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2020 – today
- 2022
[j35]Jary Pomponi
, Simone Scardapane, Aurelio Uncini:
A Probabilistic Re-Intepretation of Confidence Scores in Multi-Exit Models. Entropy 24(1): 1 (2022)- [j34]Lorenzo Lastilla, Serena Ammirati, Donatella Firmani, Nikos Komodakis, Paolo Merialdo, Simone Scardapane:
Self-supervised learning for medieval handwriting identification: A case study from the Vatican Apostolic Library. Inf. Process. Manag. 59(3): 102875 (2022) - [j33]Indro Spinelli, Simone Scardapane, Amir Hussain, Aurelio Uncini:
FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning. IEEE Trans. Artif. Intell. 3(3): 344-354 (2022) - [c38]Onur Çopur, Mert Nakip, Simone Scardapane, Jürgen Slowack:
Engagement Detection with Multi-Task Training in E-Learning Environments. ICIAP (3) 2022: 411-422 - [i42]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Pixle: a fast and effective black-box attack based on rearranging pixels. CoRR abs/2202.02236 (2022) - [i41]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Continual Learning with Invertible Generative Models. CoRR abs/2202.05694 (2022) - [i40]Arya Farkhondeh, Cristina Palmero, Simone Scardapane, Sergio Escalera:
Towards Self-Supervised Gaze Estimation. CoRR abs/2203.10974 (2022) - [i39]Eric Guizzo, Tillman Weyde, Simone Scardapane, Danilo Comminiello:
Learning Speech Emotion Representations in the Quaternion Domain. CoRR abs/2204.02385 (2022) - [i38]Onur Çopur, Mert Nakip, Simone Scardapane, Jürgen Slowack:
Engagement Detection with Multi-Task Training in E-Learning Environments. CoRR abs/2204.04020 (2022) - [i37]Valerio Marsocci, Simone Scardapane:
Continual Barlow Twins: continual self-supervised learning for remote sensing semantic segmentation. CoRR abs/2205.11319 (2022) - [i36]Valerio Marsocci, Virginia Coletta, Roberta Ravanelli, Simone Scardapane, Mattia Crespi:
Inferring 3D change detection from bitemporal optical images. CoRR abs/2205.15903 (2022) - 2021
- [j32]L. Lilli, Enrico Giarnieri, Simone Scardapane:
A Calibrated Multiexit Neural Network for Detecting Urothelial Cancer Cells. Comput. Math. Methods Medicine 2021: 5569458:1-5569458:11 (2021) - [j31]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Bayesian Neural Networks with Maximum Mean Discrepancy regularization. Neurocomputing 453: 428-437 (2021) - [j30]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Structured Ensembles: An approach to reduce the memory footprint of ensemble methods. Neural Networks 144: 407-418 (2021) - [j29]Valerio Marsocci, Simone Scardapane, Nikos Komodakis:
MARE: Self-Supervised Multi-Attention REsu-Net for Semantic Segmentation in Remote Sensing. Remote. Sens. 13(16): 3275 (2021) - [j28]Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen:
Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series. IEEE Trans. Neural Networks Learn. Syst. 32(5): 2169-2179 (2021) - [j27]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Adaptive Propagation Graph Convolutional Network. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4755-4760 (2021) - [j26]Simone Scardapane, Indro Spinelli, Paolo Di Lorenzo:
Distributed Training of Graph Convolutional Networks. IEEE Trans. Signal Inf. Process. over Networks 7: 87-100 (2021) - [c37]Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni:
Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops 2021: 3600-3610 - [i35]Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. van de Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni:
Avalanche: an End-to-End Library for Continual Learning. CoRR abs/2104.00405 (2021) - [i34]Danilo Comminiello, Alireza Nezamdoust, Simone Scardapane, Michele Scarpiniti, Amir Hussain, Aurelio Uncini:
A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling. CoRR abs/2104.09641 (2021) - [i33]Indro Spinelli, Simone Scardapane, Amir Hussain, Aurelio Uncini:
Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning. CoRR abs/2104.14210 (2021) - [i32]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Structured Ensembles: an Approach to Reduce the Memory Footprint of Ensemble Methods. CoRR abs/2105.02551 (2021) - [i31]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
A Meta-Learning Approach for Training Explainable Graph Neural Networks. CoRR abs/2109.09426 (2021) - 2020
- [j25]Riccardo Vecchi, Simone Scardapane, Danilo Comminiello, Aurelio Uncini:
Compressing deep-quaternion neural networks with targeted regularisation. CAAI Trans. Intell. Technol. 5(3): 172-176 (2020) - [j24]Simone Scardapane, Michele Scarpiniti, Enzo Baccarelli, Aurelio Uncini:
Why Should We Add Early Exits to Neural Networks? Cogn. Comput. 12(5): 954-966 (2020) - [j23]Simone Totaro, Amir Hussain, Simone Scardapane:
A non-parametric softmax for improving neural attention in time-series forecasting. Neurocomputing 381: 177-185 (2020) - [j22]Jary Pomponi, Simone Scardapane, Vincenzo Lomonaco, Aurelio Uncini:
Efficient continual learning in neural networks with embedding regularization. Neurocomputing 397: 139-148 (2020) - [j21]Enzo Baccarelli, Simone Scardapane, Michele Scarpiniti, Alireza Momenzadeh, Aurelio Uncini:
Optimized training and scalable implementation of Conditional Deep Neural Networks with early exits for Fog-supported IoT applications. Inf. Sci. 521: 107-143 (2020) - [j20]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Missing data imputation with adversarially-trained graph convolutional networks. Neural Networks 129: 249-260 (2020) - [j19]Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini:
Complex-Valued Neural Networks With Nonparametric Activation Functions. IEEE Trans. Emerg. Top. Comput. Intell. 4(2): 140-150 (2020) - [c36]Claudio Gallicchio, Mantas Lukosevicius, Simone Scardapane:
Frontiers in Reservoir Computing. ESANN 2020: 559-566 - [c35]Antonio Falvo, Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
A Wide Multimodal Dense U-Net for Fast Magnetic Resonance Imaging. EUSIPCO 2020: 1274-1278 - [c34]Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Enzo Baccarelli, Aurelio Uncini:
Differentiable Branching In Deep Networks for Fast Inference. ICASSP 2020: 4167-4171 - [c33]Michela Ricciardi Celsi, Simone Scardapane, Danilo Comminiello:
Quaternion Neural Networks for 3D Sound Source Localization in Reverberant Environments. MLSP 2020: 1-6 - [p11]Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Aurelio Uncini:
Music Genre Classification Using Stacked Auto-Encoders. Neural Approaches to Dynamics of Signal Exchanges 2020: 11-19 - [p10]Simone Scardapane, Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini:
Learning Activation Functions from Data Using Cubic Spline Interpolation. Neural Advances in Processing Nonlinear Dynamic Signals 2020: 73-83 - [p9]Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Raffaele Parisi, Aurelio Uncini:
A Low-Complexity Linear-in-the-Parameters Nonlinear Filter for Distorted Speech Signals. Neural Advances in Processing Nonlinear Dynamic Signals 2020: 107-117 - [p8]Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini:
Separation of Drum and Bass from Monaural Tracks. Neural Advances in Processing Nonlinear Dynamic Signals 2020: 141-151 - [i30]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Adaptive Propagation Graph Convolutional Network. CoRR abs/2002.10306 (2020) - [i29]Claudio Gallicchio, Simone Scardapane:
Deep Randomized Neural Networks. CoRR abs/2002.12287 (2020) - [i28]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Bayesian Neural Networks With Maximum Mean Discrepancy Regularization. CoRR abs/2003.00952 (2020) - [i27]Simone Scardapane, Michele Scarpiniti, Enzo Baccarelli, Aurelio Uncini:
Why should we add early exits to neural networks? CoRR abs/2004.12814 (2020) - [i26]Paolo Di Lorenzo, Simone Scardapane:
Distributed Stochastic Nonconvex Optimization and Learning based on Successive Convex Approximation. CoRR abs/2004.14882 (2020) - [i25]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Pseudo-Rehearsal for Continual Learning with Normalizing Flows. CoRR abs/2007.02443 (2020) - [i24]Simone Scardapane, Indro Spinelli, Paolo Di Lorenzo:
Distributed Graph Convolutional Networks. CoRR abs/2007.06281 (2020)
2010 – 2019
- 2019
- [j18]Simone Scardapane, Steven Van Vaerenbergh, Simone Totaro, Aurelio Uncini:
Kafnets: Kernel-based non-parametric activation functions for neural networks. Neural Networks 110: 19-32 (2019) - [c32]Paolo Di Lorenzo, Simone Scardapane:
Distributed Stochastic Nonconvex Optimization and Learning based on Successive Convex Approximation. ACSSC 2019: 2224-2228 - [c31]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Widely Linear Kernels for Complex-valued Kernel Activation Functions. ICASSP 2019: 8528-8532 - [c30]Danilo Comminiello, Marco Lella, Simone Scardapane, Aurelio Uncini:
Quaternion Convolutional Neural Networks for Detection and Localization of 3D Sound Events. ICASSP 2019: 8533-8537 - [c29]Claudio Gallicchio, Simone Scardapane:
Deep Randomized Neural Networks. INNSBDDL (Tutorials) 2019: 43-68 - [c28]Simone Scardapane, Elena Nieddu, Donatella Firmani, Paolo Merialdo:
Multikernel Activation Functions: Formulation and a Case Study. INNSBDDL 2019: 320-329 - [c27]Antonio Falvo, Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
A Multimodal Dense U-Net For Accelerating Multiple Sclerosis MRI. MLSP 2019: 1-6 - [i23]Simone Scardapane, Elena Nieddu, Donatella Firmani, Paolo Merialdo:
Multikernel activation functions: formulation and a case study. CoRR abs/1901.10232 (2019) - [i22]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Widely Linear Kernels for Complex-Valued Kernel Activation Functions. CoRR abs/1902.02085 (2019) - [i21]Michele Cirillo, Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini:
On the Stability and Generalization of Learning with Kernel Activation Functions. CoRR abs/1903.11990 (2019) - [i20]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Missing Data Imputation with Adversarially-trained Graph Convolutional Networks. CoRR abs/1905.01907 (2019) - [i19]Indro Spinelli, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
Efficient data augmentation using graph imputation neural networks. CoRR abs/1906.08502 (2019) - [i18]Riccardo Vecchi, Simone Scardapane, Danilo Comminiello, Aurelio Uncini:
Compressing deep quaternion neural networks with targeted regularization. CoRR abs/1907.11546 (2019) - [i17]Antonio Falvo, Danilo Comminiello, Simone Scardapane, Giorgio Finesi, Michele Scarpiniti, Aurelio Uncini:
A Multimodal Deep Network for the Reconstruction of T2W MR Images. CoRR abs/1908.03009 (2019) - [i16]Jary Pomponi, Simone Scardapane, Vincenzo Lomonaco, Aurelio Uncini:
Efficient Continual Learning in Neural Networks with Embedding Regularization. CoRR abs/1909.03742 (2019) - 2018
- [j17]Simone Scardapane, Dianhui Wang, Aurelio Uncini:
Bayesian Random Vector Functional-Link Networks for Robust Data Modeling. IEEE Trans. Cybern. 48(7): 2049-2059 (2018) - [j16]Simone Scardapane, Paolo Di Lorenzo:
Stochastic Training of Neural Networks via Successive Convex Approximations. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4947-4956 (2018) - [c26]Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen:
Bidirectional deep-readout echo state networks. ESANN 2018 - [c25]Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Luis Antonio Azpicueta-Ruiz, Aurelio Uncini:
Combined Sparse Regularization for Nonlinear Adaptive Filters. EUSIPCO 2018: 336-340 - [c24]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. EUSIPCO 2018: 872-876 - [c23]Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Aurelio Uncini:
Sparse functional link adaptive filter using an ℓ1-norm regularization. ISCAS 2018: 1-5 - [c22]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini:
Recurrent Neural Networks with flexible Gates using Kernel activation Functions. MLSP 2018: 1-6 - [p7]Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini:
Effective Blind Source Separation Based on the Adam Algorithm. Multidisciplinary Approaches to Neural Computing 2018: 57-66 - [p6]Simone Scardapane, Rosa Altilio, Valentina Ciccarelli, Aurelio Uncini, Massimo Panella:
Privacy-Preserving Data Mining for Distributed Medical Scenarios. Multidisciplinary Approaches to Neural Computing 2018: 119-128 - [i15]Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini:
Complex-valued Neural Networks with Non-parametric Activation Functions. CoRR abs/1802.08026 (2018) - [i14]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. CoRR abs/1802.09405 (2018) - [i13]Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen:
Reservoir computing approaches for representation and classification of multivariate time series. CoRR abs/1803.07870 (2018) - [i12]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini:
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions. CoRR abs/1807.04065 (2018) - [i11]Danilo Comminiello, Marco Lella, Simone Scardapane, Aurelio Uncini:
Quaternion Convolutional Neural Networks for Detection and Localization of 3D Sound Events. CoRR abs/1812.06811 (2018) - 2017
- [j15]Simone Scardapane, Aurelio Uncini:
Semi-supervised Echo State Networks for Audio Classification. Cogn. Comput. 9(1): 125-135 (2017) - [j14]Simone Scardapane, John B. Butcher, Filippo Maria Bianchi, Zeeshan Khawar Malik:
Advances in Biologically Inspired Reservoir Computing. Cogn. Comput. 9(3): 295-296 (2017) - [j13]Simone Scardapane, Danilo Comminiello, Amir Hussain, Aurelio Uncini:
Group sparse regularization for deep neural networks. Neurocomputing 241: 81-89 (2017) - [j12]Simone Scardapane, Paolo Di Lorenzo:
A framework for parallel and distributed training of neural networks. Neural Networks 91: 42-54 (2017) - [j11]Roberto Fierimonte, Simone Scardapane, Aurelio Uncini, Massimo Panella:
Fully Decentralized Semi-supervised Learning via Privacy-preserving Matrix Completion. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2699-2711 (2017) - [j10]Simone Scardapane, Dianhui Wang:
Randomness in neural networks: an overview. WIREs Data Mining Knowl. Discov. 7(2) (2017) - [c21]Donatella Firmani, Paolo Merialdo, Elena Nieddu, Simone Scardapane:
In Codice Ratio: OCR of Handwritten Latin Documents using Deep Convolutional Networks. AI*CH@AI*IA 2017: 9-16 - [c20]Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaría:
Recursive multikernel filters exploiting nonlinear temporal structure. EUSIPCO 2017: 2674-2678 - [c19]Indro Spinelli, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
Efficient Data Augmentation Using Graph Imputation Neural Networks. IIH-MSP (1) 2017: 57-66 - [c18]Eleonora Grassucci, Simone Scardapane, Danilo Comminiello, Aurelio Uncini:
Flexible Generative Adversarial Networks with Non-parametric Activation Functions. IIH-MSP (1) 2017: 67-77 - [c17]Antonio Falvo, Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
A Multimodal Deep Network for the Reconstruction of T2W MR Images. IIH-MSP (1) 2017: 423-431 - [c16]Simone Scardapane, Lucas Stoffl, Florian Röhrbein, Aurelio Uncini:
On the use of deep recurrent neural networks for detecting audio spoofing attacks. IJCNN 2017: 3483-3490 - [i10]Simone Scardapane, Jie Chen, Cédric Richard:
Adaptation and learning over networks for nonlinear system modeling. CoRR abs/1704.08913 (2017) - [i9]Steven Van Vaerenbergh, Simone Scardapane, Ignacio Santamaría:
Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure. CoRR abs/1706.03533 (2017) - [i8]Simone Scardapane, Paolo Di Lorenzo:
Stochastic Training of Neural Networks via Successive Convex Approximations. CoRR abs/1706.04769 (2017) - [i7]Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini:
Kafnets: kernel-based non-parametric activation functions for neural networks. CoRR abs/1707.04035 (2017) - [i6]Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen:
Bidirectional deep echo state networks. CoRR abs/1711.06509 (2017) - 2016
- [j9]Simone Scardapane, Massimo Panella, Danilo Comminiello, Amir Hussain, Aurelio Uncini:
Distributed Reservoir Computing with Sparse Readouts [Research Frontier]. IEEE Comput. Intell. Mag. 11(4): 59-70 (2016) - [j8]Filippo Maria Bianchi, Simone Scardapane, Antonello Rizzi, Aurelio Uncini, Alireza Sadeghian:
Granular Computing Techniques for Classification and Semantic Characterization of Structured Data. Cogn. Comput. 8(3): 442-461 (2016) - [j7]Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
A semi-supervised random vector functional-link network based on the transductive framework. Inf. Sci. 364-365: 156-166 (2016) - [j6]Simone Scardapane, Dianhui Wang, Massimo Panella:
A decentralized training algorithm for Echo State Networks in distributed big data applications. Neural Networks 78: 65-74 (2016) - [j5]Simone Scardapane, Roberto Fierimonte, Paolo Di Lorenzo, Massimo Panella, Aurelio Uncini:
Distributed semi-supervised support vector machines. Neural Networks 80: 43-52 (2016) - [c15]Simone Scardapane, Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini:
Diffusion spline adaptive filtering. EUSIPCO 2016: 1498-1502 - [c14]Simone Scardapane, Rosa Altilio, Massimo Panella, Aurelio Uncini:
Distributed spectral clustering based on Euclidean distance matrix completion. IJCNN 2016: 3093-3100 - [c13]Paolo Di Lorenzo, Simone Scardapane:
Parallel and distributed training of neural networks via successive convex approximation. MLSP 2016: 1-6 - [p5]Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini:
Benchmarking Functional Link Expansions for Audio Classification Tasks. Advances in Neural Networks 2016: 133-141 - [p4]Roberto Fierimonte, Simone Scardapane, Massimo Panella, Aurelio Uncini:
A Comparison of Consensus Strategies for Distributed Learning of Random Vector Functional-Link Networks. Advances in Neural Networks 2016: 143-152 - [p3]Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Raffaele Parisi, Aurelio Uncini:
A Nonlinear Acoustic Echo Canceller with Improved Tracking Capabilities. Recent Advances in Nonlinear Speech Processing 2016: 235-243 - [i5]Simone Scardapane, Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini:
Learning activation functions from data using cubic spline interpolation. CoRR abs/1605.05509 (2016) - [i4]Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini:
Effective Blind Source Separation Based on the Adam Algorithm. CoRR abs/1605.07833 (2016) - [i3]Simone Scardapane, Danilo Comminiello, Amir Hussain, Aurelio Uncini:
Group Sparse Regularization for Deep Neural Networks. CoRR abs/1607.00485 (2016) - [i2]Simone Scardapane:
Distributed Supervised Learning using Neural Networks. CoRR abs/1607.06364 (2016) - [i1]Simone Scardapane, Paolo Di Lorenzo:
A Framework for Parallel and Distributed Training of Neural Networks. CoRR abs/1610.07448 (2016) - 2015
- [j4]Simone Scardapane, Dianhui Wang, Massimo Panella, Aurelio Uncini:
Distributed learning for Random Vector Functional-Link networks. Inf. Sci. 301: 271-284 (2015) - [j3]Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Raffaele Parisi, Aurelio Uncini:
Improving nonlinear modeling capabilities of functional link adaptive filters. Neural Networks 69: 51-59 (2015) - [j2]Filippo Maria Bianchi, Simone Scardapane, Aurelio Uncini, Antonello Rizzi, Alireza Sadeghian:
Prediction of telephone calls load using Echo State Network with exogenous variables. Neural Networks 71: 204-213 (2015) - [j1]Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
Online Sequential Extreme Learning Machine With Kernels. IEEE Trans. Neural Networks Learn. Syst. 26(9): 2214-2220 (2015) - [c12]Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini:
Functional link expansions for nonlinear modeling of audio and speech signals. IJCNN 2015: 1-8 - [c11]Simone Scardapane, Roberto Fierimonte, Dianhui Wang, Massimo Panella, Aurelio Uncini:
Distributed music classification using Random Vector Functional-Link nets. IJCNN 2015: 1-8 - [c10]Simone Scardapane, Massimo Panella, Danilo Comminiello, Aurelio Uncini:
Learning from Distributed Data Sources Using Random Vector Functional-Link Networks. INNS Conference on Big Data 2015: 468-477 - [p2]Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
Significance-Based Pruning for Reservoir's Neurons in Echo State Networks. Advances in Neural Networks 2015: 31-38 - [p1]Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini:
Online Selection of Functional Links for Nonlinear System Identification. Advances in Neural Networks 2015: 39-47 - 2014
- [c9]