Contact

Dipartimento di Informatica
Università degli Studi di Milano
via Comelico 39/41
I-20135 Milano - Italy

Phone +39 02503.16262
Fax +39 02503.16373
Email grossi@di.unimi.it

Teaching activity

current (Italian)
GPU computing (Laurea Magistrale in Informatica)
Methods for signal processing (Laurea Magistrale in Informatica)
past
Sistemi e Segnali (Laurea Triennale in Informatica)
Signal processing laboratory (Laurea Triennale in Informatica)
Matlab course (Scuola di Fisica Medica)
Java programming laboratory (Laurea Triennale in Informatica)
Digital signal processing (Laurea Triennale in Informatica)
Stochastic signal processing (Laurea Magistrale in Informatica)

Research interests

Sparse representation models for solving underdetermined linear systems
Sparse recovery and regularization methods in signal processing
Face recognition via sparse decomposition
Computing approximate solutions to NP-hard problems mainly by neural and genetic models.
Neural hardware implementation on programmable logic

Projects

[2013-2016]
European project FP7-ICT-2013-11: Future Networks. Project title: Network Functions as-a-Service over Virtualised Infrastructures (T-NOVA), project number 619520.
[2013-2016]
National project Futuro in Ricerca (FIRB) program. Project title: Interpreting emotions: a computational tool integrating facial expressions and biosignals based shape analysis and bayesian networks, Founded by MIUR - Ministero dell'Istruzione dell'Università e della Ricerca.
[2001-2002]
National research project COFIN. Project title: Modelli di calcolo innovativi: metodi sintattici e combinatori, Founded by MIUR - Ministero dell'Istruzione dell'Università e della Ricerca.
[1998-2001]
National project with title Progetto Finalizzato Biotecnologie. Work: Studio e sviluppo di un sistema software per il controllo in tempo reale di esperimenti di misura del calcio intracellulare. Used by Centro di Cito-Farmacologia del CNR - l'ospedale San Raffaele ({\em Atti del Convegno del Progetto Finalizzato Biotecnologie Genova 2001}).

PhD student

Alessandro Adamo (past)
Massimo Marchi (past)

Software

The LiMapS algorithm
A new regularization method for sparse recovery based on a fixed-point iteration schema which combines Lipschitzian-type mappings and orthogonal projectors
LiMaps package for MATLAB
The k-LiMapS algorithm
A new algorithm to solve the sparse approximation problem over redundant dictionaries based on LiMapS, but retaining the best k basis (or dictionary) atoms
k-LiMaps package for MATLAB
The PrunICA algorithm
PrunICA is way to speed-up the FastICA-like algorithms by a controlled random pruning of the input mixtures, both on the entire mixture or on fixed-size blocks when segmented
PrunICA package for MATLAB

Papers

  2017 (3)
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
  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.
doi   bibtex
  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.
bibtex
  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.
bibtex
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.
bibtex
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.
doi   bibtex
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.
bibtex
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.
doi   bibtex
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.
bibtex
  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.
bibtex
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.
doi   bibtex
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 (1)
A Discrete Neural Algorithm for the Maximum Clique Problem: Analysis and Circuit Implementation. In , editor(s), Proceedings of the Workshop on Algorithm Engineering (WAE'97), .
bibtex

Links

Dalab: Digital Architecture Laboratory at DI.
Rice University: compressive sensing resources.
ECCC: Electronic Colloquium on Computational Complexity.
Compendium: a list of NP-complete optimization problems.
GNU: free software project.
www.itcline.it: web design.


Latest update Sept 2016