Amaury Lendasse

According to our database1, Amaury Lendasse authored at least 166 papers between 1998 and 2018.

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2018
Adaptive and online network intrusion detection system using clustering and Extreme Learning Machines.
J. Franklin Institute, 2018

Gaussian derivative models and ensemble extreme learning machine for texture image classification.
Neurocomputing, 2018

Discriminant document embeddings with an extreme learning machine for classifying clinical narratives.
Neurocomputing, 2018

Parameter-free image segmentation with SLIC.
Neurocomputing, 2018

Generating Word Embeddings from an Extreme Learning Machine for Sentiment Analysis and Sequence Labeling Tasks.
Cognitive Computation, 2018

Extreme Learning Machines for VISualization+R: Mastering Visualization with Target Variables.
Cognitive Computation, 2018

Anomaly-Based Intrusion Detection Using Extreme Learning Machine and Aggregation of Network Traffic Statistics in Probability Space.
Cognitive Computation, 2018

A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning.
Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference, 2018

2017
Advances in extreme learning machines (ELM2015).
Neurocomputing, 2017

Adding reliability to ELM forecasts by confidence intervals.
Neurocomputing, 2017

Deep Spectral Descriptors: Learning the point-wise correspondence metric via Siamese deep neural networks.
CoRR, 2017

Brute-force Missing Data Extreme Learning Machine for Predicting Huntington's Disease.
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.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs.
Proceedings of the Hybrid Artificial Intelligent Systems - 12th International Conference, 2017

On Distance Mapping from non-Euclidean Spaces to Euclidean Spaces.
Proceedings of the Machine Learning and Knowledge Extraction, 2017

Practical Estimation of Mutual Information on Non-Euclidean Spaces.
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.
Neural Computing and Applications, 2016

Manifold learning in local tangent space via extreme learning machine.
Neurocomputing, 2016

Extreme learning machine for missing data using multiple imputations.
Neurocomputing, 2016

Comparison of combining methods using Extreme Learning Machines under small sample scenario.
Neurocomputing, 2016

Advances in extreme learning machines (ELM2014).
Neurocomputing, 2016

Singular Value Decomposition update and its application to (Inc)-OP-ELM.
Neurocomputing, 2016

Brain MRI morphological patterns extraction tool based on Extreme Learning Machine and majority vote classification.
Neurocomputing, 2016

ELMVIS+: Fast nonlinear visualization technique based on cosine distance and extreme learning machines.
Neurocomputing, 2016

A new application of machine learning in health care.
Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments, 2016

Clinical narrative classification using discriminant word embeddings with ELM.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Combined nonlinear visualization and classification: ELMVIS++C.
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.
Proceedings of the 49th Hawaii International Conference on System Sciences, 2016

Data Anonymization as a Vector Quantization Problem: Control Over Privacy for Health Data.
Proceedings of the Availability, Reliability, and Security in Information Systems, 2016

2015
Meme representations for game agents.
World Wide Web, 2015

SOM-ELM - Self-Organized Clustering using ELM.
Neurocomputing, 2015

Advances in Extreme Learning Machines (ELM2013).
Neurocomputing, 2015

Minimal Learning Machine: A novel supervised distance-based approach for regression and classification.
Neurocomputing, 2015

LARSEN-ELM: Selective ensemble of extreme learning machines using LARS for blended data.
Neurocomputing, 2015

MD-ELM: Originally Mislabeled Samples Detection using OP-ELM Model.
Neurocomputing, 2015

Arbitrary Category Classification of Websites Based on Image Content.
IEEE Comp. Int. Mag., 2015

High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications.
IEEE Access, 2015

Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes.
Proceedings of the 2015 IEEE TrustCom/BigDataSE/ISPA, 2015

Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models.
Proceedings of the Advances in Computational Intelligence, 2015

Efficient Skin Segmentation via Neural Networks: HP-ELM and BD-SOM.
Proceedings of the INNS Conference on Big Data 2015, 2015

2014
Long-term time series prediction using OP-ELM.
Neural Networks, 2014

Bankruptcy prediction using Extreme Learning Machine and financial expertise.
Neurocomputing, 2014

Ensemble delta test-extreme learning machine (DT-ELM) for regression.
Neurocomputing, 2014

Extreme learning machine towards dynamic model hypothesis in fish ethology research.
Neurocomputing, 2014

Extreme learning machines for soybean classification in remote sensing hyperspectral images.
Neurocomputing, 2014

Advances in extreme learning machines (ELM2012).
Neurocomputing, 2014

Mixture of Gaussians for distance estimation with missing data.
Neurocomputing, 2014

Fast Feature Selection in a GPU Cluster Using the Delta Test.
Entropy, 2014

Robust OS-ELM with a novel selective ensemble based on particle swarm optimization.
CoRR, 2014

HSR: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection.
CoRR, 2014

LARSEN-ELM: Selective Ensemble of Extreme Learning Machines using LARS for Blended Data.
CoRR, 2014

RMSE-ELM: Recursive Model based Selective Ensemble of Extreme Learning Machines for Robustness Improvement.
CoRR, 2014

Fast Image Recognition Based on Independent Component Analysis and Extreme Learning Machine.
Cognitive Computation, 2014

Fast Face Recognition Via Sparse Coding and Extreme Learning Machine.
Cognitive Computation, 2014

A Two-Stage Methodology Using K-NN and False-Positive Minimizing ELM for Nominal Data Classification.
Cognitive Computation, 2014

Variable selection for regression problems using Gaussian mixture models to estimate mutual information.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

The delta test: The 1-NN estimator as a feature selection criterion.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Finding Originally Mislabels with MD-ELM.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Compressive ELM: Improved Models through Exploiting Time-Accuracy Trade-Offs.
Proceedings of the Engineering Applications of Neural Networks, 2014

2013
3D object recognition based on a geometrical topology model and extreme learning machine.
Neural Computing and Applications, 2013

Distance estimation in numerical data sets with missing values.
Inf. Sci., 2013

Regularized extreme learning machine for regression with missing data.
Neurocomputing, 2013

Feature selection for nonlinear models with extreme learning machines.
Neurocomputing, 2013

Extreme Learning Machines.
IEEE Intelligent Systems, 2013

Data Preprocessing and Model Design for Medicine Problems.
Comp. Math. Methods in Medicine, 2013

Extending Extreme Learning Machine with Combination Layer.
Proceedings of the Advances in Computational Intelligence, 2013

Extreme Learning Machine: A Robust Modeling Technique? Yes!
Proceedings of the Advances in Computational Intelligence, 2013

Minimal Learning Machine: A New Distance-Based Method for Supervised Learning.
Proceedings of the Advances in Computational Intelligence, 2013

Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation.
Proceedings of the Advances in Intelligent Data Analysis XII, 2013

Forecasting Financial Markets with Classified Tactical Signals.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Visualizing dependencies of spectral features using mutual information.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012
Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator.
Proceedings of the Parallel Architectures and Bioinspired Algorithms, 2012

Adaptive kernel smoothing regression for spatio-temporal environmental datasets.
Neurocomputing, 2012

Fast variable selection for memetracker phrases time series prediction.
Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments, 2012

Relevance learning for time series inspection.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011
On the Curse of Dimensionality in Supervised Learning of Smooth Regression Functions.
Neural Processing Letters, 2011

TROP-ELM: A double-regularized ELM using LARS and Tikhonov regularization.
Neurocomputing, 2011

GPU-accelerated and parallelized ELM ensembles for large-scale regression.
Neurocomputing, 2011

Locating Anomalies Using Bayesian Factorizations and Masks.
Proceedings of the ESANN 2011, 2011

Adaptive Kernel Smoothing Regression for Spatio-Temporal Environmental Datasets.
Proceedings of the ESANN 2011, 2011

Adaptive kernel smoothing regression using vector quantization.
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.
Proceedings of the Seventh International Conference on Computational Intelligence and Security, 2011

2010
OP-ELM: optimally pruned extreme learning machine.
IEEE Trans. Neural Networks, 2010

A boundary corrected expansion of the moments of nearest neighbor distributions.
Random Struct. Algorithms, 2010

Residual variance estimation using a nearest neighbor statistic.
J. Multivariate Analysis, 2010

X-SOM and L-SOM: A double classification approach for missing value imputation.
Neurocomputing, 2010

European Symposium on Times Series Prediction.
Neurocomputing, 2010

New method for instance or prototype selection using mutual information in time series prediction.
Neurocomputing, 2010

Autoregressive time series prediction by means of fuzzy inference systems using nonparametric residual variance estimation.
Fuzzy Sets and Systems, 2010

Evolving fuzzy optimally pruned extreme learning machine for regression problems.
Evolving Systems, 2010

OP-KNN: Method and Applications.
Adv. Artificial Neural Systems, 2010

Effect of different detrending approaches on computational intelligence models of time series.
Proceedings of the International Joint Conference on Neural Networks, 2010

Interpreting Extreme Learning Machine as an Approximation to an Infinite Neural Network.
Proceedings of the KDIR 2010, 2010

Evolving fuzzy Optimally Pruned Extreme Learning Machine: A comparative analysis.
Proceedings of the FUZZ-IEEE 2010, 2010

Machine Learning Techniques based on Random Projections.
Proceedings of the ESANN 2010, 2010

Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs.
Proceedings of the ESANN 2010, 2010

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs.
Proceedings of the ESANN 2010, 2010

Ensembles of Locally Linear Models: Application to Bankruptcy Prediction.
Proceedings of The 2010 International Conference on Data Mining, 2010

2009
Functional Dimension Reduction for Chemometrics.
Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

Residual variance estimation in machine learning.
Neurocomputing, 2009

A SOM-based approach to estimating product properties from spectroscopic measurements.
Neurocomputing, 2009

Reliable Steganalysis Using a Minimum Set of Samples and Features.
EURASIP J. Information Security, 2009

Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database.
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.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Efficient Parallel Feature Selection for Steganography Problems.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Long-term prediction of time series by combining direct and MIMO strategies.
Proceedings of the International Joint Conference on Neural Networks, 2009

Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction.
Proceedings of the Artificial Neural Networks, 2009

Mutual Information Based Initialization of Forward-Backward Search for Feature Selection in Regression Problems.
Proceedings of the Artificial Neural Networks, 2009

A faster model selection criterion for OP-ELM and OP-KNN: Hannan-Quinn criterion.
Proceedings of the ESANN 2009, 2009

X-SOM and L-SOM: a nested approach for missing value imputation.
Proceedings of the ESANN 2009, 2009

Applying Mutual Information for Prototype or Instance Selection in Regression Problems.
Proceedings of the ESANN 2009, 2009

2008
On Nonparametric Residual Variance Estimation.
Neural Processing Letters, 2008

Minimising the delta test for variable selection in regression problems.
IJHPSA, 2008

Long-term prediction of time series using NNE-based projection and OP-ELM.
Proceedings of the International Joint Conference on Neural Networks, 2008

OP-ELM: Theory, Experiments and a Toolbox.
Proceedings of the Artificial Neural Networks, 2008

Optimal Pruned K-Nearest Neighbors: OP-KNN - Application to Financial Modeling.
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.
Proceedings of the FUZZ-IEEE 2008, 2008

A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM.
Proceedings of the ESANN 2008, 2008

Linear Projection based on Noise Variance Estimation - Application to Spectral Data.
Proceedings of the ESANN 2008, 2008

Using the Delta Test for Variable Selection.
Proceedings of the ESANN 2008, 2008

2007
Methodology for long-term prediction of time series.
Neurocomputing, 2007

Time series prediction competition: The CATS benchmark.
Neurocomputing, 2007

Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps
CoRR, 2007

Mutual information for the selection of relevant variables in spectrometric nonlinear modelling
CoRR, 2007

Advantages of Using Feature Selection Techniques on Steganalysis Schemes.
Proceedings of the Computational and Ambient Intelligence, 2007

Non-parametric Residual Variance Estimation in Supervised Learning.
Proceedings of the Computational and Ambient Intelligence, 2007

Gaussian Fitting Based FDA for Chemometrics.
Proceedings of the Computational and Ambient Intelligence, 2007

An empirical dependence mesaures based on residual variance estimation.
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.
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.
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.
Proceedings of the IEEE International Conference on Acoustics, 2007

SOM+EOF for finding missing values.
Proceedings of the ESANN 2007, 2007

Nearest Neighbor Distributions and Noise Variance Estimation.
Proceedings of the ESANN 2007, 2007

2006
A Feature Selection Methodology for Steganalysis.
Proceedings of the Multimedia Content Representation, 2006

Analysis of Fast Input Selection: Application in Time Series Prediction.
Proceedings of the Artificial Neural Networks, 2006

Long-Term Prediction of Time Series Using State-Space Models.
Proceedings of the Artificial Neural Networks, 2006

Time series prediction using DirRec strategy.
Proceedings of the ESANN 2006, 2006

EM-algorithm for training of state-space models with application to time series prediction.
Proceedings of the ESANN 2006, 2006

Determination of the Mahalanobis matrix using nonparametric noise estimations.
Proceedings of the ESANN 2006, 2006

LS-SVM functional network for time series prediction.
Proceedings of the ESANN 2006, 2006

2005
Time series forecasting: Obtaining long term trends with self-organizing maps.
Pattern Recognition Letters, 2005

Fast bootstrap methodology for regression model selection.
Neurocomputing, 2005

Vector quantization: a weighted version for time-series forecasting.
Future Generation Comp. Syst., 2005

Input Selection for Long-Term Prediction of Time Series.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Input and Structure Selection for k-NN Approximator.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Direct and Recursive Prediction of Time Series Using Mutual Information Selection.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Mutual Information and k-Nearest Neighbors Approximator for Time Series Prediction.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

LS-SVM Hyperparameter Selection with a Nonparametric Noise Estimator.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

Pruned lazy learning models for time series prediction.
Proceedings of the ESANN 2005, 2005

Mutual information and gamma test for input selection.
Proceedings of the ESANN 2005, 2005

2004
Double quantization of the regressor space for long-term time series prediction: method and proof of stability.
Neural Networks, 2004

Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis.
Neurocomputing, 2004

Fast bootstrap for least-square support vector machines.
Proceedings of the ESANN 2004, 2004

2003
Bootstrap for Model Selection: Linear Approximation of the Optimism.
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003

Nonlinear Time Series Prediction by Weighted Vector Quantization.
Proceedings of the Computational Science - ICCS 2003, 2003

Model Selection with Cross-Validations and Bootstraps - Application to Time Series Prediction with RBFN Models.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

Fast approximation of the bootstrap for model selection.
Proceedings of the ESANN 2003, 2003

2002
Forecasting electricity consumption using nonlinear projection and self-organizing maps.
Neurocomputing, 2002

Curvilinear Distance Analysis versus Isomap.
Proceedings of the ESANN 2002, 2002

Width optimization of the Gaussian kernels in Radial Basis Function Networks.
Proceedings of the ESANN 2002, 2002

2001
Input data reduction for the prediction of financial time series.
Proceedings of the ESANN 2001, 2001

2000
Time series forecasting using CCA and Kohonen maps - application to electricity consumption.
Proceedings of the ESANN 2000, 2000

A robust non-linear projection method.
Proceedings of the ESANN 2000, 2000

1999
Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection.
Proceedings of the Engineering Applications of Bio-Inspired Artificial Neural Networks, 1999

Extraction of intrinsic dimension using CCA - Application to blind sources separation.
Proceedings of the ESANN 1999, 1999

1998
Forecasting time-series by Kohonen classification.
Proceedings of the ESANN 1998, 1998


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