Amaury Lendasse

According to our database, Amaury Lendasse authored at least 189 papers between 1998 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

USDOT Tier-1 University Transportation Center for Advancing Cybersecurity Research and Education.

Yunpeng Jack Zhang, Kailai Wang, Lingguang Song, Amaury Lendasse, Houbing Herbert Song, Zhu Han, Rakesh M. Verma, Arlei Silva, Carlos E. Rubio-Medrano, Zhixia Richard Li, Guohui Zhang

Proceedings of the IEEE International Conference on Mobility, 2023

X-ELM: A Fast Explainability Approach for Extreme Learning Machines.

Brandon Warner, Edward R. Ratner, Amaury Lendasse

Proceedings of the Advances in Computational Intelligence, 2023

Acid Sulfate Soils Classification and Prediction from Environmental Covariates Using Extreme Learning Machines.

Tamirat Atsemegiorgis, Leonardo Espinosa Leal, Amaury Lendasse, Stefan Mattbäck, Kaj-Mikael Björk, Anton Akusok

Proceedings of the Advances in Computational Intelligence, 2023

2021

Handwriting features based detection of fake signatures.

Anton Akusok, Leonardo Espinosa Leal, Kaj-Mikael Björk, Amaury Lendasse, Renjie Hu

Proceedings of the PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference, Virtual Event, Greece, 29 June, 2021

NNBMSS: a Novel and Fast Method for Model Structure Selection.

Amaury Lendasse, Kallin Khan, Edward R. Ratner

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

A Multi-ELM Model for Incomplete Data.

Baichuan Chi, Amaury Lendasse, Edward R. Ratner, Renjie Hu

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Machine Learning for Measuring and Analyzing Online Social Communications.

Chris Bronk, Amaury Lendasse, Peggy Lindner, Dan S. Wallach, Barbara Hammer

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020

A machine-learning-enhanced hierarchical multiscale method for bridging from molecular dynamics to continua.

Shaoping Xiao, Renjie Hu, Zhen Li, Siamak Attarian, Kaj-Mikael Björk, Amaury Lendasse

Neural Comput. Appl., 2020

Embedded spectral descriptors: learning the point-wise correspondence metric via Siamese neural networks.

Zhiyu Sun, Yusen He, Andrey Gritsenko, Amaury Lendasse, Stephen Baek

J. Comput. Des. Eng., 2020

A modified Lanczos Algorithm for fast regularization of extreme learning machines.

Renjie Hu, Edward R. Ratner, David E. Stewart, Kaj-Mikael Björk, Amaury Lendasse

Neurocomputing, 2020

Using machine learning to identify top predictors for nurses' willingness to report medication errors.

Renjie Hu, Amany Farag, Kaj-Mikael Björk, Amaury Lendasse

Array, 2020

Feature Bagging and Extreme Learning Machines: Machine Learning with Severe Memory Constraints.

Kallin Khan, Edward R. Ratner, Robert Ludwig, Amaury Lendasse

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Domain Adaption via Feature Selection on Explicit Feature Map.

Wan-Yu Deng, Amaury Lendasse, Yew-Soon Ong, Ivor Wai-Hung Tsang, Lin Chen, Qing-Hua Zheng

IEEE Trans. Neural Networks Learn. Syst., 2019

Local receptive fields based extreme learning machine with hybrid filter kernels for image classification.

Bo He, Yan Song, Yuemei Zhu, Qixin Sha, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse

Multidimens. Syst. Signal Process., 2019

Per-sample prediction intervals for extreme learning machines.

Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse

Int. J. Mach. Learn. Cybern., 2019

ELM-SOM+: A continuous mapping for visualization.

Renjie Hu, Karl Ratner, Edward R. Ratner, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse

Neurocomputing, 2019

Mislabel Detection of Finnish Publication Ranks.

Anton Akusok, Mirka Saarela, Tommi Kärkkäinen, Kaj-Mikael Björk, Amaury Lendasse

CoRR, 2019

Extreme Learning Tree.

Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Amaury Lendasse

CoRR, 2019

Incremental ELMVIS for unsupervised learning.

Anton Akusok, Emil Eirola, Yoan Miche, Ian Oliver, Kaj-Mikael Björk, Andrey Gritsenko, Stephen Baek, Amaury Lendasse

CoRR, 2019

A Framework for Privacy Quantification: Measuring the Impact of Privacy Techniques Through Mutual Information, Distance Mapping, and Machine Learning.

Yoan Miche, Wei Ren, Ian Oliver, Silke Holtmanns, Amaury Lendasse

Cogn. Comput., 2019

Spiking networks for improved cognitive abilities of edge computing devices.

Anton Akusok, Kaj-Mikael Björk, Leonardo Espinosa Leal, Yoan Miche, Renjie Hu, Amaury Lendasse

Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, 2019

2018

Adaptive and online network intrusion detection system using clustering and Extreme Learning Machines.

Setareh Roshan, Yoan Miche, Anton Akusok, Amaury Lendasse

J. Frankl. Inst., 2018

Gaussian derivative models and ensemble extreme learning machine for texture image classification.

Yan Song, Shujing Zhang, Bo He, Qixin Sha, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse

Neurocomputing, 2018

Discriminant document embeddings with an extreme learning machine for classifying clinical narratives.

Paula Lauren, Guangzhi Qu, Feng Zhang, Amaury Lendasse

Neurocomputing, 2018

Parameter-free image segmentation with SLIC.

Fabian Boemer, Edward R. Ratner, Amaury Lendasse

Neurocomputing, 2018

Generating Word Embeddings from an Extreme Learning Machine for Sentiment Analysis and Sequence Labeling Tasks.

Paula Lauren, Guangzhi Qu, Jucheng Yang, Paul Watta, Guang-Bin Huang, Amaury Lendasse

Cogn. Comput., 2018

Extreme Learning Machines for VISualization+R: Mastering Visualization with Target Variables.

Andrey Gritsenko, Anton Akusok, Stephen Baek, Yoan Miche, Amaury Lendasse

Cogn. Comput., 2018

Anomaly-Based Intrusion Detection Using Extreme Learning Machine and Aggregation of Network Traffic Statistics in Probability Space.

Buse Gul Atli, Yoan Miche, Aapo Kalliola, Ian Oliver, Silke Holtmanns, Amaury Lendasse

Cogn. Comput., 2018

A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning.

Leonardo Espinosa Leal, Kaj-Mikael Björk, Amaury Lendasse, Anton Akusok

Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference, 2018

ELM-SOM: A Continuous Self-Organizing Map for Visualization.

Renjie Hu, Venous Roshdibenam, Hans J. Johnson, Emil Eirola, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

A Novel ELM Ensemble for Time Series Prediction.

Zhen Li, Karl Ratner, Edward R. Ratner, Kallin Khan, Kaj-Mikael Björk, Amaury Lendasse

Proceedings of ELM 2018, 2018

2017

Advances in extreme learning machines (ELM2015).

Amaury Lendasse, Chi-Man Vong, Kar-Ann Toh, Yoan Miche, Guang-Bin Huang

Neurocomputing, 2017

Adding reliability to ELM forecasts by confidence intervals.

Anton Akusok, Andrey Gritsenko, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Paula Lauren, Amaury Lendasse

Neurocomputing, 2017

Deep Spectral Descriptors: Learning the point-wise correspondence metric via Siamese deep neural networks.

Zhiyu Sun, Yusen He, Andrey Gritsenko, Amaury Lendasse, Stephen Baek

CoRR, 2017

Brute-force Missing Data Extreme Learning Machine for Predicting Huntington's Disease.

Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Yoan Miché, Hans J. Johnson, Amaury Lendasse

Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments, 2017

A low-dimensional vector representation for words using an extreme learning machine.

Paula Lauren, Guangzhi Qu, Guang-Bin Huang, Paul Watta, Amaury Lendasse

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs.

Andrey Gritsenko, Emil Eirola, Daniel Schupp, Edward R. Ratner, Amaury Lendasse

Proceedings of the Hybrid Artificial Intelligent Systems - 12th International Conference, 2017

Advanced query strategies for Active Learning with Extreme Learning Machines.

Anton Akusok, Emil Eirola, Yoan Miché, Andrey Gritsenko, Amaury Lendasse

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

On Distance Mapping from non-Euclidean Spaces to Euclidean Spaces.

Wei Ren, Yoan Miche, Ian Oliver, Silke Holtmanns, Kaj-Mikael Björk, Amaury Lendasse

Proceedings of the Machine Learning and Knowledge Extraction, 2017

Practical Estimation of Mutual Information on Non-Euclidean Spaces.

Yoan Miche, Ian Oliver, Wei Ren, Silke Holtmanns, Anton Akusok, Amaury Lendasse

Proceedings of the Machine Learning and Knowledge Extraction, 2017

2016

HSR: L 1/2-regularized sparse representation for fast face recognition using hierarchical feature selection.

Bo Han, Bo He, Tingting Sun, Tianhong Yan, Mengmeng Ma, Yue Shen, Amaury Lendasse

Neural Comput. Appl., 2016

Manifold learning in local tangent space via extreme learning machine.

Qian Wang, Weiguo Wang, Rui Nian, Bo He, Yue Shen, Kaj-Mikael Björk, Amaury Lendasse

Neurocomputing, 2016

Extreme learning machine for missing data using multiple imputations.

Dusan Sovilj, Emil Eirola, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Anton Akusok, Amaury Lendasse

Neurocomputing, 2016

Comparison of combining methods using Extreme Learning Machines under small sample scenario.

Dusan Sovilj, Kaj-Mikael Björk, Amaury Lendasse

Neurocomputing, 2016

Advances in extreme learning machines (ELM2014).

Amaury Lendasse, Chi-Man Vong, Yoan Miche, Guang-Bin Huang

Neurocomputing, 2016

Singular Value Decomposition update and its application to (Inc)-OP-ELM.

Alexander Grigorievskiy, Yoan Miche, Maarit Käpylä, Amaury Lendasse

Neurocomputing, 2016

Brain MRI morphological patterns extraction tool based on Extreme Learning Machine and majority vote classification.

Maite Termenon, Manuel Graña, Alexandre Savio, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse

Neurocomputing, 2016

ELMVIS+: Fast nonlinear visualization technique based on cosine distance and extreme learning machines.

Anton Akusok, Stephen Baek, Yoan Miché, Kaj-Mikael Björk, Rui Nian, Paula Lauren, Amaury Lendasse

Neurocomputing, 2016

A new application of machine learning in health care.

Kaj-Mikael Björk, Emil Eirola, Yoan Miché, Amaury Lendasse

Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments, 2016

Clinical narrative classification using discriminant word embeddings with ELM.

Paula Lauren, Guangzhi Qu, Feng Zhang, Amaury Lendasse

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Combined nonlinear visualization and classification: ELMVIS++C.

Andrey Gritsenko, Anton Akusok, Yoan Miché, Kaj-Mikael Björk, Stephen Baek, Amaury Lendasse

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

A R-SOM Analysis of the Link between Financial Market Conditions and a Systemic Risk Index Based on ICA-Factors of Systemic Risk Measures.

Patrick Kouontchou, Amaury Lendasse, Yoan Miché, Alejandro Modesto, Peter Sarlin, Bertrand Maillet

Proceedings of the 49th Hawaii International Conference on System Sciences, 2016

Data Anonymization as a Vector Quantization Problem: Control Over Privacy for Health Data.

Yoan Miché, Ian Oliver, Silke Holtmanns, Aapo Kalliola, Anton Akusok, Amaury Lendasse, Kaj-Mikael Björk

Proceedings of the Availability, Reliability, and Security in Information Systems, 2016

2015

Meme representations for game agents.

Yoan Miche, Meng-Hiot Lim, Amaury Lendasse, Yew-Soon Ong

World Wide Web, 2015

SOM-ELM - Self-Organized Clustering using ELM.

Yoan Miché, Anton Akusok, David Veganzones, Kaj-Mikael Björk, Eric Séverin, Philippe du Jardin, Maite Termenon, Amaury Lendasse

Neurocomputing, 2015

Advances in Extreme Learning Machines (ELM2013).

Amaury Lendasse, Qing He, Yoan Miché, Guang-Bin Huang

Neurocomputing, 2015

Minimal Learning Machine: A novel supervised distance-based approach for regression and classification.

Amauri Holanda de Souza Júnior, Francesco Corona, Guilherme De A. Barreto, Yoan Miché, Amaury Lendasse

Neurocomputing, 2015

LARSEN-ELM: Selective ensemble of extreme learning machines using LARS for blended data.

Bo Han, Bo He, Rui Nian, Mengmeng Ma, Shujing Zhang, Minghui Li, Amaury Lendasse

Neurocomputing, 2015

MD-ELM: Originally Mislabeled Samples Detection using OP-ELM Model.

Anton Akusok, David Veganzones, Yoan Miché, Kaj-Mikael Björk, Philippe du Jardin, Eric Séverin, Amaury Lendasse

Neurocomputing, 2015

Arbitrary Category Classification of Websites Based on Image Content.

Anton Akusok, Yoan Miche, Juha Karhunen, Kaj-Mikael Björk, Rui Nian, Amaury Lendasse

IEEE Comput. Intell. Mag., 2015

High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications.

Anton Akusok, Kaj-Mikael Björk, Yoan Miché, Amaury Lendasse

IEEE Access, 2015

Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes.

Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Yoan Miché, Amaury Lendasse, Juha Karhunen

Proceedings of the 2015 IEEE TrustCom/BigDataSE/ISPA, 2015

Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models.

Emil Eirola, Andrey Gritsenko, Anton Akusok, Kaj-Mikael Björk, Yoan Miche, Dusan Sovilj, Rui Nian, Bo He, Amaury Lendasse

Proceedings of the Advances in Computational Intelligence, 2015

Efficient Skin Segmentation via Neural Networks: HP-ELM and BD-SOM.

C. Swaney, Anton Akusok, Kaj-Mikael Björk, Yoan Miché, Amaury Lendasse

Proceedings of the INNS Conference on Big Data 2015, 2015

Towards a Tomographic Index of Systemic Risk Measures.

Kaj-Mikael Björk, Patrick Kouontchou, Amaury Lendasse, Yoan Miché, Bertrand Maillet

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

Long-term time series prediction using OP-ELM.

Alexander Grigorievskiy, Yoan Miche, Anne-Mari Ventelä, Eric Séverin, Amaury Lendasse

Neural Networks, 2014

Bankruptcy prediction using Extreme Learning Machine and financial expertise.

Qi Yu, Yoan Miche, Eric Séverin, Amaury Lendasse

Neurocomputing, 2014

Ensemble delta test-extreme learning machine (DT-ELM) for regression.

Qi Yu, Mark van Heeswijk, Yoan Miche, Rui Nian, Bo He, Eric Séverin, Amaury Lendasse

Neurocomputing, 2014

Extreme learning machine towards dynamic model hypothesis in fish ethology research.

Rui Nian, Bo He, Bing Zheng, Mark van Heeswijk, Qi Yu, Yoan Miche, Amaury Lendasse

Neurocomputing, 2014

Extreme learning machines for soybean classification in remote sensing hyperspectral images.

Ramón Moreno, Francesco Corona, Amaury Lendasse, Manuel Graña, Lênio S. Galvão

Neurocomputing, 2014

Advances in extreme learning machines (ELM2012).

Amaury Lendasse, Qing He, Yoan Miche, Guang-Bin Huang

Neurocomputing, 2014

Mixture of Gaussians for distance estimation with missing data.

Emil Eirola, Amaury Lendasse, Vincent Vandewalle, Christophe Biernacki

Neurocomputing, 2014

Fast Feature Selection in a GPU Cluster Using the Delta Test.

Alberto Guillén, M. Isabel García Arenas, Mark van Heeswijk, Dusan Sovilj, Amaury Lendasse, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas

Entropy, 2014

Robust OS-ELM with a novel selective ensemble based on particle swarm optimization.

Yang Liu, Bo He, Diya Dong, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse

CoRR, 2014

HSR: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection.

Bo Han, Bo He, Tingting Sun, Mengmeng Ma, Amaury Lendasse

CoRR, 2014

RMSE-ELM: Recursive Model based Selective Ensemble of Extreme Learning Machines for Robustness Improvement.

Bo Han, Bo He, Mengmeng Ma, Tingting Sun, Tianhong Yan, Amaury Lendasse

CoRR, 2014

Fast Image Recognition Based on Independent Component Analysis and Extreme Learning Machine.

Shujing Zhang, Bo He, Rui Nian, Jing Wang, Bo Han, Amaury Lendasse, Guang Yuan

Cogn. Comput., 2014

Fast Face Recognition Via Sparse Coding and Extreme Learning Machine.

Bo He, Dongxun Xu, Rui Nian, Mark van Heeswijk, Qi Yu, Yoan Miche, Amaury Lendasse

Cogn. Comput., 2014

A Two-Stage Methodology Using K-NN and False-Positive Minimizing ELM for Nominal Data Classification.

Anton Akusok, Yoan Miche, Jozsef Hegedus, Rui Nian, Amaury Lendasse

Cogn. Comput., 2014

Variable selection for regression problems using Gaussian mixture models to estimate mutual information.

Emil Eirola, Amaury Lendasse, Juha Karhunen

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

The delta test: The 1-NN estimator as a feature selection criterion.

Emil Eirola, Amaury Lendasse, Francesco Corona, Michel Verleysen

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Finding Originally Mislabels with MD-ELM.

Anton Akusok, David Veganzones, Yoan Miché, Eric Séverin, Amaury Lendasse

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Compressive ELM: Improved Models through Exploiting Time-Accuracy Trade-Offs.

Mark van Heeswijk, Amaury Lendasse, Yoan Miché

Proceedings of the Engineering Applications of Neural Networks, 2014

2013

3D object recognition based on a geometrical topology model and extreme learning machine.

Rui Nian, Bo He, Amaury Lendasse

Neural Comput. Appl., 2013

Distance estimation in numerical data sets with missing values.

Emil Eirola, Gauthier Doquire, Michel Verleysen, Amaury Lendasse

Inf. Sci., 2013

Regularized extreme learning machine for regression with missing data.

Qi Yu, Yoan Miche, Emil Eirola, Mark van Heeswijk, Eric Séverin, Amaury Lendasse

Neurocomputing, 2013

Feature selection for nonlinear models with extreme learning machines.

Benoît Frénay, Mark van Heeswijk, Yoan Miche, Michel Verleysen, Amaury Lendasse

Neurocomputing, 2013

Extreme Learning Machines.

Erik Cambria, Guang-Bin Huang, Liyanaarachchi Lekamalage Chamara Kasun, Hongming Zhou, Chi-Man Vong, Jiarun Lin, Jianping Yin, Zhiping Cai, Qiang Liu, Kuan Li, Victor C. M. Leung, Liang Feng, Yew-Soon Ong, Meng-Hiot Lim, Anton Akusok, Amaury Lendasse, Francesco Corona, Rui Nian, Yoan Miche, Paolo Gastaldo, Rodolfo Zunino, Sergio Decherchi, Xuefeng Yang, Kezhi Mao, Beom-Seok Oh, Je-Hyoung Jeon, Kar-Ann Toh, Andrew Beng Jin Teoh, Jaihie Kim, Hanchao Yu, Yiqiang Chen, Junfa Liu

IEEE Intell. Syst., 2013

Data Preprocessing and Model Design for Medicine Problems.

Alberto Guillén, Amaury Lendasse, Guilherme A. Barreto

Comput. Math. Methods Medicine, 2013

Extending Extreme Learning Machine with Combination Layer.

Dusan Sovilj, Amaury Lendasse, Olli Simula

Proceedings of the Advances in Computational Intelligence, 2013

Extreme Learning Machine: A Robust Modeling Technique? Yes!

Amaury Lendasse, Anton Akusok, Olli Simula, Francesco Corona, Mark van Heeswijk, Emil Eirola, Yoan Miche

Proceedings of the Advances in Computational Intelligence, 2013

Minimal Learning Machine: A New Distance-Based Method for Supervised Learning.

Amauri Holanda de Souza Júnior, Francesco Corona, Yoan Miche, Amaury Lendasse, Guilherme A. Barreto, Olli Simula

Proceedings of the Advances in Computational Intelligence, 2013

Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation.

Emil Eirola, Amaury Lendasse

Proceedings of the Advances in Intelligent Data Analysis XII, 2013

Forecasting Financial Markets with Classified Tactical Signals.

Patrick Kouontchou, Amaury Lendasse, Yoan Miché, Bertrand Maillet

Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Visualizing dependencies of spectral features using mutual information.

Andrej Gisbrecht, Yoan Miché, Barbara Hammer, Amaury Lendasse

Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012

Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator.

Alberto Guillén, Dusan Sovilj, Mark van Heeswijk, Luis Javier Herrera, Amaury Lendasse, Héctor Pomares, Ignacio Rojas

Proceedings of the Parallel Architectures and Bioinspired Algorithms, 2012

Adaptive kernel smoothing regression for spatio-temporal environmental datasets.

Federico Montesino-Pouzols, Amaury Lendasse

Neurocomputing, 2012

Fast variable selection for memetracker phrases time series prediction.

Yoan Miche, Tatiana Chistiakova, Anton Akusok, Amaury Lendasse, Rui Nian, Alberto Guillén

Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments, 2012

Relevance learning for time series inspection.

Andrej Gisbrecht, Dusan Sovilj, Barbara Hammer, Amaury Lendasse

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011

On the Curse of Dimensionality in Supervised Learning of Smooth Regression Functions.

Elia Liitiäinen, Francesco Corona, Amaury Lendasse

Neural Process. Lett., 2011

TROP-ELM: A double-regularized ELM using LARS and Tikhonov regularization.

Yoan Miche, Mark van Heeswijk, Patrick Bas, Olli Simula, Amaury Lendasse

Neurocomputing, 2011

GPU-accelerated and parallelized ELM ensembles for large-scale regression.

Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse

Neurocomputing, 2011

Locating Anomalies Using Bayesian Factorizations and Masks.

Li Yao, Amaury Lendasse, Francesco Corona

Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

Adaptive kernel smoothing regression using vector quantization.

Federico Montesino-Pouzols, Amaury Lendasse

Proceedings of the 2011 IEEE Workshop on Evolving and Adaptive Intelligent Systems, 2011

Methodology for Behavioral-based Malware Analysis and Detection Using Random Projections and K-Nearest Neighbors Classifiers.

Jozsef Hegedus, Yoan Miche, Alexander Ilin, Amaury Lendasse

Proceedings of the Seventh International Conference on Computational Intelligence and Security, 2011

2010

OP-ELM: optimally pruned extreme learning machine.

Yoan Miche, Antti Sorjamaa, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse

IEEE Trans. Neural Networks, 2010

A boundary corrected expansion of the moments of nearest neighbor distributions.

Elia Liitiäinen, Amaury Lendasse, Francesco Corona

Random Struct. Algorithms, 2010

Residual variance estimation using a nearest neighbor statistic.

Elia Liitiäinen, Francesco Corona, Amaury Lendasse

J. Multivar. Anal., 2010

X-SOM and L-SOM: A double classification approach for missing value imputation.

Paul Merlin, Antti Sorjamaa, Bertrand Maillet, Amaury Lendasse

Neurocomputing, 2010

European Symposium on Times Series Prediction.

Amaury Lendasse, Timo Honkela, Olli Simula

Neurocomputing, 2010

New method for instance or prototype selection using mutual information in time series prediction.

Alberto Guillén, Luis Javier Herrera, Ginés Rubio, Héctor Pomares, Amaury Lendasse, Ignacio Rojas

Neurocomputing, 2010

Autoregressive time series prediction by means of fuzzy inference systems using nonparametric residual variance estimation.

Federico Montesino-Pouzols, Amaury Lendasse, Angel Barriga Barros

Fuzzy Sets Syst., 2010

Evolving fuzzy optimally pruned extreme learning machine for regression problems.

Federico Montesino-Pouzols, Amaury Lendasse

Evol. Syst., 2010

OP-KNN: Method and Applications.

Qi Yu, Yoan Miché, Antti Sorjamaa, Alberto Guillén, Amaury Lendasse, Eric Séverin

Adv. Artif. Neural Syst., 2010

Effect of different detrending approaches on computational intelligence models of time series.

Federico Montesino-Pouzols, Amaury Lendasse

Proceedings of the International Joint Conference on Neural Networks, 2010

Interpreting Extreme Learning Machine as an Approximation to an Infinite Neural Network.

Elina Parviainen, Jaakko Riihimäki, Yoan Miche, Amaury Lendasse

Proceedings of the KDIR 2010, 2010

Evolving fuzzy Optimally Pruned Extreme Learning Machine: A comparative analysis.

Federico Montesino-Pouzols, Amaury Lendasse

Proceedings of the FUZZ-IEEE 2010, 2010

Machine Learning Techniques based on Random Projections.

Yoan Miche, Benjamin Schrauwen, Amaury Lendasse

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs.

Yoan Miche, Emil Eirola, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse, Michel Verleysen

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs.

Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

Ensembles of Locally Linear Models: Application to Bankruptcy Prediction.

Laura Kainulainen, Qi Yu, Yoan Miche, Emil Eirola, Eric Séverin, Amaury Lendasse

Proceedings of The 2010 International Conference on Data Mining, 2010

2009

Functional Dimension Reduction for Chemometrics.

Tuomas Kärnä, Amaury Lendasse

Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

Residual variance estimation in machine learning.

Elia Liitiäinen, Michel Verleysen, Francesco Corona, Amaury Lendasse

Neurocomputing, 2009

A SOM-based approach to estimating product properties from spectroscopic measurements.

Francesco Corona, Elia Liitiäinen, Amaury Lendasse, Lorenzo Sassu, Stefano Melis, Roberto Baratti

Neurocomputing, 2009

Reliable Steganalysis Using a Minimum Set of Samples and Features.

Yoan Miche, Patrick Bas, Amaury Lendasse, Christian Jutten, Olli Simula

EURASIP J. Inf. Secur., 2009

Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database.

Antti Sorjamaa, Francesco Corona, Yoan Miche, Paul Merlin, Bertrand Maillet, Eric Séverin, Amaury Lendasse

Proceedings of the Advances in Self-Organizing Maps, 7th International Workshop, 2009

RCGA-S/RCGA-SP Methods to Minimize the Delta Test for Regression Tasks.

Fernando Mateo, Dusan Sovilj, Rafael Gadea Gironés, Amaury Lendasse

Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Efficient Parallel Feature Selection for Steganography Problems.

Alberto Guillén, Antti Sorjamaa, Yoan Miche, Amaury Lendasse, Ignacio Rojas

Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Long-term prediction of time series by combining direct and MIMO strategies.

Souhaib Ben Taieb, Gianluca Bontempi, Antti Sorjamaa, Amaury Lendasse

Proceedings of the International Joint Conference on Neural Networks, 2009

Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction.

Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutila, Peter A. J. Hilbers, Timo Honkela, Erkki Oja, Amaury Lendasse

Proceedings of the Artificial Neural Networks, 2009

Mutual Information Based Initialization of Forward-Backward Search for Feature Selection in Regression Problems.

Alberto Guillén, Antti Sorjamaa, Ginés Rubio, Amaury Lendasse, Ignacio Rojas

Proceedings of the Artificial Neural Networks, 2009

A faster model selection criterion for OP-ELM and OP-KNN: Hannan-Quinn criterion.

Yoan Miche, Amaury Lendasse

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

X-SOM and L-SOM: a nested approach for missing value imputation.

Paul Merlin, Antti Sorjamaa, Bertrand Maillet, Amaury Lendasse

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Applying Mutual Information for Prototype or Instance Selection in Regression Problems.

Alberto Guillén, Luis Javier Herrera, Ginés Rubio, Héctor Pomares, Amaury Lendasse, Ignacio Rojas

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2008

On Nonparametric Residual Variance Estimation.

Elia Liitiäinen, Francesco Corona, Amaury Lendasse

Neural Process. Lett., 2008

Minimising the delta test for variable selection in regression problems.

Alberto Guillén, Dusan Sovilj, Amaury Lendasse, Fernando Mateo, Ignacio Rojas

Int. J. High Perform. Syst. Archit., 2008

Long-term prediction of time series using NNE-based projection and OP-ELM.

Antti Sorjamaa, Yoan Miche, Robert Weiss, Amaury Lendasse

Proceedings of the International Joint Conference on Neural Networks, 2008

OP-ELM: Theory, Experiments and a Toolbox.

Yoan Miche, Antti Sorjamaa, Amaury Lendasse

Proceedings of the Artificial Neural Networks, 2008

Optimal Pruned K-Nearest Neighbors: OP-KNN - Application to Financial Modeling.

Qi Yu, Antti Sorjamaa, Yoan Miche, Amaury Lendasse, Eric Séverin, Alberto Guillén, Fernando Mateo

Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

Fuzzy inference based autoregressors for time series prediction using nonparametric residual variance estimation.

Federico Montesino-Pouzols, Amaury Lendasse, Angel Barriga

Proceedings of the FUZZ-IEEE 2008, 2008

A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM.

Yoan Miche, Patrick Bas, Christian Jutten, Olli Simula, Amaury Lendasse

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

Linear Projection based on Noise Variance Estimation - Application to Spectral Data.

Amaury Lendasse, Francesco Corona

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

Using the Delta Test for Variable Selection.

Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007

Methodology for long-term prediction of time series.

Antti Sorjamaa, Jin Hao, Nima Reyhani, Yongnan Ji, Amaury Lendasse

Neurocomputing, 2007

Time series prediction competition: The CATS benchmark.

Amaury Lendasse, Erkki Oja, Olli Simula, Michel Verleysen

Neurocomputing, 2007

Mutual information for the selection of relevant variables in spectrometric nonlinear modelling

Fabrice Rossi, Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen

CoRR, 2007

Advantages of Using Feature Selection Techniques on Steganalysis Schemes.

Yoan Miche, Patrick Bas, Amaury Lendasse, Christian Jutten, Olli Simula

Proceedings of the Computational and Ambient Intelligence, 2007

Non-parametric Residual Variance Estimation in Supervised Learning.

Elia Liitiäinen, Amaury Lendasse, Francesco Corona

Proceedings of the Computational and Ambient Intelligence, 2007

Gaussian Fitting Based FDA for Chemometrics.

Tuomas Kärnä, Amaury Lendasse

Proceedings of the Computational and Ambient Intelligence, 2007

An empirical dependence mesaures based on residual variance estimation.

Nima Reyhani, Amaury Lendasse

Proceedings of the 9th International Symposium on Signal Processing and Its Applications, 2007

Time Series Prediction as a Problem of Missing Values: Application to ESTSP2007 and NN3 Competition Benchmarks.

Antti Sorjamaa, Amaury Lendasse

Proceedings of the International Joint Conference on Neural Networks, 2007

Variable Scaling for Time Series Prediction: Application to the ESTSP'07 and the NN3 Forecasting Competitions.

Amaury Lendasse, Elia Liitiäinen

Proceedings of the International Joint Conference on Neural Networks, 2007

State-of-the-Art and Evolution in Public Data Sets and Competitions for System Identification, Time Series Prediction and Pattern Recognition.

Joos Vandewalle, Johan A. K. Suykens, Bart De Moor, Amaury Lendasse

Proceedings of the IEEE International Conference on Acoustics, 2007

SOM+EOF for finding missing values.

Antti Sorjamaa, Paul Merlin, Bertrand Maillet, Amaury Lendasse

Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

Nearest Neighbor Distributions and Noise Variance Estimation.

Elia Liitiäinen, Francesco Corona, Amaury Lendasse

Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006

A Feature Selection Methodology for Steganalysis.

Yoan Miche, Benoit Roue, Amaury Lendasse, Patrick Bas

Proceedings of the Multimedia Content Representation, 2006

Analysis of Fast Input Selection: Application in Time Series Prediction.

Jarkko Tikka, Amaury Lendasse, Jaakko Hollmén

Proceedings of the Artificial Neural Networks, 2006

Long-Term Prediction of Time Series Using State-Space Models.

Elia Liitiäinen, Amaury Lendasse

Proceedings of the Artificial Neural Networks, 2006

Time series prediction using DirRec strategy.

Antti Sorjamaa, Amaury Lendasse

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

EM-algorithm for training of state-space models with application to time series prediction.

Elia Liitiäinen, Nima Reyhani, Amaury Lendasse

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

Determination of the Mahalanobis matrix using nonparametric noise estimations.

Amaury Lendasse, Francesco Corona, Jin Hao, Nima Reyhani, Michel Verleysen

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

LS-SVM functional network for time series prediction.

Tuomas Kärnä, Fabrice Rossi, Amaury Lendasse

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

2005

Time series forecasting: Obtaining long term trends with self-organizing maps.

Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen

Pattern Recognit. Lett., 2005

Fast bootstrap methodology for regression model selection.

Amaury Lendasse, Geoffroy Simon, Vincent Wertz, Michel Verleysen

Neurocomputing, 2005

Vector quantization: a weighted version for time-series forecasting.

Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen

Future Gener. Comput. Syst., 2005

Input Selection for Long-Term Prediction of Time Series.

Jarkko Tikka, Jaakko Hollmén, Amaury Lendasse

Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Input and Structure Selection for k-NN Approximator.

Antti Sorjamaa, Nima Reyhani, Amaury Lendasse

Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Direct and Recursive Prediction of Time Series Using Mutual Information Selection.

Yongnan Ji, Jin Hao, Nima Reyhani, Amaury Lendasse

Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Mutual Information and <i>k</i>-Nearest Neighbors Approximator for Time Series Prediction.

Antti Sorjamaa, Jin Hao, Amaury Lendasse

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

LS-SVM Hyperparameter Selection with a Nonparametric Noise Estimator.

Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel Verleysen

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

Pruned lazy learning models for time series prediction.

Antti Sorjamaa, Amaury Lendasse, Michel Verleysen

Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

Mutual information and gamma test for input selection.

Nima Reyhani, Jin Hao, Yongnan Ji, Amaury Lendasse

Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

2004

Double quantization of the regressor space for long-term time series prediction: method and proof of stability.

Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen

Neural Networks, 2004

Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis.

John Aldo Lee, Amaury Lendasse, Michel Verleysen

Neurocomputing, 2004

Fast bootstrap for least-square support vector machines.

Amaury Lendasse, Geoffroy Simon, Vincent Wertz, Michel Verleysen

Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004

2003

Bootstrap for Model Selection: Linear Approximation of the Optimism.

Geoffroy Simon, Amaury Lendasse, Michel Verleysen

Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003

Nonlinear Time Series Prediction by Weighted Vector Quantization.

Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen

Proceedings of the Computational Science - ICCS 2003, 2003

Model Selection with Cross-Validations and Bootstraps - Application to Time Series Prediction with RBFN Models.

Amaury Lendasse, Vincent Wertz, Michel Verleysen

Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

Fast approximation of the bootstrap for model selection.

Geoffroy Simon, Amaury Lendasse, Vincent Wertz, Michel Verleysen

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

2002

Forecasting electricity consumption using nonlinear projection and self-organizing maps.

Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen

Neurocomputing, 2002

Curvilinear Distance Analysis versus Isomap.

John Aldo Lee, Amaury Lendasse, Michel Verleysen

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Width optimization of the Gaussian kernels in Radial Basis Function Networks.

Nabil Benoudjit, Cédric Archambeau, Amaury Lendasse, John Aldo Lee, Michel Verleysen

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Prediction of electric load using Kohonen maps - Application to the Polish electricity consumption.

Amaury Lendasse, Marie Cottrell, Vincent Wertz, Michel Verleysen

Proceedings of the American Control Conference, 2002

2001

Input data reduction for the prediction of financial time series.

Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vincent Wertz, Michel Verleysen

Proceedings of the 9th European Symposium on Artificial Neural Networks, 2001

2000

Time series forecasting using CCA and Kohonen maps - application to electricity consumption.

Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen

Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000

A robust non-linear projection method.

John Aldo Lee, Amaury Lendasse, Nicolas Donckers, Michel Verleysen

Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000

1999

Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection.

Michel Verleysen, Eric de Bodt, Amaury Lendasse

Proceedings of the Engineering Applications of Bio-Inspired Artificial Neural Networks, 1999

Extraction of intrinsic dimension using CCA - Application to blind sources separation.

Nicolas Donckers, Amaury Lendasse, Vincent Wertz, Michel Verleysen

Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

1998

Forecasting time-series by Kohonen classification.

Amaury Lendasse, Michel Verleysen, Eric de Bodt, Marie Cottrell, Philippe Grégoire

Proceedings of the 6th European Symposium on Artificial Neural Networks, 1998