default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDCesare Alippi
Person information
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j86]Luca Butera, Andrea Cini, Alberto Ferrante, Cesare Alippi:
Object-Centric Relational Representations for Image Generation. Trans. Mach. Learn. Res. 2024 (2024)- [j85]Daniele Grattarola
, Daniele Zambon, Filippo Maria Bianchi, Cesare Alippi:
Understanding Pooling in Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2708-2718 (2024) - [j84]Zhigang Liu, Cesare Alippi, Hongtian Chen, Derong Liu:
Guest Editorial: Special Issue on Explainable Representation Learning-Based Intelligent Inspection and Maintenance of Complex Systems. IEEE Trans. Neural Networks Learn. Syst. 35(5): 5819-5823 (2024) - [j83]Hongtian Chen, Zhigang Liu, Cesare Alippi, Biao Huang, Derong Liu:
Explainable Intelligent Fault Diagnosis for Nonlinear Dynamic Systems: From Unsupervised to Supervised Learning. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6166-6179 (2024) - [c103]Giovanni de Felice, Andrea Cini, Daniele Zambon, Vladimir V. Gusev, Cesare Alippi:
Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations. ICLR 2024 - [c102]Andrea Cini, Danilo P. Mandic, Cesare Alippi:
Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting. ICML 2024 - [c101]Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi:
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling. ICML 2024 - [i47]Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi:
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling. CoRR abs/2402.10634 (2024) - [i46]Giovanni de Felice, Andrea Cini, Daniele Zambon, Vladimir V. Gusev, Cesare Alippi:
Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations. CoRR abs/2402.12598 (2024) - [i45]Alessio Gravina, Daniele Zambon, Davide Bacciu, Cesare Alippi:
Temporal Graph ODEs for Irregularly-Sampled Time Series. CoRR abs/2404.19508 (2024) - [i44]Alessandro Manenti, Daniele Zambon, Cesare Alippi:
Learning Latent Graph Structures and their Uncertainty. CoRR abs/2405.19933 (2024) - 2023
- [j82]Andrea Cini, Daniele Zambon, Cesare Alippi:
Sparse Graph Learning from Spatiotemporal Time Series. J. Mach. Learn. Res. 24: 242:1-242:36 (2023) - [j81]Lorenzo Ferretti, Andrea Cini, Georgios Zacharopoulos, Cesare Alippi, Laura Pozzi:
Graph Neural Networks for High-Level Synthesis Design Space Exploration. ACM Trans. Design Autom. Electr. Syst. 28(2): 25:1-25:20 (2023) - [c100]Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi:
Scalable Spatiotemporal Graph Neural Networks. AAAI 2023: 7218-7226 - [c99]Antonino Maria Rizzo, Luca Magri, Pietro Invernizzi, Enrico Sozio, Gabriele Aquaro, Stefano Binetti, Cesare Alippi, Giacomo Boracchi:
Event Detection in Optical Signals via Domain Adaptation. EUSIPCO 2023: 1435-1439 - [c98]Antonino Maria Rizzo, Luca Magri, Pietro Invernizzi, Enrico Sozio, Stefano Piciaccia, Alberto Tanzi, Stefano Binetti, Cesare Alippi, Giacomo Boracchi:
Anomaly Detection in Optical Spectra VIA Joint Optimization. ICASSP 2023: 1-5 - [c97]Filippo Leveni, Luca Magri, Cesare Alippi, Giacomo Boracchi:
Hashing for Structure-Based Anomaly Detection. ICIAP (2) 2023: 25-36 - [c96]Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi:
Taming Local Effects in Graph-based Spatiotemporal Forecasting. NeurIPS 2023 - [i43]Daniele Zambon, Andrea Cini, Lorenzo Livi, Cesare Alippi:
Graph state-space models. CoRR abs/2301.01741 (2023) - [i42]Daniele Zambon, Cesare Alippi:
Where and How to Improve Graph-based Spatio-temporal Predictors. CoRR abs/2302.01701 (2023) - [i41]Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi:
Taming Local Effects in Graph-based Spatiotemporal Forecasting. CoRR abs/2302.04071 (2023) - [i40]Cesare Alippi, Daniele Zambon:
Graph Kalman Filters. CoRR abs/2303.12021 (2023) - [i39]Luca Butera, Andrea Cini, Alberto Ferrante, Cesare Alippi:
Relational Inductive Biases for Object-Centric Image Generation. CoRR abs/2303.14681 (2023) - [i38]Tommaso Marzi, Arshjot Khehra, Andrea Cini, Cesare Alippi:
Feudal Graph Reinforcement Learning. CoRR abs/2304.05099 (2023) - [i37]Andrea Cini, Danilo P. Mandic, Cesare Alippi:
Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting. CoRR abs/2305.19183 (2023) - [i36]Ming Jin, Huan Yee Koh, Qingsong Wen, Daniele Zambon, Cesare Alippi, Geoffrey I. Webb, Irwin King, Shirui Pan:
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection. CoRR abs/2307.03759 (2023) - [i35]Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi:
Graph Deep Learning for Time Series Forecasting. CoRR abs/2310.15978 (2023) - 2022
- [j80]Giuseppe Canonaco, Manuel Roveri, Cesare Alippi, Fabrizio Podenzani, Antonio Bennardo, Marco Conti, Nicola Mancini:
A transfer-learning approach for corrosion prediction in pipeline infrastructures. Appl. Intell. 52(7): 7622-7637 (2022) - [j79]Alberto Gasparin, Slobodan Lukovic, Cesare Alippi:
Deep learning for time series forecasting: The electric load case. CAAI Trans. Intell. Technol. 7(1): 1-25 (2022) - [j78]Daniele Grattarola, Lorenzo Livi, Cesare Alippi, Richard Wennberg, Taufik A. Valiante:
Seizure localisation with attention-based graph neural networks. Expert Syst. Appl. 203: 117330 (2022) - [j77]Luca Butera, Alberto Ferrante, Mauro Jermini, Mauro Prevostini, Cesare Alippi:
Precise Agriculture: Effective Deep Learning Strategies to Detect Pest Insects. IEEE CAA J. Autom. Sinica 9(2): 246-258 (2022) - [j76]Antonino Maria Rizzo, Luca Magri, Davide Rutigliano, Pietro Invernizzi, Enrico Sozio, Cesare Alippi, Stefano Binetti, Giacomo Boracchi:
Known and unknown event detection in OTDR traces by deep learning networks. Neural Comput. Appl. 34(22): 19655-19673 (2022) - [j75]Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Graph Neural Networks With Convolutional ARMA Filters. IEEE Trans. Pattern Anal. Mach. Intell. 44(7): 3496-3507 (2022) - [j74]Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Hierarchical Representation Learning in Graph Neural Networks With Node Decimation Pooling. IEEE Trans. Neural Networks Learn. Syst. 33(5): 2195-2207 (2022) - [j73]Pietro Verzelli, Cesare Alippi, Lorenzo Livi, Peter Tino:
Input-to-State Representation in Linear Reservoirs Dynamics. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4598-4609 (2022) - [c95]Andrea Cini, Ivan Marisca, Cesare Alippi:
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks. ICLR 2022 - [c94]Simone Eandi, Andrea Cini, Slobodan Lukovic, Cesare Alippi:
Spatio-Temporal Graph Neural Networks for Aggregate Load Forecasting. IJCNN 2022: 1-8 - [c93]Matteo Munari, Luca Pasa, Daniele Zambon, Cesare Alippi, Nicolò Navarin:
Understanding Catastrophic Forgetting of Gated Linear Networks in Continual Learning. IJCNN 2022: 1-8 - [c92]Daniele Zambon, Lorenzo Livi, Cesare Alippi:
Graph iForest: Isolation of anomalous and outlier graphs. IJCNN 2022: 1-8 - [c91]Ivan Marisca, Andrea Cini, Cesare Alippi:
Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations. NeurIPS 2022 - [c90]Daniele Zambon, Cesare Alippi:
AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs. NeurIPS 2022 - [c89]Kleanthis Malialis, Manuel Roveri, Cesare Alippi, Christos G. Panayiotou, Marios M. Polycarpou:
A Hybrid Active-Passive Approach to Imbalanced Nonstationary Data Stream Classification. SSCI 2022: 1021-1027 - [i34]Daniele Zambon, Cesare Alippi:
AZ-whiteness test: a test for uncorrelated noise on spatio-temporal graphs. CoRR abs/2204.11135 (2022) - [i33]Ivan Marisca, Andrea Cini, Cesare Alippi:
Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations. CoRR abs/2205.13479 (2022) - [i32]Andrea Cini, Daniele Zambon, Cesare Alippi:
Sparse Graph Learning for Spatiotemporal Time Series. CoRR abs/2205.13492 (2022) - [i31]Andrea Cini, Ivan Marisca, Filippo Maria Bianchi, Cesare Alippi:
Scalable Spatiotemporal Graph Neural Networks. CoRR abs/2209.06520 (2022) - [i30]Kleanthis Malialis, Manuel Roveri, Cesare Alippi, Christos G. Panayiotou, Marios M. Polycarpou:
A Hybrid Active-Passive Approach to Imbalanced Nonstationary Data Stream Classification. CoRR abs/2210.04949 (2022) - 2021
- [j72]Daniele Grattarola, Cesare Alippi:
Graph Neural Networks in TensorFlow and Keras with Spektral [Application Notes]. IEEE Comput. Intell. Mag. 16(1): 99-106 (2021) - [j71]Cesare Alippi:
2021 IEEE CIS Awards [Society Briefs]. IEEE Comput. Intell. Mag. 16(4): 10-13 (2021) - [j70]Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli:
Gaussian Approximation for Bias Reduction in Q-Learning. J. Mach. Learn. Res. 22: 277:1-277:51 (2021) - [j69]Simone Disabato, Manuel Roveri, Cesare Alippi:
Distributed Deep Convolutional Neural Networks for the Internet-of-Things. IEEE Trans. Computers 70(8): 1239-1252 (2021) - [j68]Bo Zhao, Derong Liu, Cesare Alippi:
Sliding-Mode Surface-Based Approximate Optimal Control for Uncertain Nonlinear Systems With Asymptotically Stable Critic Structure. IEEE Trans. Cybern. 51(6): 2858-2869 (2021) - [c88]Davide Rutigliano, Giacomo Boracchi, Pietro Invernizzi, Enrico Sozio, Cesare Alippi, Stefano Binetti:
Event-Detection Deep Neural Network for OTDR Trace Analysis. EANN 2021: 190-201 - [c87]Davide Bacciu, Filippo Maria Bianchi, Benjamin Paassen, Cesare Alippi:
Deep learning for graphs. ESANN 2021 - [c86]Giuseppe Canonaco, Manuel Roveri, Cesare Alippi, Fabrizio Podenzani, Antonio Bennardo, Marco Conti, Nicola Mancini:
A Machine-Learning Approach for the Prediction of Internal Corrosion in Pipeline Infrastructures. I2MTC 2021: 1-6 - [c85]Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara Hammer:
Graph Edit Networks. ICLR 2021 - [c84]Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Learning Graph Cellular Automata. NeurIPS 2021: 20983-20994 - [c83]Simone Disabato, Giuseppe Canonaco, Paul G. Flikkema, Manuel Roveri, Cesare Alippi:
Birdsong Detection at the Edge with Deep Learning. SMARTCOMP 2021: 9-16 - [i29]Andrea Cini, Ivan Marisca, Cesare Alippi:
Multivariate Time Series Imputation by Graph Neural Networks. CoRR abs/2108.00298 (2021) - [i28]Daniele Grattarola, Daniele Zambon, Filippo Maria Bianchi, Cesare Alippi:
Understanding Pooling in Graph Neural Networks. CoRR abs/2110.05292 (2021) - [i27]Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Learning Graph Cellular Automata. CoRR abs/2110.14237 (2021) - [i26]Zhiwen Chen, Jiamin Xu, Cesare Alippi, Steven X. Ding, Yuri A. W. Shardt, Tao Peng, Chunhua Yang:
Graph neural network-based fault diagnosis: a review. CoRR abs/2111.08185 (2021) - [i25]Lorenzo Ferretti, Andrea Cini, Georgios Zacharopoulos, Cesare Alippi, Laura Pozzi:
A Graph Deep Learning Framework for High-Level Synthesis Design Space Exploration. CoRR abs/2111.14767 (2021) - 2020
- [j67]Cesare Alippi:
2020 IEEE CIS Awards [Society Briefs]. IEEE Comput. Intell. Mag. 15(1): 14-16 (2020) - [j66]Haowei Lin, Bo Zhao, Derong Liu, Cesare Alippi:
Data-based fault tolerant control for affine nonlinear systems through particle swarm optimized neural networks. IEEE CAA J. Autom. Sinica 7(4): 954-964 (2020) - [j65]Dongbin Zhao, Shukai Duan, Zheng Yan, Cesare Alippi:
Advances in deep neural information processing. Neurocomputing 408: 80-81 (2020) - [j64]Daniele Grattarola, Daniele Zambon, Lorenzo Livi, Cesare Alippi:
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds. IEEE Trans. Neural Networks Learn. Syst. 31(6): 1856-1869 (2020) - [c82]Giuseppe Canonaco, Manuel Roveri, Cesare Alippi, Fabrizio Podenzani, Antonio Bennardo, Marco Conti, Nicola Mancini:
Corrosion Prediction in Oil and Gas Pipelines: a Machine Learning Approach. I2MTC 2020: 1-6 - [c81]Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi:
Spectral Clustering with Graph Neural Networks for Graph Pooling. ICML 2020: 874-883 - [c80]Daniele Zambon, Cesare Alippi, Lorenzo Livi:
Graph Random Neural Features for Distance-Preserving Graph Representations. ICML 2020: 10968-10977 - [c79]Filippo Leveni, Luca Magri, Giacomo Boracchi, Cesare Alippi:
PIF: Anomaly detection via preference embedding. ICPR 2020: 8077-8084 - [c78]Andrea Cini, Slobodan Lukovic, Cesare Alippi:
Cluster-based Aggregate Load Forecasting with Deep Neural Networks. IJCNN 2020: 1-8 - [i24]Andrea Cini, Carlo D'Eramo, Jan Peters, Cesare Alippi:
Deep Reinforcement Learning with Weighted Q-Learning. CoRR abs/2003.09280 (2020) - [i23]Pietro Verzelli, Cesare Alippi, Lorenzo Livi, Peter Tiño:
Input representation in recurrent neural networks dynamics. CoRR abs/2003.10585 (2020) - [i22]Daniele Grattarola, Cesare Alippi:
Graph Neural Networks in TensorFlow and Keras with Spektral. CoRR abs/2006.12138 (2020) - [i21]Pietro Verzelli, Cesare Alippi, Lorenzo Livi:
Learn to Synchronize, Synchronize to Learn. CoRR abs/2010.02860 (2020)
2010 – 2019
- 2019
- [j63]Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Adversarial autoencoders with constant-curvature latent manifolds. Appl. Soft Comput. 81 (2019) - [j62]Daniele Zambon, Cesare Alippi, Lorenzo Livi:
Change-Point Methods on a Sequence of Graphs. IEEE Trans. Signal Process. 67(24): 6327-6341 (2019) - [c77]Pietro Verzelli, Cesare Alippi, Lorenzo Livi:
Hyper-spherical Reservoirs for Echo State Networks. ICANN (Workshop) 2019: 89-93 - [c76]Daniele Zambon, Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Autoregressive Models for Sequences of Graphs. IJCNN 2019: 1-8 - [i20]Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Graph Neural Networks with convolutional ARMA filters. CoRR abs/1901.01343 (2019) - [i19]Daniele Zambon, Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Autoregressive Models for Sequences of Graphs. CoRR abs/1903.07299 (2019) - [i18]Pietro Verzelli, Cesare Alippi, Lorenzo Livi:
Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere. CoRR abs/1903.11691 (2019) - [i17]Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi:
Mincut pooling in Graph Neural Networks. CoRR abs/1907.00481 (2019) - [i16]Alberto Gasparin, Slobodan Lukovic, Cesare Alippi:
Deep Learning for Time Series Forecasting: The Electric Load Case. CoRR abs/1907.09207 (2019) - [i15]Simone Disabato, Manuel Roveri, Cesare Alippi:
Distributed Deep Convolutional Neural Networks for the Internet-of-Things. CoRR abs/1908.01656 (2019) - [i14]Daniele Zambon, Cesare Alippi, Lorenzo Livi:
Distance-Preserving Graph Embeddings from Random Neural Features. CoRR abs/1909.03790 (2019) - [i13]Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling. CoRR abs/1910.11436 (2019) - 2018
- [j61]Jianhua Ma, Cesare Alippi, Laurence T. Yang, Huansheng Ning, Kevin I-Kai Wang:
Introduction to the IEEE CIS TC on Smart World (SWTC) [Society Briefs]. IEEE Comput. Intell. Mag. 13(1): 7-9 (2018) - [j60]Li Bu, Cesare Alippi, Dongbin Zhao:
A pdf-Free Change Detection Test Based on Density Difference Estimation. IEEE Trans. Neural Networks Learn. Syst. 29(2): 324-334 (2018) - [j59]Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi:
Investigating Echo-State Networks Dynamics by Means of Recurrence Analysis. IEEE Trans. Neural Networks Learn. Syst. 29(2): 427-439 (2018) - [j58]Lorenzo Livi, Filippo Maria Bianchi, Cesare Alippi:
Determination of the Edge of Criticality in Echo State Networks Through Fisher Information Maximization. IEEE Trans. Neural Networks Learn. Syst. 29(3): 706-717 (2018) - [j57]Andrea Dal Pozzolo, Giacomo Boracchi, Olivier Caelen, Cesare Alippi, Gianluca Bontempi:
Credit Card Fraud Detection: A Realistic Modeling and a Novel Learning Strategy. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3784-3797 (2018) - [j56]Daniele Zambon, Cesare Alippi, Lorenzo Livi:
Concept Drift and Anomaly Detection in Graph Streams. IEEE Trans. Neural Networks Learn. Syst. 29(11): 5592-5605 (2018) - [c75]Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi:
On the Interpretation and Characterization of Echo State Networks Dynamics: A Complex Systems Perspective. Advances in Data Analysis with Computational Intelligence Methods 2018: 143-167 - [c74]Francesco Regazzoni, Cesare Alippi, Ilia Polian:
Security: the dark side of approximate computing? ICCAD 2018: 44 - [c73]Daniele Zambon, Lorenzo Livi, Cesare Alippi:
Anomaly and Change Detection in Graph Streams through Constant-Curvature Manifold Embeddings. IJCNN 2018: 1-7 - [c72]Cesare Alippi, Simone Disabato, Manuel Roveri:
Moving convolutional neural networks to embedded systems: the alexnet and VGG-16 case. IPSN 2018: 212-223 - [c71]Pietro Verzelli, Lorenzo Livi, Cesare Alippi:
A characterization of the Edge of Criticality in Binary echo State Networks. MLSP 2018: 1-6 - [p3]Cesare Alippi, Wen Qi, Manuel Roveri:
An Improved Hilbert-Huang Transform for Non-linear and Time-Variant Signals. Multidisciplinary Approaches to Neural Computing 2018: 109-117 - [i12]Daniele Zambon, Lorenzo Livi, Cesare Alippi:
Anomaly and Change Detection in Graph Streams through Constant-Curvature Manifold Embeddings. CoRR abs/1805.01360 (2018) - [i11]Daniele Grattarola, Daniele Zambon, Cesare Alippi, Lorenzo Livi:
Learning Graph Embeddings on Constant-Curvature Manifolds for Change Detection in Graph Streams. CoRR abs/1805.06299 (2018) - [i10]Daniele Zambon, Cesare Alippi, Lorenzo Livi:
Change Point Methods on a Sequence of Graphs. CoRR abs/1805.07113 (2018) - [i9]Pietro Verzelli, Lorenzo Livi, Cesare Alippi:
A characterization of the Edge of Criticality in Binary Echo State Networks. CoRR abs/1810.01742 (2018) - [i8]Daniele Grattarola, Lorenzo Livi, Cesare Alippi:
Adversarial Autoencoders with Constant-Curvature Latent Manifolds. CoRR abs/1812.04314 (2018) - [i7]Stjepan Picek, Annelie Heuser, Cesare Alippi, Francesco Regazzoni:
When Theory Meets Practice: A Framework for Robust Profiled Side-channel Analysis. IACR Cryptol. ePrint Arch. 2018: 1123 (2018) - 2017
- [j55]Cesare Alippi, Manuel Roveri:
The (Not) Far-Away Path to Smart Cyber-Physical Systems: An Information-Centric Framework. Computer 50(4): 38-47 (2017) - [j54]Sen Bong Gee, Kay Chen Tan, Cesare Alippi:
Solving Multiobjective Optimization Problems in Unknown Dynamic Environments: An Inverse Modeling Approach. IEEE Trans. Cybern. 47(12): 4223-4234 (2017) - [j53]Cesare Alippi, Stavros Ntalampiras, Manuel Roveri:
Model-Free Fault Detection and Isolation in Large-Scale Cyber-Physical Systems. IEEE Trans. Emerg. Top. Comput. Intell. 1(1): 61-71 (2017) - [j52]Cesare Alippi, Giacomo Boracchi, Manuel Roveri:
Hierarchical Change-Detection Tests. IEEE Trans. Neural Networks Learn. Syst. 28(2): 246-258 (2017) - [j51]Lorenzo Livi, Cesare Alippi:
One-Class Classifiers Based on Entropic Spanning Graphs. IEEE Trans. Neural Networks Learn. Syst. 28(12): 2846-2858 (2017) - [j50]Li Bu, Dongbin Zhao, Cesare Alippi:
An Incremental Change Detection Test Based on Density Difference Estimation. IEEE Trans. Syst. Man Cybern. Syst. 47(10): 2714-2726 (2017) - [c70]Cesare Alippi, Wen Qi, Manuel Roveri:
Learning in Nonstationary Environments: A Hybrid Approach. ICAISC (2) 2017: 703-714 - [c69]Filippo Maria Bianchi, Lorenzo Livi, Robert Jenssen, Cesare Alippi:
Critical echo state network dynamics by means of Fisher information maximization. IJCNN 2017: 852-858 - [c68]Cesare Alippi, Viviana D'Alto, Mirko Falchetto, Danilo Pau, Manuel Roveri:
Detecting changes at the sensor level in cyber-physical systems: Methodology and technological implementation. IJCNN 2017: 1780-1786 - [c67]