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  2018 (3)
Enhanced multicore–manycore interaction in high-performance video encoding. Grossi, G.; Paglierani, P.; Pedersini, F.; and Petrini, A. Journal of Real-Time Image Processing. Nov 2018.
Enhanced multicore–manycore interaction in high-performance video encoding [link]Paper   doi   bibtex  
A GPU-based algorithm for fast node label learning in large and unbalanced biomolecular networks. Frasca, M.; Grossi, G.; Gliozzo, J.; Mesiti, M.; Notaro, M.; Perlasca, P.; Petrini, A.; and Valentini, G. BMC Bioinformatics, 19(10): 353. Oct 2018.
A GPU-based algorithm for fast node label learning in large and unbalanced biomolecular networks [link]Paper   doi   bibtex  
Deep Construction of an Affective Latent Space via Multimodal Enactment. Boccignone, G.; Conte, D.; Cuculo, V.; D’Amelio, A.; Grossi, G.; and Lanzarotti, R. IEEE Transactions on Cognitive and Developmental Systems, 10(4): 865-880. 2018.
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  2017 (6)
Sparse decomposition by iterating Lipschitzian-type mappings . Adamo, A.; Grossi, G.; Lanzarotti, R.; and Lin, J. Theoretical Computer Science , 664: 12 - 28. 2017.
Sparse decomposition by iterating Lipschitzian-type mappings  [link]Paper   doi   bibtex  
Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation. Grossi, G. A. L.; and Raffaella AND Lin, J. PLOS ONE, 12(1): 1-16. 01 2017.
Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation [link]Paper   doi   bibtex  
Sum signal dosimetry: A new approach for high dose quality assurance with Gafchromic EBT3. Cusumano, D.; Fumagalli, M. L.; Ghielmetti, F.; Rossi, L.; Grossi, G.; Lanzarotti, R.; Fariselli, L.; and De Martin, E. Journal of Applied Clinical Medical Physics. 2017.
Sum signal dosimetry: A new approach for high dose quality assurance with Gafchromic EBT3 [link]Paper   doi   bibtex  
Taking the Hidden Route: Deep Mapping of Affect via 3D Neural Networks. Ceruti, C.; Cuculo, V.; D'Amelio, A.; Grossi, G.; and Lanzarotti, R. In Battiato, S.; Farinella, G. M.; Leo, M.; and Gallo, G., editor(s), New Trends in Image Analysis and Processing – ICIAP 2017, pages 189–196, Cham, 2017. Springer International Publishing
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Virtual EMG via Facial Video Analysis. Boccignone, G.; Cuculo, V.; Grossi, G.; Lanzarotti, R.; and Migliaccio, R. In Battiato, S.; Gallo, G.; Schettini, R.; and Stanco, F., editor(s), Image Analysis and Processing - ICIAP 2017 , pages 197–207, Cham, 2017. Springer International Publishing
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A Note on Modelling a Somatic Motor Space for Affective Facial Expressions. D'Amelio, A.; Cuculo, V.; Grossi, G.; Lanzarotti, R.; and Lin, J. In Battiato, S.; Farinella, G. M.; Leo, M.; and Gallo, G., editor(s), New Trends in Image Analysis and Processing – ICIAP 2017, pages 181–188, 2017. Springer International Publishing
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  2016 (3)
Robust Face Recognition Providing the Identity and Its Reliability Degree Combining Sparse Representation and Multiple Features. Grossi, G.; Lanzarotti, R.; and Lin, J. International Journal of Pattern Recognition and Artificial Intelligence, 30(10): 1656007. 2016.
Robust Face Recognition Providing the Identity and Its Reliability Degree Combining Sparse Representation and Multiple Features [link]Paper   doi   bibtex  
GPU-based VP8 encoding: Performance in native and virtualized environments. Paglierani, P.; Grossi, G.; Pedersini, F.; and Petrini, A. In 2016 International Conference on Telecommunications and Multimedia, TEMU 2016, Heraklion, Crete, Greece, July 25-27, 2016, pages 1–5, 2016.
GPU-based VP8 encoding: Performance in native and virtualized environments [link]Paper   doi   bibtex  
Hardware-accelerated high-resolution video coding in Virtual Network Functions. Comi, P.; Crosta, P. S.; Beccari, M.; Paglierani, P.; Grossi, G.; Pedersini, F.; and Petrini, A. In 2016 European Conference on Networks and Communications (EuCNC), pages 32-36, 2016.
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  2015 (4)
High-rate compression of ECG signals by an accuracy-driven sparsity model relying on natural basis. Grossi, G.; Lanzarotti, R.; and Lin, J. Digital Signal Processing, 45: 96–106. 2015.
High-rate compression of ECG signals by an accuracy-driven sparsity model relying on natural basis [link]Paper   doi   bibtex  
Robust face recognition using sparse representation in LDA space. Adamo, A.; Grossi, G.; Lanzarotti, R.; and Lin, J. Machine Vision and Applications, 26(6): 837–847. 2015.
Robust face recognition using sparse representation in LDA space [link]Paper   doi   bibtex  
ECG compression retaining the best natural basis k-coefficients via sparse decomposition. Adamo, A.; Grossi, G.; Lanzarotti, R.; and Lin, J. Biomed. Signal Proc. and Control, 15: 11–17. 2015.
ECG compression retaining the best natural basis k-coefficients via sparse decomposition [link]Paper   doi   bibtex  
A Selection Module for Large-Scale Face Recognition Systems. Grossi, G.; Lanzarotti, R.; and Lin, J. In Image Analysis and Processing - ICIAP 2015 - 18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II, pages 529–539, 2015.
A Selection Module for Large-Scale Face Recognition Systems [link]Paper   doi   bibtex  
  2013 (2)
Face Recognition in Uncontrolled Conditions Using Sparse Representation and Local Features. Adamo, A.; Grossi, G.; and Lanzarotti, R. In Image Analysis and Processing - ICIAP 2013 - 17th International Conference, pages 31–40, 2013.
Face Recognition in Uncontrolled Conditions Using Sparse Representation and Local Features [link]Paper   doi   bibtex  
Local features and sparse representation for face recognition with partial occlusions. Adamo, A.; Grossi, G.; and Lanzarotti, R. In IEEE International Conference on Image Processing, ICIP 2013, pages 3008–3012, 2013.
Local features and sparse representation for face recognition with partial occlusions [link]Paper   doi   bibtex  
  2012 (1)
Sparse Representation Based Classification for Face Recognition by k-LiMapS Algorithm. Adamo, A.; Grossi, G.; and Lanzarotti, R. In Image and Signal Processing - 5th International Conference, ICISP 2012, pages 245–252, 2012.
Sparse Representation Based Classification for Face Recognition by k-LiMapS Algorithm [link]Paper   doi   bibtex  
  2011 (2)
A fixed-point iterative schema for error minimization in k-sparse decomposition. Adamo, A.; and Grossi, G. In 2011 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011, pages 167–172, 2011.
A fixed-point iterative schema for error minimization in k-sparse decomposition [link]Paper   doi   bibtex  
Sparsity recovery by iterative orthogonal projections of nonlinear mappings. Adamo, A.; and Grossi, G. In 2011 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011, pages 173–178, 2011.
Sparsity recovery by iterative orthogonal projections of nonlinear mappings [link]Paper   doi   bibtex  
  2010 (4)
Random Pruning of Blockwise Stationary Mixtures for Online BSS. Adamo, A.; and Grossi, G. In Latent Variable Analysis and Signal Separation - 9th International Conference, LVA/ICA 2010, pages 213–220, 2010.
Random Pruning of Blockwise Stationary Mixtures for Online BSS [link]Paper   doi   bibtex  
Trade-off between hops and delays in hub-based forwarding in DTNs. Adamo, A.; Grossi, G.; and Pedersini, F. In Proceedings of the 3rd IFIP Wireless Days Conference 2010, pages 1–5, 2010.
Trade-off between hops and delays in hub-based forwarding in DTNs [link]Paper   doi   bibtex  
Hub-betweenness analysis in delay tolerant networks inferred by real traces. Grossi, G.; and Pedersini, F. In 8th International Symposium on Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks (WiOpt 2010), pages 318–323, 2010.
Hub-betweenness analysis in delay tolerant networks inferred by real traces [link]Paper   bibtex  
Learning functional linkage networks with a cost-sensitive approach. Bertoni, A.; Frasca, M.; Grossi, G.; and Valentini, G. In Neural Nets WIRN10 - Proceedings of the 20th Italian Workshop on Neural Nets, pages 52–61, 2010.
Learning functional linkage networks with a cost-sensitive approach [link]Paper   doi   bibtex  
  2009 (2)
Adaptiveness in Monotone Pseudo-Boolean Optimization and Stochastic Neural Computation. Grossi, G. Int. J. Neural Syst., 19(4): 241–252. 2009.
Adaptiveness in Monotone Pseudo-Boolean Optimization and Stochastic Neural Computation [link]Paper   doi   bibtex  
Experimental Analysis of Graph-based Answer Set Computation over Parallel and Distributed Architectures. Grossi, G.; Marchi, M.; Pontelli, E.; and Provetti, A. J. Log. Comput., 19(4): 697–715. 2009.
Experimental Analysis of Graph-based Answer Set Computation over Parallel and Distributed Architectures [link]Paper   doi   bibtex  
  2008 (3)
FPGA implementation of a stochastic neural network for monotonic pseudo-Boolean optimization. Grossi, G.; and Pedersini, F. Neural Networks, 21(6): 872–879. 2008.
FPGA implementation of a stochastic neural network for monotonic pseudo-Boolean optimization [link]Paper   doi   bibtex  
A two-level social mobility model for trace generation. Gaito, S.; Grossi, G.; and Pedersini, F. In Proceedings of the 9th ACM Interational Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2008, pages 457–458, 2008.
A two-level social mobility model for trace generation [link]Paper   doi   bibtex  
Experimental validation of a 2-level social mobility model in opportunistic networks. Gaito, S.; Grossi, G.; Pedersini, F.; and Rossi, P. In Wireless Days, 2008. WD '08. 1st IFIP, pages 334–338, 2008.
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  2007 (5)
Experiments with answer set computation over parallel and distributed architectures. Grossi, G.; and Marchi, M. In 4th International Workshop on Answer Set Programming (ASP '07), pages 7–20, 2007.
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Experiments with answer set computation over parallel and distributed architectures. Grossi, G.; and Marchi, M. In 4th International Workshop on Answer Set Programming (ASP '07), pages 21–32, 2007.
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Speeding Up FastICA by Mixture Random Pruning. Gaito, S.; and Grossi, G. In Independent Component Analysis and Signal Separation, 7th International Conference, ICA 2007, pages 185–192, 2007.
Speeding Up FastICA by Mixture Random Pruning [link]Paper   doi   bibtex  
Extending Mixture Random Pruning to Nonpolynomial Contrast Functions in FastICA. Gaito, S.; and Grossi, G. In Signal Processing and Information Technology (ISSPIT 07), IEEE International Symposium on, pages 334–338, 2007.
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FPGA Implementation of an Adaptive Stochastic Neural Model. Grossi, G.; and Pedersini, F. In Artificial Neural Networks - ICANN 2007, 17th International Conference, pages 559–568, 2007.
FPGA Implementation of an Adaptive Stochastic Neural Model [link]Paper   doi   bibtex  
  2006 (3)
Solving maximum independent set by asynchronous distributed hopfield-type neural networks. Grossi, G.; Marchi, M.; and Posenato, R. RAIRO - Theoretical Informatics and Applications, 40(2): 371–388. 2006.
Solving maximum independent set by asynchronous distributed hopfield-type neural networks [link]Paper   doi   bibtex  
Random projections for dimensionality reduction in ICA. Gaito, S.; Greppi, A.; and Grossi, G. International Journal of Applied Science, Engineering and Technology, 15: 154–158. 2006.
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A Discrete Adaptive Stochastic Neural Model for Constrained Optimization. Grossi, G. In Artificial Neural Networks - ICANN 2006, 16th International Conference, pages 641–650, 2006.
A Discrete Adaptive Stochastic Neural Model for Constrained Optimization [link]Paper   doi   bibtex  
  2005 (2)
A Stochastic Neural Model for Graph Problems: Software and Hardware Implementation. Grossi, G.; and Pedersini, F. In Neural Networks and Brain (ICNNB '05). International Conference on, volume 1, pages 115–120, 2005.
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A New Algorithm for Answer Set Computation. Grossi, G.; and Marchi, M. In Answer Set Programming, Advances in Theory and Implementation, Proceedings of the 3rd Intl. ASP'05 Workshop, 2005.
A New Algorithm for Answer Set Computation [pdf]Paper   bibtex  
  2002 (2)
A Neural Algorithm for the Maximum Clique Problem: Analysis, Experiments, and Circuit Implementation. Bertoni, A.; Campadelli, P.; and Grossi, G. Algorithmica, 33(1): 71–88. 2002.
A Neural Algorithm for the Maximum Clique Problem: Analysis, Experiments, and Circuit Implementation [link]Paper   doi   bibtex  
A Distributed Algorithm for Max Independent Set Problem Based on Hopfield Networks. Grossi, G.; and Posenato, R. In Neural Nets, 13th Italian Workshop on Neural Nets, WIRN VIETRI 2002, pages 64–74, 2002.
A Distributed Algorithm for Max Independent Set Problem Based on Hopfield Networks [link]Paper   doi   bibtex  
  2001 (3)
An approximation algorithm for the maximum cut problem and its experimental analysis. Bertoni, A.; Campadelli, P.; and Grossi, G. Discrete Applied Mathematics, 110(1): 3–12. 2001.
An approximation algorithm for the maximum cut problem and its experimental analysis [link]Paper   doi   bibtex  
Solving Min Vertex Cover with Iterated Hopfield Networks. Bertoni, A.; Campadelli, P.; and Grossi, G. In Neural Nets, 13th Italian Workshop on Neural Nets, WIRN'01, pages 87–95, 2001. Springer London
Solving Min Vertex Cover with Iterated Hopfield Networks [link]Paper   doi   bibtex  
The Prospect for Answer Sets Computation by a Genetic Model. Bertoni, A.; Grossi, G.; Provetti, A.; Kreinovich, V.; and Tari, L. In Answer Set Programming, Towards Efficient and Scalable Knowledge Representation and Reasoning, Proceedings of the 1st Intl. ASP'01 Workshop, 2001.
The Prospect for Answer Sets Computation by a Genetic Model [ps]Paper   bibtex  
  2000 (1)
A Genetic Model: Analysis and Application to MAXSAT. Bertoni, A.; Campadelli, P.; Carpentieri, M.; and Grossi, G. Evolutionary Computation, 8(3): 291–309. 2000.
A Genetic Model: Analysis and Application to MAXSAT [link]Paper   doi   bibtex  
  1998 (1)
An approximation algorithm for the maximum cut problem and its experimental analysis. Bertoni, A.; Campadelli, P.; and Grossi, G. In Battiti, R.; and Bertossi, A., editor(s), Algorithms and Experiments (ALEX98), pages 137–143, 1998.
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  1997 (3)
A Neural Algorithm for MAX-2SAT: Performance Analysis and Circuit Implementation. Alberti, M. A.; Bertoni, A.; Campadelli, P.; Grossi, G.; and Posenato, R. Neural Networks, 10(3): 555–560. 1997.
A Neural Algorithm for MAX-2SAT: Performance Analysis and Circuit Implementation [link]Paper   doi   bibtex  
Analysis of a Genetic Model. Bertoni, A.; Campadelli, P.; Carpentieri, M.; and Grossi, G. In Proceedings of the 7th International Conference on Genetic Algorithms, pages 121–126, 1997.
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Sequences of Discrete Hopfield Networks for the Maximum Clique Problem. Grossi, G. In Neural Nets WIRN VIETRI-97, pages 139–146, 1997. Springer London
Sequences of Discrete Hopfield Networks for the Maximum Clique Problem [link]Paper   doi   bibtex  
  1996 (1)
A Genetic Model and the Hopfield Networks. Bertoni, A.; Campadelli, P.; Carpentieri, M.; and Grossi, G. In Artificial Neural Networks - ICANN 96, 1996 International Conference, pages 463–468, 1996.
A Genetic Model and the Hopfield Networks [link]Paper   doi   bibtex  
  1995 (2)
A neural circuit for the maximum 2-satisfiability problem. Alberti, M. A.; Bertoni, A.; Campadelli, P.; Grossi, G.; and Posenato, R. In Parallel and Distributed Processing. Proceedings. Euromicro Workshop on, pages 319-323, Jan 1995.
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A neural circuit for the maximum 2-satisfiability problem. Alberti, M. A.; Bertoni, A.; Campadelli, P.; Grossi, G.; and Posenato, R. In 3rd Euromicro Workshop on Parallel and Distributed Processing (PDP '95, pages 319–323, 1995.
A neural circuit for the maximum 2-satisfiability problem [link]Paper   doi   bibtex  
  undefined (3)
Predictive sampling of facial expression dynamics driven by a latent action space. Boccignone, G.; Bodini, M.; Cuculo, V.; and Grossi, G. In IEEE 14th Int. Conf. on Signal Image Technology Internet Based Systems (SITIS-2018), . to appear
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. In .
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A Discrete Neural Algorithm for the Maximum Clique Problem: Analysis and Circuit Implementation. In null, editor(s), Proceedings of the Workshop on Algorithm Engineering (WAE'97), .
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