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2020 – today
- 2023
[c103]Brandon Warner, Edward R. Ratner
, Amaury Lendasse:
X-ELM: A Fast Explainability Approach for Extreme Learning Machines. IWANN (2) 2023: 411-422- [c102]Tamirat Atsemegiorgis, Leonardo Espinosa Leal, Amaury Lendasse, Stefan Mattbäck, Kaj-Mikael Björk, Anton Akusok:
Acid Sulfate Soils Classification and Prediction from Environmental Covariates Using Extreme Learning Machines. IWANN (1) 2023: 614-625 - [c101]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:
USDOT Tier-1 University Transportation Center for Advancing Cybersecurity Research and Education. MOST 2023: 237-241 - 2021
- [c100]Chris Bronk, Amaury Lendasse, Peggy Lindner, Dan S. Wallach, Barbara Hammer:
Machine Learning for Measuring and Analyzing Online Social Communications. ESANN 2021 - [c99]Baichuan Chi, Amaury Lendasse, Edward R. Ratner, Renjie Hu:
A Multi-ELM Model for Incomplete Data. ESANN 2021 - [c98]Amaury Lendasse, Kallin Khan, Edward R. Ratner:
NNBMSS: a Novel and Fast Method for Model Structure Selection. ESANN 2021 - [c97]Anton Akusok, Leonardo Espinosa Leal, Kaj-Mikael Björk, Amaury Lendasse, Renjie Hu:
Handwriting features based detection of fake signatures. PETRA 2021: 86-89 - 2020
- [j77]Renjie Hu, Amany Farag, Kaj-Mikael Björk, Amaury Lendasse:
Using machine learning to identify top predictors for nurses' willingness to report medication errors. Array 8: 100049 (2020) - [j76]Renjie Hu, Edward R. Ratner, David E. Stewart, Kaj-Mikael Björk, Amaury Lendasse:
A modified Lanczos Algorithm for fast regularization of extreme learning machines. Neurocomputing 414: 172-181 (2020) - [j75]Zhiyu Sun, Yusen He, Andrey Gritsenko, Amaury Lendasse, Stephen Baek:
Embedded spectral descriptors: learning the point-wise correspondence metric via Siamese neural networks. J. Comput. Des. Eng. 7(1): 18-29 (2020) - [j74]Shaoping Xiao, Renjie Hu, Zhen Li, Siamak Attarian, Kaj-Mikael Björk, Amaury Lendasse:
A machine-learning-enhanced hierarchical multiscale method for bridging from molecular dynamics to continua. Neural Comput. Appl. 32(18): 14359-14373 (2020) - [c96]Kallin Khan, Edward R. Ratner, Robert Ludwig, Amaury Lendasse:
Feature Bagging and Extreme Learning Machines: Machine Learning with Severe Memory Constraints. IJCNN 2020: 1-7 - [e1]Jiuwen Cao, Chi-Man Vong, Yoan Miche, Amaury Lendasse:
Proceedings of ELM 2018, International Conference on Extreme Learning Machine, Singapore, 21-23 November 2018. Proceedings in Adaptation, Learning and Optimization 11, Springer 2020, ISBN 978-3-030-23306-8 [contents]
2010 – 2019
- 2019
- [j73]Yoan Miche, Wei Ren, Ian Oliver, Silke Holtmanns, Amaury Lendasse:
A Framework for Privacy Quantification: Measuring the Impact of Privacy Techniques Through Mutual Information, Distance Mapping, and Machine Learning. Cogn. Comput. 11(2): 241-261 (2019) - [j72]Renjie Hu, Karl Ratner, Edward R. Ratner, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse:
ELM-SOM+: A continuous mapping for visualization. Neurocomputing 365: 147-156 (2019) - [j71]Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse:
Per-sample prediction intervals for extreme learning machines. Int. J. Mach. Learn. Cybern. 10(5): 991-1001 (2019) - [j70]Bo He, Yan Song, Yuemei Zhu, Qixin Sha, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse:
Local receptive fields based extreme learning machine with hybrid filter kernels for image classification. Multidimens. Syst. Signal Process. 30(3): 1149-1169 (2019) - [j69]Wan-Yu Deng, Amaury Lendasse, Yew-Soon Ong, Ivor Wai-Hung Tsang, Lin Chen, Qing-Hua Zheng:
Domain Adaption via Feature Selection on Explicit Feature Map. IEEE Trans. Neural Networks Learn. Syst. 30(4): 1180-1190 (2019) - [c95]Anton Akusok, Kaj-Mikael Björk, Leonardo Espinosa Leal, Yoan Miche, Renjie Hu, Amaury Lendasse:
Spiking networks for improved cognitive abilities of edge computing devices. PETRA 2019: 307-308 - [i13]Anton Akusok, Emil Eirola, Yoan Miche, Ian Oliver, Kaj-Mikael Björk, Andrey Gritsenko, Stephen Baek, Amaury Lendasse:
Incremental ELMVIS for unsupervised learning. CoRR abs/1912.08638 (2019) - [i12]Leonardo Espinosa Leal, Kaj-Mikael Björk, Amaury Lendasse, Anton Akusok:
A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning. CoRR abs/1912.08644 (2019) - [i11]Anton Akusok, Kaj-Mikael Björk, Leonardo Espinosa Leal, Yoan Miche, Renjie Hu, Amaury Lendasse:
Spiking Networks for Improved Cognitive Abilities of Edge Computing Devices. CoRR abs/1912.09083 (2019) - [i10]Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Amaury Lendasse:
Extreme Learning Tree. CoRR abs/1912.09087 (2019) - [i9]Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse:
Per-sample Prediction Intervals for Extreme Learning Machines. CoRR abs/1912.09090 (2019) - [i8]Anton Akusok, Mirka Saarela, Tommi Kärkkäinen, Kaj-Mikael Björk, Amaury Lendasse:
Mislabel Detection of Finnish Publication Ranks. CoRR abs/1912.09094 (2019) - 2018
- [j68]Andrey Gritsenko, Anton Akusok, Stephen Baek, Yoan Miche, Amaury Lendasse:
Extreme Learning Machines for VISualization+R: Mastering Visualization with Target Variables. Cogn. Comput. 10(3): 464-477 (2018) - [j67]Paula Lauren, Guangzhi Qu, Jucheng Yang, Paul Watta, Guang-Bin Huang, Amaury Lendasse:
Generating Word Embeddings from an Extreme Learning Machine for Sentiment Analysis and Sequence Labeling Tasks. Cogn. Comput. 10(4): 625-638 (2018) - [j66]Buse Gul Atli, Yoan Miche, Aapo Kalliola, Ian Oliver, Silke Holtmanns, Amaury Lendasse:
Anomaly-Based Intrusion Detection Using Extreme Learning Machine and Aggregation of Network Traffic Statistics in Probability Space. Cogn. Comput. 10(5): 848-863 (2018) - [j65]Yan Song, Shujing Zhang, Bo He, Qixin Sha, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse:
Gaussian derivative models and ensemble extreme learning machine for texture image classification. Neurocomputing 277: 53-64 (2018) - [j64]Paula Lauren, Guangzhi Qu, Feng Zhang, Amaury Lendasse:
Discriminant document embeddings with an extreme learning machine for classifying clinical narratives. Neurocomputing 277: 129-138 (2018) - [j63]Fabian Boemer, Edward R. Ratner, Amaury Lendasse:
Parameter-free image segmentation with SLIC. Neurocomputing 277: 228-236 (2018) - [j62]Setareh Roshan, Yoan Miche, Anton Akusok, Amaury Lendasse:
Adaptive and online network intrusion detection system using clustering and Extreme Learning Machines. J. Frankl. Inst. 355(4): 1752-1779 (2018) - [c94]Zhen Li, Karl Ratner, Edward R. Ratner, Kallin Khan, Kaj-Mikael Björk, Amaury Lendasse:
A Novel ELM Ensemble for Time Series Prediction. ELM 2018: 283-291 - [c93]Renjie Hu, Venous Roshdibenam, Hans J. Johnson, Emil Eirola, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse:
ELM-SOM: A Continuous Self-Organizing Map for Visualization. IJCNN 2018: 1-8 - [c92]Leonardo Espinosa Leal, Kaj-Mikael Björk, Amaury Lendasse, Anton Akusok:
A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning. PETRA 2018: 13-16 - 2017
- [j61]Anton Akusok, Andrey Gritsenko, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Paula Lauren, Amaury Lendasse:
Adding reliability to ELM forecasts by confidence intervals. Neurocomputing 219: 232-241 (2017) - [j60]Amaury Lendasse, Chi-Man Vong, Kar-Ann Toh, Yoan Miche, Guang-Bin Huang:
Advances in extreme learning machines (ELM2015). Neurocomputing 261: 1-3 (2017) - [c91]Wei Ren, Yoan Miche, Ian Oliver, Silke Holtmanns, Kaj-Mikael Björk, Amaury Lendasse:
On Distance Mapping from non-Euclidean Spaces to Euclidean Spaces. CD-MAKE 2017: 3-13 - [c90]Yoan Miche, Ian Oliver, Wei Ren, Silke Holtmanns, Anton Akusok, Amaury Lendasse:
Practical Estimation of Mutual Information on Non-Euclidean Spaces. CD-MAKE 2017: 123-136 - [c89]Anton Akusok, Emil Eirola, Yoan Miché, Andrey Gritsenko, Amaury Lendasse:
Advanced query strategies for Active Learning with Extreme Learning Machines. ESANN 2017 - [c88]Andrey Gritsenko, Emil Eirola, Daniel Schupp, Edward R. Ratner, Amaury Lendasse:
Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs. HAIS 2017: 293-305 - [c87]Paula Lauren, Guangzhi Qu, Guang-Bin Huang, Paul Watta, Amaury Lendasse:
A low-dimensional vector representation for words using an extreme learning machine. IJCNN 2017: 1817-1822 - [c86]Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Yoan Miché, Hans J. Johnson, Amaury Lendasse:
Brute-force Missing Data Extreme Learning Machine for Predicting Huntington's Disease. PETRA 2017: 189-192 - [i7]Zhiyu Sun, Yusen He, Andrey Gritsenko, Amaury Lendasse, Stephen Baek:
Deep Spectral Descriptors: Learning the point-wise correspondence metric via Siamese deep neural networks. CoRR abs/1710.06368 (2017) - 2016
- [j59]Amaury Lendasse, Chi-Man Vong, Yoan Miche, Guang-Bin Huang:
Advances in extreme learning machines (ELM2014). Neurocomputing 174: 1-3 (2016) - [j58]Dusan Sovilj, Kaj-Mikael Björk, Amaury Lendasse:
Comparison of combining methods using Extreme Learning Machines under small sample scenario. Neurocomputing 174: 4-17 (2016) - [j57]Qian Wang, Weiguo Wang, Rui Nian, Bo He, Yue Shen, Kaj-Mikael Björk, Amaury Lendasse:
Manifold learning in local tangent space via extreme learning machine. Neurocomputing 174: 18-30 (2016) - [j56]Alexander Grigorievskiy, Yoan Miche, Maarit Käpylä, Amaury Lendasse:
Singular Value Decomposition update and its application to (Inc)-OP-ELM. Neurocomputing 174: 99-108 (2016) - [j55]Dusan Sovilj, Emil Eirola, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Anton Akusok, Amaury Lendasse:
Extreme learning machine for missing data using multiple imputations. Neurocomputing 174: 220-231 (2016) - [j54]Maite Termenon, Manuel Graña, Alexandre Savio, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse:
Brain MRI morphological patterns extraction tool based on Extreme Learning Machine and majority vote classification. Neurocomputing 174: 344-351 (2016) - [j53]Anton Akusok, Stephen Baek, Yoan Miché, Kaj-Mikael Björk, Rui Nian, Paula Lauren, Amaury Lendasse:
ELMVIS+: Fast nonlinear visualization technique based on cosine distance and extreme learning machines. Neurocomputing 205: 247-263 (2016) - [j52]Bo Han, Bo He, Tingting Sun, Tianhong Yan, Mengmeng Ma, Yue Shen, Amaury Lendasse:
HSR: L 1/2-regularized sparse representation for fast face recognition using hierarchical feature selection. Neural Comput. Appl. 27(2): 305-320 (2016) - [c85]Yoan Miché, Ian Oliver, Silke Holtmanns, Aapo Kalliola, Anton Akusok, Amaury Lendasse, Kaj-Mikael Björk:
Data Anonymization as a Vector Quantization Problem: Control Over Privacy for Health Data. CD-ARES 2016: 193-203 - [c84]Patrick Kouontchou, Amaury Lendasse, Yoan Miché, Alejandro Modesto, Peter Sarlin, Bertrand Maillet:
A R-SOM Analysis of the Link between Financial Market Conditions and a Systemic Risk Index Based on ICA-Factors of Systemic Risk Measures. HICSS 2016: 1759-1770 - [c83]Andrey Gritsenko, Anton Akusok, Yoan Miché, Kaj-Mikael Björk, Stephen Baek, Amaury Lendasse:
Combined nonlinear visualization and classification: ELMVIS++C. IJCNN 2016: 2617-2624 - [c82]Paula Lauren, Guangzhi Qu, Feng Zhang, Amaury Lendasse:
Clinical narrative classification using discriminant word embeddings with ELM. IJCNN 2016: 2931-2938 - [c81]Kaj-Mikael Björk, Emil Eirola, Yoan Miché, Amaury Lendasse:
A new application of machine learning in health care. PETRA 2016: 49 - 2015
- [j51]Anton Akusok, Kaj-Mikael Björk, Yoan Miché, Amaury Lendasse:
High-Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications. IEEE Access 3: 1011-1025 (2015) - [j50]Anton Akusok, Yoan Miche, Juha Karhunen, Kaj-Mikael Björk, Rui Nian, Amaury Lendasse:
Arbitrary Category Classification of Websites Based on Image Content. IEEE Comput. Intell. Mag. 10(2): 30-41 (2015) - [j49]Amaury Lendasse, Qing He, Yoan Miché, Guang-Bin Huang:
Advances in Extreme Learning Machines (ELM2013). Neurocomputing 149: 158-159 (2015) - [j48]Bo Han, Bo He, Rui Nian, Mengmeng Ma, Shujing Zhang, Minghui Li, Amaury Lendasse:
LARSEN-ELM: Selective ensemble of extreme learning machines using LARS for blended data. Neurocomputing 149: 285-294 (2015) - [j47]Anton Akusok, David Veganzones, Yoan Miché, Kaj-Mikael Björk, Philippe du Jardin, Eric Séverin, Amaury Lendasse:
MD-ELM: Originally Mislabeled Samples Detection using OP-ELM Model. Neurocomputing 159: 242-250 (2015) - [j46]Amauri Holanda de Souza Júnior, Francesco Corona, Guilherme De A. Barreto, Yoan Miché, Amaury Lendasse:
Minimal Learning Machine: A novel supervised distance-based approach for regression and classification. Neurocomputing 164: 34-44 (2015) - [j45]Yoan Miché, Anton Akusok, David Veganzones, Kaj-Mikael Björk, Eric Séverin, Philippe du Jardin, Maite Termenon, Amaury Lendasse:
SOM-ELM - Self-Organized Clustering using ELM. Neurocomputing 165: 238-254 (2015) - [j44]Yoan Miche, Meng-Hiot Lim, Amaury Lendasse, Yew-Soon Ong:
Meme representations for game agents. World Wide Web 18(2): 215-234 (2015) - [c80]Kaj-Mikael Björk, Patrick Kouontchou, Amaury Lendasse, Yoan Miché, Bertrand Maillet:
Towards a Tomographic Index of Systemic Risk Measures. ESANN 2015 - [c79]C. Swaney, Anton Akusok, Kaj-Mikael Björk, Yoan Miché, Amaury Lendasse:
Efficient Skin Segmentation via Neural Networks: HP-ELM and BD-SOM. INNS Conference on Big Data 2015: 400-409 - [c78]Emil Eirola, Andrey Gritsenko, Anton Akusok, Kaj-Mikael Björk, Yoan Miche, Dusan Sovilj, Rui Nian, Bo He, Amaury Lendasse:
Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models. IWANN (2) 2015: 153-164 - [c77]Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Yoan Miché, Amaury Lendasse, Juha Karhunen:
Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes. TrustCom/BigDataSE/ISPA (1) 2015: 198-205 - 2014
- [j43]Bo He, Dongxun Xu, Rui Nian, Mark van Heeswijk, Qi Yu, Yoan Miche, Amaury Lendasse:
Fast Face Recognition Via Sparse Coding and Extreme Learning Machine. Cogn. Comput. 6(2): 264-277 (2014) - [j42]Shujing Zhang, Bo He, Rui Nian, Jing Wang, Bo Han, Amaury Lendasse, Guang Yuan:
Fast Image Recognition Based on Independent Component Analysis and Extreme Learning Machine. Cogn. Comput. 6(3): 405-422 (2014) - [j41]Anton Akusok, Yoan Miche, Jozsef Hegedus, Rui Nian, Amaury Lendasse:
A Two-Stage Methodology Using K-NN and False-Positive Minimizing ELM for Nominal Data Classification. Cogn. Comput. 6(3): 432-445 (2014) - [j40]Alberto Guillén, M. Isabel García Arenas, Mark van Heeswijk, Dusan Sovilj, Amaury Lendasse, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas:
Fast Feature Selection in a GPU Cluster Using the Delta Test. Entropy 16(2): 854-869 (2014) - [j39]Amaury Lendasse, Qing He, Yoan Miche, Guang-Bin Huang:
Advances in extreme learning machines (ELM2012). Neurocomputing 128: 1-3 (2014) - [j38]Ramón Moreno, Francesco Corona, Amaury Lendasse, Manuel Graña, Lênio S. Galvão:
Extreme learning machines for soybean classification in remote sensing hyperspectral images. Neurocomputing 128: 207-216 (2014) - [j37]Rui Nian, Bo He, Bing Zheng, Mark van Heeswijk, Qi Yu, Yoan Miche, Amaury Lendasse:
Extreme learning machine towards dynamic model hypothesis in fish ethology research. Neurocomputing 128: 273-284 (2014) - [j36]Qi Yu, Yoan Miche, Eric Séverin, Amaury Lendasse:
Bankruptcy prediction using Extreme Learning Machine and financial expertise. Neurocomputing 128: 296-302 (2014) - [j35]Qi Yu, Mark van Heeswijk, Yoan Miche, Rui Nian, Bo He, Eric Séverin, Amaury Lendasse:
Ensemble delta test-extreme learning machine (DT-ELM) for regression. Neurocomputing 129: 153-158 (2014) - [j34]Emil Eirola, Amaury Lendasse, Vincent Vandewalle, Christophe Biernacki:
Mixture of Gaussians for distance estimation with missing data. Neurocomputing 131: 32-42 (2014) - [j33]Alexander Grigorievskiy, Yoan Miche, Anne-Mari Ventelä, Eric Séverin, Amaury Lendasse:
Long-term time series prediction using OP-ELM. Neural Networks 51: 50-56 (2014) - [c76]Mark van Heeswijk, Amaury Lendasse, Yoan Miché:
Compressive ELM: Improved Models through Exploiting Time-Accuracy Trade-Offs. EANN 2014: 165-174 - [c75]Anton Akusok, David Veganzones, Yoan Miché, Eric Séverin, Amaury Lendasse:
Finding Originally Mislabels with MD-ELM. ESANN 2014 - [c74]Emil Eirola, Amaury Lendasse, Juha Karhunen:
Variable selection for regression problems using Gaussian mixture models to estimate mutual information. IJCNN 2014: 1606-1613 - [c73]Emil Eirola, Amaury Lendasse, Francesco Corona, Michel Verleysen:
The delta test: The 1-NN estimator as a feature selection criterion. IJCNN 2014: 4214-4222 - [i6]Bo Han, Bo He, Rui Nian, Mengmeng Ma, Shujing Zhang, Minghui Li, Amaury Lendasse:
LARSEN-ELM: Selective Ensemble of Extreme Learning Machines using LARS for Blended Data. CoRR abs/1408.2003 (2014) - [i5]Bo Han, Bo He, Mengmeng Ma, Tingting Sun, Tianhong Yan, Amaury Lendasse:
RMSE-ELM: Recursive Model based Selective Ensemble of Extreme Learning Machines for Robustness Improvement. CoRR abs/1408.2004 (2014) - [i4]Yang Liu, Bo He, Diya Dong, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse:
Robust OS-ELM with a novel selective ensemble based on particle swarm optimization. CoRR abs/1408.2890 (2014) - [i3]Bo Han, Bo He, Tingting Sun, Mengmeng Ma, Amaury Lendasse:
HSR: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection. CoRR abs/1409.6448 (2014) - 2013
- [j32]Alberto Guillén, Amaury Lendasse, Guilherme A. Barreto:
Data Preprocessing and Model Design for Medicine Problems. Comput. Math. Methods Medicine 2013: 625623:1 (2013) - [j31]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:
Extreme Learning Machines. IEEE Intell. Syst. 28(6): 30-59 (2013) - [j30]Qi Yu, Yoan Miche, Emil Eirola, Mark van Heeswijk, Eric Séverin, Amaury Lendasse:
Regularized extreme learning machine for regression with missing data. Neurocomputing 102: 45-51 (2013) - [j29]Benoît Frénay, Mark van Heeswijk, Yoan Miche, Michel Verleysen, Amaury Lendasse:
Feature selection for nonlinear models with extreme learning machines. Neurocomputing 102: 111-124 (2013) - [j28]Emil Eirola, Gauthier Doquire, Michel Verleysen, Amaury Lendasse:
Distance estimation in numerical data sets with missing values. Inf. Sci. 240: 115-128 (2013) - [j27]Rui Nian, Bo He, Amaury Lendasse:
3D object recognition based on a geometrical topology model and extreme learning machine. Neural Comput. Appl. 22(3-4): 427-433 (2013) - [c72]Andrej Gisbrecht, Yoan Miché, Barbara Hammer, Amaury Lendasse:
Visualizing dependencies of spectral features using mutual information. ESANN 2013 - [c71]Patrick Kouontchou, Amaury Lendasse, Yoan Miché, Bertrand Maillet:
Forecasting Financial Markets with Classified Tactical Signals. ESANN 2013 - [c70]Emil Eirola, Amaury Lendasse:
Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation. IDA 2013: 162-173 - [c69]Amaury Lendasse, Anton Akusok, Olli Simula, Francesco Corona, Mark van Heeswijk, Emil Eirola, Yoan Miche:
Extreme Learning Machine: A Robust Modeling Technique? Yes! IWANN (1) 2013: 17-35 - [c68]Amauri Holanda de Souza Júnior, Francesco Corona, Yoan Miche, Amaury Lendasse, Guilherme A. Barreto, Olli Simula:
Minimal Learning Machine: A New Distance-Based Method for Supervised Learning. IWANN (1) 2013: 408-416 - [c67]Dusan Sovilj, Amaury Lendasse, Olli Simula:
Extending Extreme Learning Machine with Combination Layer. IWANN (1) 2013: 417-426 - 2012
- [j26]Federico Montesino-Pouzols, Amaury Lendasse:
Adaptive kernel smoothing regression for spatio-temporal environmental datasets. Neurocomputing 90: 59-65 (2012) - [c66]Andrej Gisbrecht, Dusan Sovilj, Barbara Hammer, Amaury Lendasse:
Relevance learning for time series inspection. ESANN 2012 - [c65]Yoan Miche, Tatiana Chistiakova, Anton Akusok, Amaury Lendasse, Rui Nian, Alberto Guillén:
Fast variable selection for memetracker phrases time series prediction. PETRA 2012: 47 - [p1]Alberto Guillén, Dusan Sovilj, Mark van Heeswijk, Luis Javier Herrera, Amaury Lendasse, Héctor Pomares, Ignacio Rojas:
Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator. Parallel Architectures and Bioinspired Algorithms 2012: 243-266 - 2011
- [j25]Yoan Miche, Mark van Heeswijk, Patrick Bas, Olli Simula, Amaury Lendasse:
TROP-ELM: A double-regularized ELM using LARS and Tikhonov regularization. Neurocomputing 74(16): 2413-2421 (2011) - [j24]Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse:
GPU-accelerated and parallelized ELM ensembles for large-scale regression. Neurocomputing 74(16): 2430-2437 (2011) - [j23]Elia Liitiäinen, Francesco Corona, Amaury Lendasse:
On the Curse of Dimensionality in Supervised Learning of Smooth Regression Functions. Neural Process. Lett. 34(2): 133-154 (2011) - [c64]Jozsef Hegedus, Yoan Miche, Alexander Ilin, Amaury Lendasse:
Methodology for Behavioral-based Malware Analysis and Detection Using Random Projections and K-Nearest Neighbors Classifiers. CIS 2011: 1016-1023 - [c63]Federico Montesino-Pouzols, Amaury Lendasse:
Adaptive kernel smoothing regression using vector quantization. EAIS 2011: 85-92 - [c62]Federico Montesino-Pouzols, Amaury Lendasse:
Adaptive Kernel Smoothing Regression for Spatio-Temporal Environmental Datasets. ESANN 2011 - [c61]Li Yao, Amaury Lendasse, Francesco Corona:
Locating Anomalies Using Bayesian Factorizations and Masks. ESANN 2011 - 2010
- [j22]Qi Yu, Yoan Miché, Antti Sorjamaa, Alberto Guillén, Amaury Lendasse, Eric Séverin:
OP-KNN: Method and Applications. Adv. Artif. Neural Syst. 2010: 597373:1-597373:6 (2010) - [j21]Federico Montesino-Pouzols, Amaury Lendasse:
Evolving fuzzy optimally pruned extreme learning machine for regression problems. Evol. Syst. 1(1): 43-58 (2010) - [j20]Federico Montesino-Pouzols, Amaury Lendasse, Angel Barriga Barros:
Autoregressive time series prediction by means of fuzzy inference systems using nonparametric residual variance estimation. Fuzzy Sets Syst. 161(4): 471-497 (2010) - [j19]Paul Merlin, Antti Sorjamaa, Bertrand Maillet, Amaury Lendasse:
X-SOM and L-SOM: A double classification approach for missing value imputation. Neurocomputing 73(7-9): 1103-1108 (2010) - [j18]Amaury Lendasse, Timo Honkela, Olli Simula:
European Symposium on Times Series Prediction. Neurocomputing 73(10-12): 1919-1922 (2010) - [j17]Alberto Guillén, Luis Javier Herrera, Ginés Rubio, Héctor Pomares, Amaury Lendasse, Ignacio Rojas:
New method for instance or prototype selection using mutual information in time series prediction. Neurocomputing 73(10-12): 2030-2038 (2010) - [j16]Elia Liitiäinen, Francesco Corona, Amaury Lendasse:
Residual variance estimation using a nearest neighbor statistic. J. Multivar. Anal. 101(4): 811-823 (2010) - [j15]Elia Liitiäinen, Amaury Lendasse, Francesco Corona:
A boundary corrected expansion of the moments of nearest neighbor distributions. Random Struct. Algorithms 37(2): 223-247 (2010) - [j14]Yoan Miche, Antti Sorjamaa, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse:
OP-ELM: optimally pruned extreme learning machine. IEEE Trans. Neural Networks 21(1): 158-162 (2010) - [c60]Laura Kainulainen, Qi Yu, Yoan Miche, Emil Eirola, Eric Séverin, Amaury Lendasse:
Ensembles of Locally Linear Models: Application to Bankruptcy Prediction. DMIN 2010: 280-286 - [c59]Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse:
Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs. ESANN 2010 - [c58]Yoan Miche, Emil Eirola, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse, Michel Verleysen:
Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs. ESANN 2010 - [c57]Yoan Miche, Benjamin Schrauwen, Amaury Lendasse:
Machine Learning Techniques based on Random Projections. ESANN 2010 - [c56]Federico Montesino-Pouzols, Amaury Lendasse:
Evolving fuzzy Optimally Pruned Extreme Learning Machine: A comparative analysis. FUZZ-IEEE 2010: 1-8 - [c55]Elina Parviainen, Jaakko Riihimäki, Yoan Miche, Amaury Lendasse:
Interpreting Extreme Learning Machine as an Approximation to an Infinite Neural Network. KDIR 2010: 65-73 - [c54]Federico Montesino-Pouzols, Amaury Lendasse:
Effect of different detrending approaches on computational intelligence models of time series. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j13]Yoan Miche, Patrick Bas, Amaury Lendasse, Christian Jutten, Olli Simula:
Reliable Steganalysis Using a Minimum Set of Samples and Features. EURASIP J. Inf. Secur. 2009 (2009) - [j12]Elia Liitiäinen, Michel Verleysen, Francesco Corona, Amaury Lendasse:
Residual variance estimation in machine learning. Neurocomputing 72(16-18): 3692-3703 (2009) - [j11]Francesco Corona, Elia Liitiäinen, Amaury Lendasse, Lorenzo Sassu, Stefano Melis, Roberto Baratti:
A SOM-based approach to estimating product properties from spectroscopic measurements. Neurocomputing 73(1-3): 71-79 (2009) - [c53]Alberto Guillén, Luis Javier Herrera, Ginés Rubio, Héctor Pomares, Amaury Lendasse, Ignacio Rojas:
Applying Mutual Information for Prototype or Instance Selection in Regression Problems. ESANN 2009 - [c52]Paul Merlin, Antti Sorjamaa, Bertrand Maillet, Amaury Lendasse:
X-SOM and L-SOM: a nested approach for missing value imputation. ESANN 2009 - [c51]Yoan Miche, Amaury Lendasse:
A faster model selection criterion for OP-ELM and OP-KNN: Hannan-Quinn criterion. ESANN 2009 - [c50]Alberto Guillén, Antti Sorjamaa, Ginés Rubio, Amaury Lendasse, Ignacio Rojas:
Mutual Information Based Initialization of Forward-Backward Search for Feature Selection in Regression Problems. ICANN (1) 2009: 1-9 - [c49]Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutila, Peter A. J. Hilbers, Timo Honkela, Erkki Oja, Amaury Lendasse:
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction. ICANN (2) 2009: 305-314 - [c48]Souhaib Ben Taieb, Gianluca Bontempi, Antti Sorjamaa, Amaury Lendasse:
Long-term prediction of time series by combining direct and MIMO strategies. IJCNN 2009: 3054-3061 - [c47]Fernando Mateo, Dusan Sovilj, Rafael Gadea Gironés, Amaury Lendasse:
RCGA-S/RCGA-SP Methods to Minimize the Delta Test for Regression Tasks. IWANN (1) 2009: 359-366 - [c46]Alberto Guillén, Antti Sorjamaa, Yoan Miche, Amaury Lendasse, Ignacio Rojas:
Efficient Parallel Feature Selection for Steganography Problems. IWANN (1) 2009: 1224-1231 - [c45]Antti Sorjamaa, Francesco Corona, Yoan Miche, Paul Merlin, Bertrand Maillet, Eric Séverin, Amaury Lendasse:
Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database. WSOM 2009: 290-297 - [r1]Tuomas Kärnä, Amaury Lendasse:
Functional Dimension Reduction for Chemometrics. Encyclopedia of Artificial Intelligence 2009: 661-666 - 2008
- [j10]Alberto Guillén, Dusan Sovilj, Amaury Lendasse, Fernando Mateo, Ignacio Rojas:
Minimising the delta test for variable selection in regression problems. Int. J. High Perform. Syst. Archit. 1(4): 269-281 (2008) - [j9]Elia Liitiäinen, Francesco Corona, Amaury Lendasse:
On Nonparametric Residual Variance Estimation. Neural Process. Lett. 28(3): 155-167 (2008) - [c44]Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen:
Using the Delta Test for Variable Selection. ESANN 2008: 25-30 - [c43]Yoan Miche, Patrick Bas, Christian Jutten, Olli Simula, Amaury Lendasse:
A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM. ESANN 2008: 247-252 - [c42]Amaury Lendasse, Francesco Corona:
Linear Projection based on Noise Variance Estimation - Application to Spectral Data. ESANN 2008: 457-462 - [c41]Federico Montesino-Pouzols, Amaury Lendasse, Angel Barriga:
Fuzzy inference based autoregressors for time series prediction using nonparametric residual variance estimation. FUZZ-IEEE 2008: 613-618 - [c40]Qi Yu, Antti Sorjamaa, Yoan Miche, Amaury Lendasse, Eric Séverin, Alberto Guillén, Fernando Mateo:
Optimal Pruned K-Nearest Neighbors: OP-KNN - Application to Financial Modeling. HIS 2008: 764-769 - [c39]Yoan Miche, Antti Sorjamaa, Amaury Lendasse:
OP-ELM: Theory, Experiments and a Toolbox. ICANN (1) 2008: 145-154 - [c38]Antti Sorjamaa, Yoan Miche, Robert Weiss, Amaury Lendasse:
Long-term prediction of time series using NNE-based projection and OP-ELM. IJCNN 2008: 2674-2680 - 2007
- [j8]Amaury Lendasse, Erkki Oja, Olli Simula, Michel Verleysen:
Time series prediction competition: The CATS benchmark. Neurocomputing 70(13-15): 2325-2329 (2007) - [j7]Antti Sorjamaa, Jin Hao, Nima Reyhani, Yongnan Ji, Amaury Lendasse:
Methodology for long-term prediction of time series. Neurocomputing 70(16-18): 2861-2869 (2007) - [c37]Elia Liitiäinen, Francesco Corona, Amaury Lendasse:
Nearest Neighbor Distributions and Noise Variance Estimation. ESANN 2007: 67-72 - [c36]Antti Sorjamaa, Paul Merlin, Bertrand Maillet, Amaury Lendasse:
SOM+EOF for finding missing values. ESANN 2007: 115-120 - [c35]Joos Vandewalle, Johan A. K. Suykens, Bart De Moor, Amaury Lendasse:
State-of-the-Art and Evolution in Public Data Sets and Competitions for System Identification, Time Series Prediction and Pattern Recognition. ICASSP (4) 2007: 1269-1272 - [c34]Amaury Lendasse, Elia Liitiäinen:
Variable Scaling for Time Series Prediction: Application to the ESTSP'07 and the NN3 Forecasting Competitions. IJCNN 2007: 2812-2816 - [c33]Antti Sorjamaa, Amaury Lendasse:
Time Series Prediction as a Problem of Missing Values: Application to ESTSP2007 and NN3 Competition Benchmarks. IJCNN 2007: 2948-2953 - [c32]Nima Reyhani, Amaury Lendasse:
An empirical dependence mesaures based on residual variance estimation. ISSPA 2007: 1-4 - [c31]Elia Liitiäinen, Amaury Lendasse, Francesco Corona:
Non-parametric Residual Variance Estimation in Supervised Learning. IWANN 2007: 63-71 - [c30]Tuomas Kärnä, Amaury Lendasse:
Gaussian Fitting Based FDA for Chemometrics. IWANN 2007: 186-193 - [c29]Yoan Miche, Patrick Bas, Amaury Lendasse, Christian Jutten, Olli Simula:
Advantages of Using Feature Selection Techniques on Steganalysis Schemes. IWANN 2007: 606-613 - [i2]Fabrice Rossi, Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen:
Mutual information for the selection of relevant variables in spectrometric nonlinear modelling. CoRR abs/0709.3427 (2007) - [i1]Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen:
Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps. CoRR abs/cs/0701052 (2007) - 2006
- [c28]Elia Liitiäinen, Nima Reyhani, Amaury Lendasse:
EM-algorithm for training of state-space models with application to time series prediction. ESANN 2006: 137-142 - [c27]Antti Sorjamaa, Amaury Lendasse:
Time series prediction using DirRec strategy. ESANN 2006: 143-148 - [c26]Amaury Lendasse, Francesco Corona, Jin Hao, Nima Reyhani, Michel Verleysen:
Determination of the Mahalanobis matrix using nonparametric noise estimations. ESANN 2006: 227-232 - [c25]Tuomas Kärnä, Fabrice Rossi, Amaury Lendasse:
LS-SVM functional network for time series prediction. ESANN 2006: 473-478 - [c24]Jarkko Tikka, Amaury Lendasse, Jaakko Hollmén:
Analysis of Fast Input Selection: Application in Time Series Prediction. ICANN (2) 2006: 161-170 - [c23]Elia Liitiäinen, Amaury Lendasse:
Long-Term Prediction of Time Series Using State-Space Models. ICANN (2) 2006: 181-190 - [c22]Yoan Miche, Benoit Roue, Amaury Lendasse, Patrick Bas:
A Feature Selection Methodology for Steganalysis. MRCS 2006: 49-56 - 2005
- [j6]Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen:
Vector quantization: a weighted version for time-series forecasting. Future Gener. Comput. Syst. 21(7): 1056-1067 (2005) - [j5]Amaury Lendasse, Geoffroy Simon, Vincent Wertz, Michel Verleysen:
Fast bootstrap methodology for regression model selection. Neurocomputing 64: 161-181 (2005) - [j4]Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen:
Time series forecasting: Obtaining long term trends with self-organizing maps. Pattern Recognit. Lett. 26(12): 1795-1808 (2005) - [c21]Nima Reyhani, Jin Hao, Yongnan Ji, Amaury Lendasse:
Mutual information and gamma test for input selection. ESANN 2005: 503-508 - [c20]Antti Sorjamaa, Amaury Lendasse, Michel Verleysen:
Pruned lazy learning models for time series prediction. ESANN 2005: 509-514 - [c19]Antti Sorjamaa, Jin Hao, Amaury Lendasse:
Mutual Information and k-Nearest Neighbors Approximator for Time Series Prediction. ICANN (2) 2005: 553-558 - [c18]Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel Verleysen:
LS-SVM Hyperparameter Selection with a Nonparametric Noise Estimator. ICANN (2) 2005: 625-630 - [c17]Antti Sorjamaa, Nima Reyhani, Amaury Lendasse:
Input and Structure Selection for k-NN Approximator. IWANN 2005: 985-992 - [c16]Jarkko Tikka, Jaakko Hollmén, Amaury Lendasse:
Input Selection for Long-Term Prediction of Time Series. IWANN 2005: 1002-1009 - [c15]Yongnan Ji, Jin Hao, Nima Reyhani, Amaury Lendasse:
Direct and Recursive Prediction of Time Series Using Mutual Information Selection. IWANN 2005: 1010-1017 - 2004
- [j3]John Aldo Lee, Amaury Lendasse, Michel Verleysen:
Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis. Neurocomputing 57: 49-76 (2004) - [j2]Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen:
Double quantization of the regressor space for long-term time series prediction: method and proof of stability. Neural Networks 17(8-9): 1169-1181 (2004) - [c14]Amaury Lendasse, Geoffroy Simon, Vincent Wertz, Michel Verleysen:
Fast bootstrap for least-square support vector machines. ESANN 2004: 525-530 - 2003
- [c13]Geoffroy Simon, Amaury Lendasse, Vincent Wertz, Michel Verleysen:
Fast approximation of the bootstrap for model selection. ESANN 2003: 475-480 - [c12]Amaury Lendasse, Vincent Wertz, Michel Verleysen:
Model Selection with Cross-Validations and Bootstraps - Application to Time Series Prediction with RBFN Models. ICANN 2003: 573-580 - [c11]Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen:
Nonlinear Time Series Prediction by Weighted Vector Quantization. International Conference on Computational Science 2003: 417-426 - [c10]Geoffroy Simon, Amaury Lendasse, Michel Verleysen:
Bootstrap for Model Selection: Linear Approximation of the Optimism. IWANN (1) 2003: 182-189 - 2002
- [j1]Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen:
Forecasting electricity consumption using nonlinear projection and self-organizing maps. Neurocomputing 48(1-4): 299-311 (2002) - [c9]Amaury Lendasse, Marie Cottrell, Vincent Wertz, Michel Verleysen:
Prediction of electric load using Kohonen maps - Application to the Polish electricity consumption. ACC 2002: 3684-3689 - [c8]John Aldo Lee, Amaury Lendasse, Michel Verleysen:
Curvilinear Distance Analysis versus Isomap. ESANN 2002: 185-192 - [c7]Nabil Benoudjit, Cédric Archambeau, Amaury Lendasse, John Aldo Lee, Michel Verleysen:
Width optimization of the Gaussian kernels in Radial Basis Function Networks. ESANN 2002: 425-432 - 2001
- [c6]Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vincent Wertz, Michel Verleysen:
Input data reduction for the prediction of financial time series. ESANN 2001: 237-244 - 2000
- [c5]John Aldo Lee, Amaury Lendasse, Nicolas Donckers, Michel Verleysen:
A robust non-linear projection method. ESANN 2000: 13-20 - [c4]Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen:
Time series forecasting using CCA and Kohonen maps - application to electricity consumption. ESANN 2000: 329-334
1990 – 1999
- 1999
- [c3]Nicolas Donckers, Amaury Lendasse, Vincent Wertz, Michel Verleysen:
Extraction of intrinsic dimension using CCA - Application to blind sources separation. ESANN 1999: 339-344 - [c2]Michel Verleysen, Eric de Bodt, Amaury Lendasse:
Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection. IWANN (2) 1999: 596-605 - 1998
- [c1]Amaury Lendasse, Michel Verleysen, Eric de Bodt, Marie Cottrell, Philippe Grégoire:
Forecasting time-series by Kohonen classification. ESANN 1998: 221-226
Coauthor Index
Yoan Miché
aka: Yoan Miche
aka: Yoan Miche
[e1] [j73] [j72] [j71] [c95] [i13] [i11] [i9] [j68] [j66] [j62] [c93] [j61] [j60] [c91] [c90] [c89] [c86] [j59] [j56] [j55] [j54] [j53] [c85] [c84] [c83] [c81] [j51] [j50] [j49] [j47] [j46] [j45] [j44] [c80] [c79] [c78] [c77] [j43] [j41] [j39] [j37] [j36] [j35] [j33] [c76] [c75] [j31] [j30] [j29] [c72] [c71] [c69] [c68] [c65] [j25] [j24] [c64] [j22] [j14] [c60] [c59] [c58] [c57] [c55] [j13] [c51] [c49] [c46] [c45] [c43] [c40] [c39] [c38] [c29] [c22]
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