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2020 – today
- 2022
[j64]Jary Pomponi
, Simone Scardapane, Aurelio Uncini:
A Probabilistic Re-Intepretation of Confidence Scores in Multi-Exit Models. Entropy 24(1): 1 (2022)- [j63]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) - [j62]Christian Brignone, Gioia Mancini, Eleonora Grassucci, Aurelio Uncini, Danilo Comminiello:
Efficient Sound Event Localization and Detection in the Quaternion Domain. IEEE Trans. Circuits Syst. II Express Briefs 69(5): 2453-2457 (2022) - [c113]Eric Guizzo, Christian Marinoni, Marco Pennese, Xinlei Ren, Xiguang Zheng, Chen Zhang, Bruno Masiero, Aurelio Uncini, Danilo Comminiello:
L3DAS22 Challenge: Learning 3D Audio Sources in a Real Office Environment. ICASSP 2022: 9186-9190 - [i31]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Pixle: a fast and effective black-box attack based on rearranging pixels. CoRR abs/2202.02236 (2022) - [i30]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Continual Learning with Invertible Generative Models. CoRR abs/2202.05694 (2022) - [i29]Eric Guizzo, Christian Marinoni, Marco Pennese, Xinlei Ren, Xiguang Zheng, Chen Zhang, Bruno Masiero, Aurelio Uncini, Danilo Comminiello:
L3DAS22 Challenge: Learning 3D Audio Sources in a Real Office Environment. CoRR abs/2202.10372 (2022) - [i28]Eleonora Grassucci, Gioia Mancini, Christian Brignone, Aurelio Uncini, Danilo Comminiello:
Dual Quaternion Ambisonics Array for Six-Degree-of-Freedom Acoustic Representation. CoRR abs/2204.01851 (2022) - [i27]Eleonora Grassucci, Luigi Sigillo, Aurelio Uncini, Danilo Comminiello:
Hypercomplex Image-to-Image Translation. CoRR abs/2205.02087 (2022) - [i26]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Centroids Matching: an efficient Continual Learning approach operating in the embedding space. CoRR abs/2208.02048 (2022) - 2021
- [j61]Eleonora Grassucci, Danilo Comminiello, Aurelio Uncini:
An Information-Theoretic Perspective on Proper Quaternion Variational Autoencoders. Entropy 23(7): 856 (2021) - [j60]Michele Scarpiniti, Francesco Colasante, Simone Di Tanna, Marco Ciancia, Yong-Cheol Lee, Aurelio Uncini:
Deep Belief Network based audio classification for construction sites monitoring. Expert Syst. Appl. 177: 114839 (2021) - [j59]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Bayesian Neural Networks with Maximum Mean Discrepancy regularization. Neurocomputing 453: 428-437 (2021) - [j58]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Structured Ensembles: An approach to reduce the memory footprint of ensemble methods. Neural Networks 144: 407-418 (2021) - [j57]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Adaptive Propagation Graph Convolutional Network. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4755-4760 (2021) - [c112]Eleonora Grassucci, Danilo Comminiello, Aurelio Uncini:
A Quaternion-Valued Variational Autoencoder. ICASSP 2021: 3310-3314 - [c111]Eric Guizzo, Riccardo F. Gramaccioni, Saeid Jamili, Christian Marinoni, Edoardo Massaro, Claudia Medaglia, Giuseppe Nachira, Leonardo Nucciarelli, Ludovica Paglialunga, Marco Pennese, Sveva Pepe, Enrico Rocchi, Aurelio Uncini, Danilo Comminiello:
L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing. MLSP 2021: 1-6 - [i25]Eric Guizzo, Riccardo F. Gramaccioni, Saeid Jamili, Christian Marinoni, Edoardo Massaro, Claudia Medaglia, Giuseppe Nachira, Leonardo Nucciarelli, Ludovica Paglialunga, Marco Pennese, Sveva Pepe, Enrico Rocchi, Aurelio Uncini, Danilo Comminiello:
L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing. CoRR abs/2104.05499 (2021) - [i24]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) - [i23]Indro Spinelli, Simone Scardapane, Amir Hussain, Aurelio Uncini:
Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning. CoRR abs/2104.14210 (2021) - [i22]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Structured Ensembles: an Approach to Reduce the Memory Footprint of Ensemble Methods. CoRR abs/2105.02551 (2021) - [i21]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
A Meta-Learning Approach for Training Explainable Graph Neural Networks. CoRR abs/2109.09426 (2021) - 2020
- [j56]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) - [j55]Simone Scardapane, Michele Scarpiniti, Enzo Baccarelli, Aurelio Uncini:
Why Should We Add Early Exits to Neural Networks? Cogn. Comput. 12(5): 954-966 (2020) - [j54]Jary Pomponi, Simone Scardapane, Vincenzo Lomonaco, Aurelio Uncini:
Efficient continual learning in neural networks with embedding regularization. Neurocomputing 397: 139-148 (2020) - [j53]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) - [j52]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Missing data imputation with adversarially-trained graph convolutional networks. Neural Networks 129: 249-260 (2020) - [j51]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) - [c110]Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini, Yong-Cheol Lee:
Deep Recurrent Neural Networks for Audio Classification in Construction Sites. EUSIPCO 2020: 810-814 - [c109]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 - [c108]Simone Scardapane, Danilo Comminiello, Michele Scarpiniti, Enzo Baccarelli, Aurelio Uncini:
Differentiable Branching In Deep Networks for Fast Inference. ICASSP 2020: 4167-4171 - [p14]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 - [p13]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 - [p12]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 - [p11]Francesca Ortolani, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
On 4-Dimensional Hypercomplex Algebras in Adaptive Signal Processing. Neural Advances in Processing Nonlinear Dynamic Signals 2020: 131-140 - [p10]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 - [i20]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Adaptive Propagation Graph Convolutional Network. CoRR abs/2002.10306 (2020) - [i19]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Bayesian Neural Networks With Maximum Mean Discrepancy Regularization. CoRR abs/2003.00952 (2020) - [i18]Simone Scardapane, Michele Scarpiniti, Enzo Baccarelli, Aurelio Uncini:
Why should we add early exits to neural networks? CoRR abs/2004.12814 (2020) - [i17]Jary Pomponi, Simone Scardapane, Aurelio Uncini:
Pseudo-Rehearsal for Continual Learning with Normalizing Flows. CoRR abs/2007.02443 (2020) - [i16]Eleonora Grassucci, Danilo Comminiello, Aurelio Uncini:
Quaternion-Valued Variational Autoencoder. CoRR abs/2010.11647 (2020)
2010 – 2019
- 2019
- [j50]Danilo Comminiello, Michele Scarpiniti, Luis Antonio Azpicueta-Ruiz, Aurelio Uncini:
Steady-State Performance of an Adaptive Combined MISO Filter Using the Multichannel Affine Projection Algorithm. Algorithms 12(1): 2 (2019) - [j49]Mahdieh Izadpanahkakhk, Seyyed Mohammad Razavi, Mehran Taghipour-Gorjikolaie, Seyyed Hamid Zahiri, Aurelio Uncini:
Novel mobile palmprint databases for biometric authentication. Int. J. Grid Util. Comput. 10(5): 465-474 (2019) - [j48]Mahdieh Izadpanahkakhk, Seyyed Mohammad Razavi, Mehran Taghipour-Gorjikolaie, Seyyed Hamid Zahiri, Aurelio Uncini:
Joint feature fusion and optimization via deep discriminative model for mobile palmprint verification. J. Electronic Imaging 28(4): 043026 (2019) - [j47]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) - [c107]Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini:
Convex Combination of Spline Adaptive Filters. EUSIPCO 2019: 1-5 - [c106]Danilo Comminiello, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini:
Frequency-domain Adaptive Filtering: from Real to Hypercomplex Signal Processing. ICASSP 2019: 7745-7749 - [c105]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Widely Linear Kernels for Complex-valued Kernel Activation Functions. ICASSP 2019: 8528-8532 - [c104]Danilo Comminiello, Marco Lella, Simone Scardapane, Aurelio Uncini:
Quaternion Convolutional Neural Networks for Detection and Localization of 3D Sound Events. ICASSP 2019: 8533-8537 - [c103]Antonio Falvo, Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
A Multimodal Dense U-Net For Accelerating Multiple Sclerosis MRI. MLSP 2019: 1-6 - [i15]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Widely Linear Kernels for Complex-Valued Kernel Activation Functions. CoRR abs/1902.02085 (2019) - [i14]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) - [i13]Indro Spinelli, Simone Scardapane, Aurelio Uncini:
Missing Data Imputation with Adversarially-trained Graph Convolutional Networks. CoRR abs/1905.01907 (2019) - [i12]Indro Spinelli, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
Efficient data augmentation using graph imputation neural networks. CoRR abs/1906.08502 (2019) - [i11]Riccardo Vecchi, Simone Scardapane, Danilo Comminiello, Aurelio Uncini:
Compressing deep quaternion neural networks with targeted regularization. CoRR abs/1907.11546 (2019) - [i10]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) - [i9]Jary Pomponi, Simone Scardapane, Vincenzo Lomonaco, Aurelio Uncini:
Efficient Continual Learning in Neural Networks with Embedding Regularization. CoRR abs/1909.03742 (2019) - 2018
- [j46]Simone Scardapane, Dianhui Wang, Aurelio Uncini:
Bayesian Random Vector Functional-Link Networks for Robust Data Modeling. IEEE Trans. Cybern. 48(7): 2049-2059 (2018) - [j45]Stefano Squartini, Björn W. Schuller, Aurelio Uncini, C.-K. Ting:
Guest Editorial Special Issue on Computational Intelligence for End-to-End Audio Processing. IEEE Trans. Emerg. Top. Comput. Intell. 2(2): 89-91 (2018) - [j44]Michele Scarpiniti, Enzo Baccarelli, Paola Gabriela Vinueza Naranjo, Aurelio Uncini:
Energy performance of heuristics and meta-heuristics for real-time joint resource scaling and consolidation in virtualized networked data centers. J. Supercomput. 74(5): 2161-2198 (2018) - [c102]Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Luis Antonio Azpicueta-Ruiz, Aurelio Uncini:
Combined Sparse Regularization for Nonlinear Adaptive Filters. EUSIPCO 2018: 336-340 - [c101]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. EUSIPCO 2018: 872-876 - [c100]Danilo Comminiello, Michele Scarpiniti, Simone Scardapane, Aurelio Uncini:
Sparse functional link adaptive filter using an ℓ1-norm regularization. ISCAS 2018: 1-5 - [c99]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 - [p9]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 - [p8]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 - [i8]Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain, Aurelio Uncini:
Complex-valued Neural Networks with Non-parametric Activation Functions. CoRR abs/1802.08026 (2018) - [i7]Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Aurelio Uncini:
Improving Graph Convolutional Networks with Non-Parametric Activation Functions. CoRR abs/1802.09405 (2018) - [i6]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) - [i5]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
- [j43]Simone Scardapane, Aurelio Uncini:
Semi-supervised Echo State Networks for Audio Classification. Cogn. Comput. 9(1): 125-135 (2017) - [j42]Simone Scardapane, Danilo Comminiello, Amir Hussain, Aurelio Uncini:
Group sparse regularization for deep neural networks. Neurocomputing 241: 81-89 (2017) - [j41]Danilo Comminiello, Michele Scarpiniti, Luis Antonio Azpicueta-Ruiz, Jerónimo Arenas-García, Aurelio Uncini:
Combined nonlinear filtering architectures involving sparse functional link adaptive filters. Signal Process. 135: 168-178 (2017) - [j40]Francesca Ortolani, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
Frequency domain quaternion adaptive filters: Algorithms and convergence performance. Signal Process. 136: 69-80 (2017) - [j39]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) - [c98]Danilo Comminiello, Michele Scarpiniti, Luis Antonio Azpicueta-Ruiz, Jerónimo Arenas-García, Aurelio Uncini:
Full proportionate functional link adaptive filters for nonlinear acoustic echo cancellation. EUSIPCO 2017: 1145-1149 - [c97]Indro Spinelli, Simone Scardapane, Michele Scarpiniti, Aurelio Uncini:
Efficient Data Augmentation Using Graph Imputation Neural Networks. IIH-MSP (1) 2017: 57-66 - [c96]Eleonora Grassucci, Simone Scardapane, Danilo Comminiello, Aurelio Uncini:
Flexible Generative Adversarial Networks with Non-parametric Activation Functions. IIH-MSP (1) 2017: 67-77 - [c95]Alessandro Maccagno, Andrea Mastropietro, Umberto Mazziotta, Michele Scarpiniti, Yong-Cheol Lee, Aurelio Uncini:
A CNN Approach for Audio Classification in Construction Sites. IIH-MSP (1) 2017: 371-381 - [c94]Michele Scarpiniti, Danilo Comminiello, Federico Muciaccia, Aurelio Uncini:
Quaternion Widely Linear Forecasting of Air Quality. IIH-MSP (1) 2017: 393-403 - [c93]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 - [c92]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 - [i4]Simone Scardapane, Steven Van Vaerenbergh, Aurelio Uncini:
Kafnets: kernel-based non-parametric activation functions for neural networks. CoRR abs/1707.04035 (2017) - 2016
- [j38]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) - [j37]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) - [j36]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) - [j35]Simone Scardapane, Roberto Fierimonte, Paolo Di Lorenzo, Massimo Panella, Aurelio Uncini:
Distributed semi-supervised support vector machines. Neural Networks 80: 43-52 (2016) - [j34]Michele Scarpiniti, Danilo Comminiello, Gaetano Scarano, Raffaele Parisi, Aurelio Uncini:
Steady-State Performance of Spline Adaptive Filters. IEEE Trans. Signal Process. 64(4): 816-828 (2016) - [c91]Simone Scardapane, Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini:
Diffusion spline adaptive filtering. EUSIPCO 2016: 1498-1502 - [c90]Simone Scardapane, Rosa Altilio, Massimo Panella, Aurelio Uncini:
Distributed spectral clustering based on Euclidean distance matrix completion. IJCNN 2016: 3093-3100 - [c89]Vinal Patel, Danilo Comminiello, Michele Scarpiniti, Nithin V. George, Aurelio Uncini:
Design of hybrid nonlinear spline adaptive filters for active noise control. IJCNN 2016: 3420-3425 - [c88]Danilo Comminiello, Michele Scarpiniti, Luis Antonio Azpicueta-Ruiz, Jerónimo Arenas-García, Aurelio Uncini:
A block-based combined scheme exploiting sparsity in nonlinear acoustic echo cancellation. MLSP 2016: 1-6 - [c87]Francesca Ortolani, Danilo Comminiello, Aurelio Uncini:
The widely linear block quaternion least mean square algorithm for fast computation in 3D audio systems. MLSP 2016: 1-6 - [p7]Francesca Ortolani, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
Frequency-Domain Adaptive Filtering in Hypercomplex Systems. Advances in Neural Networks 2016: 47-56 - [p6]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 - [p5]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 - [p4]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 - [e1]Francesco A. N. Palmieri, Aurelio Uncini, Kostas I. Diamantaras, Jan Larsen:
26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016, Vietri sul Mare, Salerno, Italy, September 13-16, 2016. IEEE 2016, ISBN 978-1-5090-0746-2 [contents] - [i3]Simone Scardapane, Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini:
Learning activation functions from data using cubic spline interpolation. CoRR abs/1605.05509 (2016) - [i2]Michele Scarpiniti, Simone Scardapane, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini:
Effective Blind Source Separation Based on the Adam Algorithm. CoRR abs/1605.07833 (2016) - [i1]Simone Scardapane, Danilo Comminiello, Amir Hussain, Aurelio Uncini:
Group Sparse Regularization for Deep Neural Networks. CoRR abs/1607.00485 (2016) - 2015
- [j33]Simone Scardapane, Dianhui Wang, Massimo Panella, Aurelio Uncini:
Distributed learning for Random Vector Functional-Link networks. Inf. Sci. 301: 271-284 (2015) - [j32]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) - [j31]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) - [j30]Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini:
Nonlinear system identification using IIR Spline Adaptive Filters. Signal Process. 108: 30-35 (2015) - [j29]Michele Scarpiniti, Danilo Comminiello, Raffaele Parisi, Aurelio Uncini:
Novel Cascade Spline Architectures for the Identification of Nonlinear Systems. IEEE Trans. Circuits Syst. I Regul. Pap. 62-I(7): 1825-1835 (2015) - [j28]Danilo Comminiello, Stefania Cecchi, Michele Scarpiniti, Michele Gasparini, Laura Romoli, Francesco Piazza, Aurelio Uncini:
Intelligent Acoustic Interfaces With Multisensor Acquisition for Immersive Reproduction. IEEE Trans. Multim. 17(8): 1262-1272 (2015) - [j27]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) - [c86]Danilo Comminiello, Michele Scarpiniti, Luis Antonio Azpicueta-Ruiz, Jerónimo Arenas-García, Aurelio Uncini:
A nonlinear architecture involving a combination of proportionate functional link adaptive filters. EUSIPCO 2015: 2869-2873 - [c85]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 - [c84]Laura Romoli, Stefania Cecchi, Francesco Piazza, Danilo Comminiello, Michele Scarpiniti, Aurelio Uncini:
An interactive optimization procedure for stereophonic acoustic echo cancellation systems. IJCNN 2015: 1-7 - [c83]Simone Scardapane, Roberto Fierimonte, Dianhui Wang, Massimo Panella, Aurelio Uncini:
Distributed music classification using Random Vector Functional-Link nets. IJCNN 2015: 1-8 - [c82]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 - [p3]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 - [p2]