Conference (CCC), 2014 33rd Chinese (pp. 4716-4720). IEEE.
[citation][year=2014]Parada, P. Peso, et al. "A quantitative comparison of blind C 50 estimators." Acoustic Signal Enhancement (IWAENC), 2014 14th International Workshop on. IEEE, 2014.

[publication]Hasan, S. and Shamsuddin, S.M. and Noel Lopes , "Machine Learning Big Data Framework and Analytics for Big Data Problems", Int. J. Advance Soft Compu. Appl (IJASCA),  vol. 6, 2014
[citation][year=2015]Wienhofen, L., Mathisen, B. M., & Roman, D. (2015). Empirical Big Data Research: A Systematic Literature Mapping. arXiv preprint arXiv:1509.03045.
[citation][year=2015]Ali, A., Shamsuddin, S. M., & Ralescu, A. L. (2015). Classification with class imbalance problem: A Review. Int. J. Advance Soft Compu. Appl, 7(3).

2012(2 publications)
[publication]Noel Lopes and Ribeiro, B. , "Towards a Hybrid NMF-based Neural Approach for Face Recognition on GPUs", International Journal of Data Mining, Modelling and Management (IJDMMM),  vol. 4,  pp. 138-155, 2012

[publication]Noel Lopes and Ribeiro, B. , "Handling Missing Values via a Neural Selective Input Model ", Neural Network World  ,  vol. 22,  pp. 357-370, 2012

2011(2 publications)
[publication]Noel Lopes and Ribeiro, B. , "GPUMLib: An Efficient Open-Source GPU Machine Learning Library", International Journal of Computer Information Systems and Industrial Management Applications,  vol. 3,  pp. 355-362, 2011
[citation][year=2016]Huang, W. B., & Sun, F. C. (2016). Building feature space of extreme learning machine with sparse denoising stacked-autoencoder. Neurocomputing, 174, 60-71.
[citation][year=2016]Mi, P. (2016). GPU Based Methods for Interactive Information Visualization of Big Data (Doctoral dissertation, Virginia Tech).
[citation][year=2015]Dong, Y., Xue, M., Zheng, X., Wang, J., Qi, Z., & Guan, H. (2015). Boosting GPU virtualization performance with hybrid shadow page tables. In 2015 USENIX Annual Technical Conference (USENIX ATC 15) (pp. 517-528).
[citation][year=2015]Smithrud, J. M., McElroy, P., & Andonie, R. (2015). Massively Parallel kNN using CUDA on Spam-Classification. In MAICS (pp. 175-180).
[citation][year=2015]Ashari, A., Tatikonda, S., Boehm, M., Reinwald, B., Campbell, K., Keenleyside, J., & Sadayappan, P. (2015, January). On optimizing machine learning workloads via kernel fusion. In ACM SIGPLAN Notices (Vol. 50, No. 8, pp. 173-182). ACM.
[citation][year=2015]Huang, Wen-bing, and Fu-chun Sun. "A Deep and Stable Extreme Learning Approach for Classification and Regression." Proceedings of ELM-2014 Volume 1. Springer International Publishing, 2015. 141-150.
[citation][year=2014]Wu, Zheng Yi, "Portable GPU-Based Artificial Neural Networks For Data-Driven Modeling" (2014). Proceedings of the 11th International Conference on Hydroinformatics. CUNY Academic Works.
[citation][year=2014]Le-le Cao, W. B. H., & Sun, F. C. (2014). A Deep and Stable Extreme Learning Approach for Classification and Regression?. Proceedings of ELM-2014 Volume 1: Algorithms and Theories, 3, 141.
[citation][year=2014]Codreanu, Valeriu, et al. "Evaluating automatically parallelized versions of the support vector machine." Concurrency and Computation: Practice and Experience (2014).
[citation][year=2013]Kumar, D. P. (2013). Intra Frame Luma Prediction using Neural Networks in HEVC (Doctoral dissertation, UNIVERSITY OF TEXAS AT ARLINGTON).
[citation][year=2012]Comparative Study on Use of Mobile Videos in Elementary and Middle School
P Tuomi, J Multisilta - mirlabs.org
[citation][year=2012]A Distributed Data Mining Framework Accelerated with Graphics Processing Units
NL Tran, Q Dugauthier, S Skhiri - euranova.eu
[citation][year=2012]Generalized GPU-based Artificial Neural Network Surrogate Model for Extended Period Hydraulic Simulation
M Behandish, ZY Wu - ascelibrary.org
[citation][year=2012]Jansson, Karl. "Performance study of using the Direct Compute API for implementing Support vector machines on GPUs." (2012).

[publication]Noel Lopes and Ribeiro, B. , "An Evaluation of Multiple Feed-Forward Networks on GPUs", International Journal of Neural Systems (IJNS),  vol. 21,  pp. 31-47, 2011
[citation][year=2016]Fazanaro, F. I., Soriano, D. C., Suyama, R., Madrid, M. K., de Oliveira, J. R., Muñoz, I. B., & Attux, R. (2016). Numerical characterization of nonlinear dynamical systems using parallel computing: The role of GPUs approach. Communications in Nonlinear Science and Numerical Simulation, 37, 143-162.
[citation][year=2015]Zhao, L., Lu, J., Chen, D. F., & Wang, W. (2015). The Research on the Multi-Sensor Information Fusion Identifying of Alcohol based on Modified PCA and ANN. International Journal of u-and e-Service, Science and Technology, 8(8), 55-64.
[citation][year=2015]Wang, Y., Tang, P., An, H., Liu, Z., Wang, K., & Zhou, Y. (2015, November). Optimization and Analysis of Parallel Back Propagation Neural Network on GPU Using CUDA. In Neural Information Processing (pp. 156-163). Springer International Publishing.
[citation][year=2014]Menke, Nathan Benjamin, et al. "A retrospective analysis of the utility of an artificial neural network to predict ED volume." The American journal of emergency medicine 32.6 (2014): 614-617.
[citation][year=2013]S. Melih Nigdeli and M. Hasan Boduroglu. Active tendon control of torsionally irregular structures under near-fault ground motion excitation. Computer-Aided Civil and Infrastructure Engineering, 28(9):718–736, 2013.
[citation][year=2013]F. Hejazi, I. Toloue, M. S. Jaafar, and J. Noorzaei. Optimization of earthquake energy dissipation system by genetic algorithm. Computer-Aided Civil and Infrastructure Engineering, 28(10):796–810, 2013.
[citation][year=2013]Nigdeli, S. Melih, and M. Hasan Boduro?lu. "Active Tendon Control of Torsionally Irregular Structures under Near?Fault Ground Motion Excitation." Computer?Aided Civil and Infrastructure Engineering 28.9 (2013): 718-736.
[citation][year=2012]Karl Pauwels and Marc M. Van Hulle. Head-centric disparity and epipolar geometry estimation from a population of binocular energy neurons. International Journal of Neural Systems, 22(3), 2012.
[citation][year=2012]Álvaro Herrero, Urko Zurutuza, and Emilio Corchado. A neural-visualization IDS for honeynet data. International Journal of Neural Systems, 22(2), 2012.
[citation][year=2012]M. A. H. Akhand and K. Murase. Ensembles of neural networks based on the alteration of input feature values. International Journal of Neural Systems, 22(1):77-87, 2012.
[citation][year=2012]Juan Pablo Balarini, Sergio Nesmachnow, and Martín Rodríguez. Facial recognition using neural networks over GPGPU. CLEI Electronic Journal, 15(3), 2012.

2003(1 publication)
[publication]Noel Lopes and Ribeiro, B. , "An efficient Gradient-Based Learning Algorithm Applied to Neural Networks with Selective Actuation Neurons", Neural, Parallel and Scientific Computations,  vol. 11,  pp. 253-272, 2003
[citation][year=2015]Paul Phillips, Krystin Zigan, Maria Manuela Santos Silva, Roland Schegg, The interactive effects of online reviews on the determinants of Swiss hotel performance: A neural network analysis, Tourism Management, Volume 50, October 2015, Pages 130-141, ISSN 0261-5177, http://dx.doi.org/10.1016/j.tourman.2015.01.028.
[citation][year=2015]Moutinho, Luiz; Caber, Meltem; Silva, Maria Manuela Santos; Albayrak, Tahir. Impact of Group Package Tour Dimensions on Customer Satisfaction (an ANNs Application), Tourism Analysis, Volume 20, Number 6, 2015, pp. 619-629(11). DOI: http://dx.doi.org/10.3727/108354215X14464845877913
[citation][year=2015]Silva, Maria, and Luiz Moutinho. "Artificial Neural Networks in Marketing." Wiley Encyclopedia of Management (2015).
[citation][year=2015]Haryanto, Jony Oktavian, Manuela Silva, and Luiz Moutinho. "Neural network approach to understanding the children’s market." European Journal of Marketing 49.3/4 (2015): 372-397.
[citation][year=2015]K.Karthikeyan, Sayantani Basu. Neural Network Technique in Data Mining for Prediction of Earth Quake. International Journal Of Pharmacy & Technology. Vol. 7, Issue 3, pp. 9543-9554 (2015)
[citation][year=2014]Balázs Czél, Keith A. Woodbury, Gyula Gróf, Simultaneous estimation of temperature-dependent volumetric heat capacity and thermal conductivity functions via neural networks, International Journal of Heat and Mass Transfer, Volume 68, January 2014, Pages 1-13

Tereza Maria de Oliveira, Distância Psíquica e seus Efeitos sobre o Fluxo de Exportações dos Estados Brasileiros, PhD thesis, Faculty of Economy, University of Coimbra, 2014.
[citation][year=2013]Supeni, E. E. and Epaarachchi, J. A. and Islam, M. M. and Lau, K. T. (2013) Development of artificial neural network model in predicting performance of the smart wind turbine blade. In: 3rd Malaysian Postgraduate Conference (MPC 2013), 4-5 Jul 2013, Sydney, Australia.
[citation][year=2012]Carlo Cravero, Paolo Macelloni and Giuseppe Briasco. Three-Dimensional Design Optimization of Multistage Axial Flow Turbines Using a RSM Based Approach. In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition, Volume 8: Turbomachinery, Parts A, B, and C, 2012
[citation][year=2012]Milindanath Samarasinghe and Waseem Al-Hawani, Short-term Forecasting of Electricity Consumption using Gaussian Processes, MSc thesis, University of Agder, Norway, 2012
[citation][year=2012]Gelso Pedrosi Filho, Determinantes do Envolvimento de Pesquisadores Acadêmicos Brasileiros na Criação de Spin-Off, PhD thesis, Faculty of Economy, University of Coimbra, 2012
[citation][year=2012]Yi Wu Zheng and Behandish Morad. Real-time pump scheduling using genetic algorithm and artificial neural network based on graphics processing unit. In 14th Water Distribution Systems Analysis Conference (WDSA 2012), 2012.
[citation][year=2012]Yi Wu Zheng and Behandish Morad. Comparing methods of parallel genetic optimization for pump scheduling using hydraulic model and GPU-based ANN metamodel. In 14th Water Distribution Systems Analysis Conference (WDSA 2012), 2012.
[citation][year=2011]Saleheen, Mushfiq U., Embedded hardware architecture for multi-parameter physiological signal monitoring, MSc thesis, University of Illinois at Urbana-Champaign, 2011
[citation][year=2011]Laurentiu Bucur and Adina Florea. Techniques for prediction in chaos: A comparative study on financial data. U.P.B. Sci. Bull., Series C, 73(3):17–32, 2011.
[citation][year=2011]Roli Pradhan, K. K. Pathak, and V. P. Singh. Application of neural network in prediction of financial viability. International Journal of Soft Computing and Engineering (IJSCE), 1(2):41-45, 2011.
[citation][year=2011]SA Zapryagaev and AA Karpushin. Calculation and learning artificial neural networks direct distribution by GPUs. VSU HERALD SERIES: System Analysis and Information Technologies, (1):157-164, 2011.
[citation][year=2011]Laurentiu Bucur, Sparse Kernel Machines and High Performance Computing, PhD thesis, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 2011.
[citation][year=2010]Mushfiq U. Saleheen, Homa Alemzadeh, Ajay M. Cheriyan, Zbigniew Kalbarczyk and Ravishankar K. Iyer, "An Efficient Embedded Hardware for High Accuracy Detection of Epileptic Seizures", 3rd International Conference on Biomedical Engineering and Informatics (BMEI 2010), pp. 1889-1896, 2010.
[citation][year=2010]Laurentiu Bucur, Adina Florea, "Exploring Chaos with Sparse Kernel Machines," 12th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, pp.239-242, 2010
[citation][year=2010]Xinliang Yu, "Prediction of Q-e Parameters of Monomers in Free-radical Copolymerizations", ACTA CHIMICA SINICA,vol. 68, no. 22, pp 2264-2272, 2010
[citation][year=2009]Market orientation and performance: modelling a neural network,  Manuela Silva, Luiz Moutinho, Arnaldo Coelho, Alzira Marques,  European Journal of Marketing
Year: 2009 Volume: 43 Issue: 3/4 Page: 421 - 437
[citation][year=2008]Sandra Holanda, "Os antecedentes da lealdade no contexto bancário: um estudo com clientes do segmento empresa", PHd thesis, University of Coimbra, 2008

Conference Articles
2017(1 publication)
[publication]Noel Lopes and Ribeiro, B. , "Novel Trends in Scaling Up Machine Learning Algorithms", in 16th IEEE International Conference On Machine Learning And Applications. ICMLA 2017, 2017

2016(1 publication)
[publication]Noel Lopes and Ribeiro, B. , "Trading off Distance Metrics vs Accuracy in Incremental Learning Algorithms", in IberoAmerican  Congress on Pattern Recognition, LNCS, Springer, 2016

2015(3 publications)
[publication]Ribeiro, B. and Noel Lopes and Silva, C. , "Learning the Hash Code with Generalised Regression Neural Networks for Biometric Data Retrieval", in International Joint Conference on Neural Networks (IJCNN'15), 2015

[publication]Noel Lopes and Ribeiro, B. , "Novel Trends in Scaling Up Machine Learning Algorithms", in Proceedings of European Conference on Machine Learning (ECML), CEUR Workshop on Parallel and Distributed Computing, Porto, September, 2015

[publication]Noel Lopes and Ribeiro, B. , "On the Impact of Distance Metrics in Instance-Based Learning Algorithms", in Pattern Recognition and Image Analysis,Lecture Notes in Computer Science (LNCS), Vol 9117,Springer International Publishing, 2015

2014(2 publications)
[publication]Ribeiro, B. and Noel Lopes and João Gonçalves , "Signature Identification via Efficient Feature Selection and GPU-based  SVM Classifier", in IEEE International Joint Conference on Neural Networks (IJCNN), 2014
[citation][year=2015]Yin, Z., Liu, J., Krueger, M., & Gao, H. (2015, July). Introduction of SVM algorithms and recent applications about fault diagnosis and other aspects. In Industrial Informatics (INDIN), 2015 IEEE 13th International Conference on (pp. 550-555). IEEE.

[publication]João Gonçalves and Noel Lopes and Ribeiro, B. , "Handwritten Signature Matching using GPUMLib", in 20th edition of the Portuguese Conference on Pattern Recognition - RECPAD 2014, 2014

2013(2 publications)
[publication]Ribeiro, B. and Noel Lopes , "Extreme Learning Classifier With Deep Concepts", in 18th Iberoamerican Congress on Pattern Recognition (CIARP 2013), LNCS; Springer, 2013
[citation][year=2016]Huang, W. B., & Sun, F. C. (2016). Building feature space of extreme learning machine with sparse denoising stacked-autoencoder. Neurocomputing, 174, 60-71.
[citation][year=2015]Huang, Wen-bing, and Fu-chun Sun. "A Deep and Stable Extreme Learning Approach for Classification and Regression." Proceedings of ELM-2014 Volume 1. Springer International Publishing, 2015. 141-150.
[citation][year=2015]Zeng, Y., Xu, X., Fang, Y., & Zhao, K. (2015, June). Traffic sign recognition using extreme learning classifier with deep convolutional features. In The 2015 international conference on intelligence science and big data engineering (IScIDE 2015), Suzhou, China.
[citation][year=2015]Chen, L., Qu, H., Zhao, J., Chen, B., & Principe, J. C. (2015). Efficient and robust deep learning with Correntropy-induced loss function. Neural Computing and Applications, 1-13.
[citation][year=2014]Andrea Carolina Peres Kulaif, Técnicas de Regularização para Máquinas de Aprendizado Extremo, MSc thesis, Faculdade de Engenharia elétrica e da Computação, Universidade Estadual De Campinas, 2014
[citation][year=2014]Le-le Cao, W. B. H., & Sun, F. C. (2014). A Deep and Stable Extreme Learning Approach for Classification and Regression?. Proceedings of ELM-2014 Volume 1: Algorithms and Theories, 3, 141.

[publication]Hasan, S. and Shamsuddin, S.M. and Noel Lopes , "Soft computing methods for big data problems", in 2013 Symposium on GPU Computing and Applications, 2013
[citation][year=2015]Tsai, C. W., Lai, C. F., Chao, H. C., & Vasilakos, A. V. (2015). Big data analytics: a survey. Journal of Big Data, 2(1), 1-32.

2012(5 publications)
[publication]Noel Lopes and Pereira, C. and Ribeiro, B. and António Dourado , "An Incremental Hypersphere Learning Framework for Protein Membership Prediction", in International Conference on Hybrid Artificial Intelligence Systems, LNCS 7208, pp. 429-439, 2012
[citation][year=2013]Chen, Y. H., et al. "A Hybrid Text Classification Method Based on K-Congener-Nearest-Neighbors and Hypersphere Support Vector Machine." Information Technology and Applications (ITA), 2013 International Conference on. IEEE, 2013.

[publication]Noel Lopes and Ribeiro, B. , "Restricted Boltzmann Machines and Deep Belief Networks on Multi-Core Processors", in IEEE World Congress on Computational Intelligence (WCCI 2012), IEEE, Brisbane, Australia (DOI: 10.1007/978-3-642-32639-4_90), 2012
[citation][year=2016]Patrawut Ruangkanokmas, Tiranee Achalakul and Khajonpong Akkarajitsakul. "Deep Belief Networks with Feature Selection for Sentiment Classification". 7th International Conference on Intelligent Systems, Modelling and Simulation (2016).
[citation][year=2016]Brito, R., Fong, S., Cho, K., Song, W., Wong, R., Mohammed, S., & Fiaidhi, J. (2016). GPU-enabled back-propagation artificial neural network for digit recognition in parallel. The Journal of Supercomputing, 1-19.
[citation][year=2015]Li, T., Dou, Y., Jiang, J., Wang, Y., & Lv, Q. (2015, July). Optimized deep belief networks on CUDA GPUs. In Neural Networks (IJCNN), 2015 International Joint Conference on (pp. 1-8). IEEE.
[citation][year=2015]Satoshi Masaki and Sato Kosin pair. "Learning faster DBN by the learning data parallelism with MPI". Information Processing Society 77th Annual National Convention 3 (2015): 08.
[citation][year=2014]Ahn, Byungik. "Computation of deep belief networks using special-purpose hardware architecture." Neural Networks (IJCNN), 2014 International Joint Conference on. IEEE, 2014.
[citation][year=2014]Thompson, Elizabeth A., and Timothy R. Anderson. "A CUDA implementation of the Continuous Space Language Model." The Journal of Supercomputing 68.1 (2014): 65-86.
[citation][year=2013]Zhu, Yun; Zhang, Yanqing; Pan, Yi, "Large-scale restricted boltzmann machines on single GPU", IEEE International Conference on Big Data, pp.169-174, 2013
[citation][year=2013]Popovi?, B., Ostrogonac, S., Deli?, V., Janev, M., & Stankovi?, I. (2013). Deep architectures for automatic emotion recognition based on lip shape. In 12th International Scientific Professional Symposium INFOTEH-JAHORINA, Jahorina, Bosnia and Herzegovina (pp. 939-943).
[citation][year=2013]Xueshao Fei, Song Yan and Dai Lirong "Fast training method based on multi-GPU deep neural networks". Journal of Tsinghua University : Natural Science Edition 6 (2013): 745-748.

[publication]Noel Lopes and Ribeiro, B. , "Improving convergence of restricted Boltzmann machines via a learning adaptive step size", in 17th Iberoamerican Congress on Pattern Recognition (CIARP 2012), LNCS vol. 7441, pp: 511-518, 2012
[citation][year=2015]Gao Qiang, Yang Wu , & Li Qian . (2015). DBN level trend and its fault recognition in aerial imagery applications. Instrumentation Technology, 36 ( 6 ) , 1267-1274 .

[publication]João Gonçalves and Noel Lopes and Ribeiro, B. , "Multi-Thread Support Vector Machines for Pattern Recognition", in International Conference on Neural Information Processing, Part III, LNCS 7665, pp. 228--235. Springer, Heidelberg, 2012

[publication]Noel Lopes and Ribeiro, B. and João Gonçalves , "Restricted Boltzmann machines and deep belief networks on multi-core processors", in The 2012 international joint conference on neural networks (IJCNN), 2012

2011(6 publications)
[publication]Noel Lopes and Ribeiro, B. , "A Robust Learning Model for Dealing with Missing Values in Many-Core Architectures", in ICANNGA'11 - International Conference on Adaptive and Natural Computing Algorithms, pp. 108-117, 2011
[citation][year=2014]Oliveira, E. V. (2014). A percepção dos TOCs sobre o normativo contabilístico das Entidades do Setor Não Lucrativo (Doctoral dissertation, Instituto Superior de Economia e Gestão).
[citation][year=2013]Mohammadreza Baharani, Hamid Noori, Mohammad Aliasgari, and Zain Navabi. High-level design space exploration of locally linear neuro-fuzzy models for embedded systems. Fuzzy Sets and Systems, 2013.

[publication]Ribeiro, B. and Quintas, R. and Noel Lopes , "Evaluation of a Resource Allocating Network with Long Term Memory using GPU", in Proc Int Conf on Adaptive and Natural Computing Algorithms, pp 41-47, Part II, LNCS 6594, 2011, 2011
[citation][year=2013]Chunlei Chen, Dejun Mu, Huixiang Zhang, and Wei Hu. Towards a moderate granularity incremental clustering algorithm for GPU. In 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), pages 194–201, 2013.
[citation][year=2012]Chunlei Chen, Dejun Mu, Huixiang Zhang, and Bo Hong. A GPU-accelerated approximate algorithm for incremental learning of Gaussian mixture model. In IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum, pages 1937–1943, 2012.

[publication]Noel Lopes and Ribeiro, B. , "A Fast Optimized Semi-Supervised Non-Negative Matrix Factorization Algorithm", in IEEE  International Joint Conference on Neural Networks (IJCNN), 2011
[citation][year=2015]Wu, Q., Tan, M., Li, X., Min, H., & Sun, N. (2015). NMFE-SSCC: Non-negative matrix factorization ensemble for semi-supervised collective classification. Knowledge-Based Systems, 89, 160-172.

[publication]Ribeiro, B. and Noel Lopes , "Deep Belief Networks for Financial Prediction", in B.-L. Lu, L. Zhang, and J. Kwok (Eds.):ICONIP 2011, Part III, LNCS 7064, pp. 766--773. Springer, Heidelberg (2011), 2011
[citation][year=2015]Fagiani, M., Squartini, S., Gabrielli, L., Spinsante, S., & Piazza, F. (2015). A review of datasets and load forecasting techniques for smart natural gas and water grids: Analysis and experiments. Neurocomputing, 170, 448-465.
[citation][year=2015]Yeo, M., Fletcher, T., & Shawe-Taylor, J. (2015). Machine Learning in Fine Wine Price Prediction. Journal of Wine Economics, 10(02), 151-172.
[citation][year=2015]Hoteit, T. (2015). Effects of Investor Sentiment Using Social Media on Corporate Financial Distress.
[citation][year=2012]Milan Halabuk. Testing the hierarchical neural network DBN in invariant object recognition. Master's thesis, Comenius University in Bratislava, 2012.

[publication]Noel Lopes and Ribeiro, B. , "An Incremental Class Boundary Preserving Hypersphere Classifier", in B.-L. Lu, L. Zhang, and J. Kwok (Eds.):ICONIP 2011, Part II, LNCS 7063, pp. 690--699. Springer, Heidelberg (2011), 2011
[citation][year=2015]Xia, W., Mita, Y., & Shibata, T. (2015). A Nearest Neighbor Classifier Employing Critical Boundary Vectors for Efficient On-Chip Template Reduction.

[publication]Noel Lopes and Ribeiro, B. , "Incremental Learning for Non-Stationary Patterns", in 17th edition of the Portuguese Conference on Pattern Recognition - RECPAD 2011, 2011

2010(7 publications)
[publication]Noel Lopes and Ribeiro, B. , "Stochastic GPU-based Multithread Implementation of Multiple Back-Propagation", in Second International Conference on Agents and Artificial Intelligence (ICAART 2010), pp. 271-276, 2010

[publication]Silva, C. and Ribeiro, B. and Noel Lopes , "Improving Recall Values in Breast Cancer Diagnosis with Incremental Background Knowledge", in IEEE World Congress on Computational Intelligence (WCCI 2010), 2010
[citation][year=2013]Somdatta Patra and Mr. GourSundarMitra Thakur. A proposed neuro-fuzzy model for adult asthma disease diagnosis. Computer Science & Information Technology (CS & IT), 3(2):191–205, 2013.

[publication]Noel Lopes and Ribeiro, B. , "A Strategy for Dealing With Missing Values by Using Selective Activation Neurons in a Multi-Topology Framework", in IEEE World Congress on Computational Intelligence (WCCI 2010), 2010
[citation][year=2015]K.Karthikeyan, Sayantani Basu. Neural Network Technique in Data Mining for Prediction of Earth Quake. International Journal Of Pharmacy & Technology. Vol. 7, Issue 3, pp. 9543-9554 (2015)
[citation][year=2012]Andréa Martiniano da Silva. Aplicação de técnica da mineração de dados na identificação do perfil de empregados absenteístas e presenteístas em uma empresa de courier da cidade de são paulo. Master’s thesis, Universidade Nove de Julho – UNINOVE, 2012.

[publication]Ribeiro, B. and Noel Lopes and Silva, C. , "High-Performance Bankruptcy Prediction Model using Graphics Processing Units", in IEEE World Congress on Computational Intelligence (WCCI 2010), 2010
[citation][year=2014]Gaspar-Cunha, A., Recio, G., Costa, L., & Estébanez, C. (2014). Self-adaptive MOEA feature selection for classification of bankruptcy prediction data. The Scientific World Journal, 2014.
[citation][year=2014]Kumar, R., & Cheema, A. K. (2014). GPU Implementation of a Deep Learning Network for Financial Prediction. The International Journal of Science and Technoledge, 2(5), 374.
[citation][year=2013]Antonio Gaspar-Cunha, Gustavo Recio, L. Costa, and Cesar Estebanez, Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data, The Scientific World Journal, 2013
[citation][year=2013]Langdon, W. B. (2013). Large-Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units. In Massively Parallel Evolutionary Computation on GPGPUs (pp. 311-347). Springer Berlin Heidelberg.
[citation][year=2012]Sabine McConnell, Robert Sturgeon, Gregory Henry, Andrew Mayne and Richard Hurley, Scalability of Self-organizing Maps on a GPU cluster using OpenCL and CUDA, Journal of Physics: Conference Series, vol. 341, 2012.
[citation][year=2012]Li Weiming . ( 2012 ) . In the hierarchical growth patterns from network mapping and trajectory analysis Construction of Enterprise Financial Crisis Prediction Model .
[citation][year=2011]W. B. Langdon, "Graphics Processing Units and Genetic Programming: An overview", Soft Computing - A Fusion of Foundations, Methodologies and Applications, vol. 15, no. 8, pp. 1657-1669, 2011
[citation][year=2010]William B. Langdon, Large Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units, Parallel and Distributed Computational Intelligence Studies in Computational Intelligence, vol. 269, pp 113-141, 2010

[publication]Noel Lopes and Ribeiro, B. and Quintas, R. , "GPUMLib: A New Library to Combine Machine Learning Algorithms with Graphics Processing Units", in 10th International Conference on Hybrid Intelligent Systems (IEEE), 2010
[citation][year=2015]Strnad, D., & Nerat, A. (2015). Parallel construction of classification trees on a GPU. Concurrency and Computation: Practice and Experience.
[citation][year=2015]Ashari, A., Tatikonda, S., Boehm, M., Reinwald, B., Campbell, K., Keenleyside, J., & Sadayappan, P. (2015, January). On optimizing machine learning workloads via kernel fusion. In ACM SIGPLAN Notices (Vol. 50, No. 8, pp. 173-182). ACM.
[citation][year=2014]Wu, Zheng Yi, "Portable GPU-Based Artificial Neural Networks For Data-Driven Modeling" (2014). Proceedings of the 11th International Conference on Hydroinformatics. CUNY Academic Works.
[citation][year=2013]M. Behandish. Generalized GPU-based artificial neural network surrogate model for extended period hydraulic simulation. In World Environmental and Water Resources Congress 2013, pages 716–731, 2013.
[citation][year=2013]Mohammadreza Baharani, Hamid Noori, Mohammad Aliasgari, and Zain Navabi. High-level design space exploration of locally linear neuro-fuzzy models for embedded systems. Fuzzy Sets and Systems, 2013.
[citation][year=2012]Karl Jansson. Performance study of using the direct compute API for implementing support vector machines on GPUs. Department of Computer and Systems Sciences, Stockholm University, 2012.
[citation][year=2010]Art Gresham, Literature Review: Blind Audio Source Separation on the GPU, 2010.

[publication]Noel Lopes and Ribeiro, B. , "Non-Negative Matrix Factorization Implementation Using Graphic Processing Units", in 11th International Conference on Intelligent Data Engineering and Automated Learning, LNCS 6283, Springer, pp. 275-283, 2010
[citation][year=2015]Rossi, R. A., & Ahmed, N. K. (2015). Role discovery in networks. Knowledge and Data Engineering, IEEE Transactions on, 27(4), 1112-1131.
[citation][year=2015]Mejía-Roa, E., Tabas-Madrid, D., Setoain, J., García, C., Tirado, F., & Pascual-Montano, A. (2015). NMF-mGPU: non-negative matrix factorization on multi-GPU systems. BMC bioinformatics, 16(1), 1.
[citation][year=2014]Rossi, Ryan A., and Nesreen K. Ahmed. "Role Discovery in Networks." arXiv preprint arXiv:1405.7134 (2014).
[citation][year=2014]Zhang, Yin, et al. "A GPU-accelerated non-negative sparse latent semantic analysis algorithm for social tagging data." Information Sciences (2014).
[citation][year=2013]Ding, Chris. "Nonnegative Matrix Factorizations for Clustering: A Survey." Data Clustering: Algorithms and Applications (2013): 148.
[citation][year=2011]E. Mejía-Roa, C. García, J.I. Gómez, M. Prieto, F. Tirado, R. Nogales and A. Pascual-Montano, Biclustering and Classification Analysis in Gene Expression using Nonnegative Matrix Factorization on Multi-GPU Systems, 11th International Conference on Intelligent Systems Design and Applications, pp. 882-887, 2011
[citation][year=2011]Edgardo Mejía-Roa, Carlos García, José Ignacio Gómez, Manuel Prieto, Christian Tenllado, Alberto D. Pascual-Montano and Francisco Tirado, Parallelism on the Nonnegative Matrix Factorization. In Applications, Tools and Techniques on the Road to Exascale Computing, pp. 421-428 , 2011
[citation][year=2011]Tirado, F. "Parallelism on the Nonnegative Matrix Factorization". Advances in Parallel Computing 22:421-428 (2011)
[citation][year=2010]Pei-Yin Tsai, NMF on CUDA, 2010.

[publication]Noel Lopes and Ribeiro, B. , "A Hybrid Face Recognition Approach Using GPUMLib", in Iberoamerican Congress on Pattern Recognition, CIARP 2010, LNCS 6419, Springer, pp. 96-103, 2010

2009(3 publications)
[publication]Noel Lopes and Ribeiro, B. , "GPU implementation of the multiple back-propagation algorithm", in 10th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2009, 2009
[citation][year=2015]Wang, Y., Tang, P., An, H., Liu, Z., Wang, K., & Zhou, Y. (2015, November). Optimization and Analysis of Parallel Back Propagation Neural Network on GPU Using CUDA. In Neural Information Processing (pp. 156-163). Springer International Publishing.
[citation][year=2015]Li, B., & Liu, C. (2015, August). Parallel BP Neural Network on Single-chip Cloud Computer. In High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conference on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on (pp. 1871-1875). IEEE.
[citation][year=2015]K.Karthikeyan, Sayantani Basu. Neural Network Technique in Data Mining for Prediction of Earth Quake. International Journal Of Pharmacy & Technology. Vol. 7, Issue 3, pp. 9543-9554 (2015)
[citation][year=2014]Beam, Andrew L., Alison Motsinger-Reif, and Jon Doyle. "Bayesian neural networks for detecting epistasis in genetic association studies." BMC bioinformatics 15.1 (2014): 368.
[citation][year=2014]Horita, Tadayoshi, et al. "A GPGPU-Based Acceleration of Fault-Tolerant MLP Learnings." Embedded Multicore/Manycore SoCs (MCSoc), 2014 IEEE 8th International Symposium on. IEEE, 2014.
[citation][year=2014]Beam, Andrew L., Alison Motsinger-Reif, and Jon Doyle. "Bayesian Neural Networks for Genetic Association Studies of Complex Disease." arXiv preprint arXiv:1404.3989 (2014).
[citation][year=2013]Baptista, Darío, and Fernando Morgado-Dias. "A survey of artificial neural network training tools." Neural Computing and Applications 23.3-4 (2013): 609-615.
[citation][year=2013]Kahandawa, G. C., et al. "Use of fixed wavelength fibre-bragg grating (FBG) filters to capture time domain data from the distorted spectrum of an embedded FBG sensor to estimate strain with an artificial neural network." Sensors and Actuators A: Physical 194 (2013): 1-7.
[citation][year=2013]Kahandawa, Gayan C., et al. "Prediction of obsolete FBG sensor using ANN for efficient and robust operation of SHM systems." Key Engineering Materials 558 (2013): 546-553.
[citation][year=2012]Ole-Christoffer Granmo. Short-term forecasting of electricity consumption using Gaussian processes. Master’s thesis, University of Agder, 2012.
[citation][year=2012]Zhang Branch, Yang Bo , Wang Lin , and Zhu Fuxiang "Modern parallel GPU-based optimization algorithm". Computer Science 39, no 4 (2012), 304-310.
[citation][year=2012]Yi Wu Zheng and Behandish Morad. Real-time pump scheduling using genetic algorithm and artificial neural network based on graphics processing unit. In 14th Water Distribution Systems Analysis Conference (WDSA 2012), 2012.
[citation][year=2012]Yi Wu Zheng and Behandish Morad. Comparing methods of parallel genetic optimization for pump scheduling using hydraulic model and GPU-based ANN metamodel. In 14th Water Distribution Systems Analysis Conference (WDSA 2012), 2012.
[citation][year=2012]Pavel Krömer, Emilio Corchado, Václav Snášel, Jan Platoš, and Laura García-Hernández. Neural PCA and maximum likelihood hebbian learning on the GPU. In Artificial Neural Networks and Machine Learning (ICANN 2012), LNCS 7553, pages 132–139, 2012.
[citation][year=2012]Andréa Martiniano da Silva. Aplicação de técnica da mineração de dados na identificação do perfil de empregados absenteístas e presenteístas em uma empresa de courier da cidade de são paulo. Master’s thesis, Universidade Nove de Julho – UNINOVE, 2012.
[citation][year=2011]Jarno Mielikainena, Bormin Huanga, Allen H.-L. Huanga, and Mitchell D. Goldbergb. Development of the GPU-based stony-brook university 5-class microphysics scheme in the weather research and forecasting model. J. Proceedings of the SPIE, High-Performance Computing in Remote Sensing, 8183(2):81830V–1–81830V–10, 2011.
[citation][year=2011]Roli Pradhan, K. K. Pathak, and V. P. Singh. Application of neural network in prediction of nancial viability. International Journal of Soft Computing and Engineering (IJSCE), 1(2):41-45, 2011.
[citation][year=2011]Laurentiu Bucur. Sparse Kernel Machines and High Performance Computing. PhD thesis, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 2011.
[citation][year=2011]Boonkiatpong, Kritsanatt, and Sukree Sinthupinyo. "Applying Multiple Neural Networks on Large Scale Data." Proceedings of International Conference on Information and Electronics Engineering (ICIEE 2011). 2011.
[citation][year=2011]S. A. Zapryagaev and A. A. Karpushin. Calculation and learning artificial neural networks direct distribution by GPUs. VSU HERALD SERIES: System Analysis and Information Technologies, (1):157-164, 2011.
[citation][year=2011]Li Liang. Parallel implementations of hopefield neural networks on GPU. Technical report, DUMAS, Grenoble Universites, 2011.

[publication]Noel Lopes and Ribeiro, B. , "MBPGPU: A Supervised Pattern Classifier for Graphical Processing Units", in 15th edition of the Portuguese Conference on Pattern Recognition - RECPAD 2009, 2009

[publication]Noel Lopes and Ribeiro, B. , "Fast pattern classification of ventricular arrhythmias using graphics processing units", in 14th Iberoamerican Congress on Pattern Recognition (CIARP 2009), 2009
[citation][year=2011]Laurentiu Bucur, Sparse Kernel Machines and High Performance Computing, PhD thesis, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 2011.

2001(1 publication)
[publication]Noel Lopes and Ribeiro, B. , "Hybrid learning in a multi-neural network architecture", in INNS-IEEE International Joint Conference on Neural Networks (IJCNN'01), 2001
[citation][year=2015]K.Karthikeyan, Sayantani Basu. Neural Network Technique in Data Mining for Prediction of Earth Quake. International Journal Of Pharmacy & Technology. Vol. 7, Issue 3, pp. 9543-9554 (2015)
[citation][year=2013]E. E. Supeni, J. A. Epaarachchi, M. M. Islam, and K. T. Lau. Development of artificial neural network model in predicting performance of the smart wind turbine blade. In 3rd Malaysian Postgraduate Conference (MPC2013), 2013.
[citation][year=2013]G. C. Kahandawa, J. A. Epaarachchi, H. Wang, D. Followell, and P. Birt. Use of fixed wavelength fibre-bragg grating (FBG) filters to capture time domain data from the distorted spectrum of an embedded FBG sensor to estimate strain with an artificial neural network. Sensors and Actuators A: Physical, 194:1–7, 2013.
[citation][year=2013]Kahandawa, G. C., Epaarachchi, J. A., Wang, H., & Lau, K. T. (2013, June). Prediction of obsolete FBG sensor using ANN for efficient and robust operation of SHM systems. In Key Engineering Materials (Vol. 558, pp. 546-553). Trans Tech Publications.
[citation][year=2012]Ole-Christoffer Granmo. Short-term forecasting of electricity consumption using Gaussian processes. Master’s thesis, University of Agder, 2012.
[citation][year=2012]Kahandawa, G. C. (2012). Monitoring damage in advanced composite structures using embedded fibre optic sensors (Doctoral dissertation, University of Southern Queensland).
[citation][year=2012]Yi Wu Zheng and Behandish Morad. Real-time pump scheduling using genetic algorithm and artificial neural network based on graphics processing unit. In 14th Water Distribution Systems Analysis Conference (WDSA 2012), 2012.
[citation][year=2012]Yi Wu Zheng and Behandish Morad. Comparing methods of parallel genetic optimization for pump scheduling using hydraulic model and GPU-based ANN metamodel. In 14th Water Distribution Systems Analysis Conference (WDSA 2012), 2012.
[citation][year=2011]Kritsanatt Boonkiatpong and Sukree Sinthupinyo, Applying Multiple Neural Networks on Large Scale Data, 2011 International Conference on Information and Electronics Engineering, vol.6, pp. 189-193, 2011.
[citation][year=2011]Laurentiu Bucur, Sparse Kernel Machines and High Performance Computing, PhD thesis, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 2011.
[citation][year=2010]Xinliang Yu, "Prediction of Q-e Parameters of Monomers in Free-radical Copolymerizations", ACTA CHIMICA SINICA,vol. 68, no. 22, pp 2264-2272, 2010

1999(2 publications)
[publication]Noel Lopes and Ribeiro, B. , "A Data Pre-Processing Tool for Neural Networks (DTPNN) Use in a Moulding Injection Machine", in Second World Manufacturing Congress (WMC'99), 1999

[publication]Noel Lopes and Ribeiro, B. , "Part Quality Prediction in an Injection Moulding Process using Neural Networks", in Second World Manufacturing Congress (WMC\'99), 1999
[citation][year=2013]Zheng, Zou Shun, and Rui Rui Leng. "The Intelligent Control Method of the Density of the Metal Injection Molding Billet based on ANN." Materials Science Forum. Vol. 749. 2013.
[citation][year=2010]Han Yong, He Xinbo, Qu Xuanhui, Zhou Yu, Xu Junli, "Application of artificial neural network to metal injection molding", POWDER METALLURGY TECHNOLOGY, vol. 28, no. 1, pp. 66-72, 2010
[citation][year=2008]Drago Torkar, Sasa Novak and Franc Novak, "Apparent viscosity prediction of alumina–paraffin suspensions using artificial neural networks", Journal of Materials Processing Technology, Elsevier, 203 (2008), pp. 208-215
[citation][year=2008]Zahra HAMOU MAMAR, "Analyse Temps-Échelle et Reconnaissance des Formes pour le Diagnostic du Système de Guidage d'un Tramway sur Pneumatiques", PHd Thesis, UNIVERSITE BLAISE PASCAL - CLERMONT II, 2008
[citation][year=2007]Nouha Baccour, Heni Kaaniche, Mohamed Chtourou, and Maher Ben Jemaa. "Recurrent neural network based time series prediction: Particular design problems", International Conference on Smart Systems and Devices (SSD 2007), Hammamet , Tunisia, March 19-22, 2007
[citation][year=2007]Daniel da Cunha Reis, "Modelação do Processo de Moldação por Injecção Utilizando Redes Neuronais Artificiais", MSc thesis, University of Aveiro, 2007.
[citation][year=2006]Racoceanu, D., Contribution à la Surveillance des Systèmes de Production et Utilisant les Techniques de l’Intelligence Artificielle, 2006.
[citation][year=2006]Nouha Baccour Sellami, Conception D’une Nouvelle Strategie De Routage Dynamique Pour Les Reseaux Mobiles Ad Hoc, MSc. thesis, Université de Sfax, 2006.
[citation][year=2003]M. R. Zemouri,Contribution à la surveillance des systèmes de production à
l’aide des réseaux de neurones dynamiques : Application à la e-maintenance, PhD thesis, L’UFR des Sciences et Techniques de l’Université de Franche-Comté, 2003.

Book Chapters
2014(1 publication)
[publication]Hasan, S. and Shamsuddin, S.M. and Noel Lopes , "Soft Computing Methods for Big Data Problems", in GPU Computing and Applications,  vol. na,  pp. 235-247, 2014

PhD Theses
2014(2 publications)
[publication]Noel Lopes , "Machine Learning for Adaptive Multi-Core Machines", 2014

[publication]Noel Lopes , "Machine Learning for Adaptive Multi-Core Machines", 2014

MSc Theses
2012(1 publication)
[publication]João Gonçalves and Ribeiro, B. and Noel Lopes , "Development of Support Vector Machines in Graphics Processing Units for Pattern Recognition", 2012