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ORCIDPaolo Frasconi
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- affiliation: Università degli Studi di Firenze, Italy
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2020 – today
- 2024
[j56]Luca Bindini
, Stefano Pagani, Andrea Bernardini, Benedetta Grossi, Andrea Giomi, Antonio Frontera, Paolo Frasconi:
All-in-one electrical atrial substrate indicators with deep anomaly detection. Biomed. Signal Process. Control. 98: 106737 (2024)- 2021
- [c67]Giovanni Pellegrini, Alessandro Tibo, Paolo Frasconi, Andrea Passerini, Manfred Jaeger:
Learning Aggregation Functions. IJCAI 2021: 2892-2898 - 2020
- [j55]Alessandro Tibo, Manfred Jaeger, Paolo Frasconi:
Learning and Interpreting Multi-Multi-Instance Learning Networks. J. Mach. Learn. Res. 21: 193:1-193:60 (2020) - [j54]Stefano Martina, Leonardo Ventura, Paolo Frasconi:
Classification of Cancer Pathology Reports: A Large-Scale Comparative Study. IEEE J. Biomed. Health Informatics 24(11): 3085-3094 (2020) - [c66]Michele Donini, Luca Franceschi, Orchid Majumder, Massimiliano Pontil, Paolo Frasconi:
Marthe: Scheduling the Learning Rate Via Online Hypergradients. IJCAI 2020: 2119-2125 - [c65]Valentijn Borghuis, Luca Angioloni, Lorenzo Brusci, Paolo Frasconi:
Pattern-Based Music Generation with Wasserstein Autoencoders and PRC Descriptions. IJCAI 2020: 5225-5227 - [c64]Luca Angioloni, Valentijn Borghuis, Lorenzo Brusci, Paolo Frasconi:
CONLON: A Pseudo-Song Generator Based on a New Pianoroll, Wasserstein Autoencoders, and Optimal Interpolations. ISMIR 2020: 876-883 - [i13]Stefano Martina, Leonardo Ventura, Paolo Frasconi:
Classification of cancer pathology reports: a large-scale comparative study. CoRR abs/2006.16370 (2020) - [i12]Giovanni Pellegrini, Alessandro Tibo, Paolo Frasconi, Andrea Passerini, Manfred Jaeger:
Learning Aggregation Functions. CoRR abs/2012.08482 (2020)
2010 – 2019
- 2019
- [i11]Michele Donini, Luca Franceschi, Massimiliano Pontil, Orchid Majumder, Paolo Frasconi:
Scheduling the Learning Rate via Hypergradients: New Insights and a New Algorithm. CoRR abs/1910.08525 (2019) - 2018
- [j53]Francesco Orsini, Daniele Baracchi, Paolo Frasconi:
Shift Aggregate Extract Networks. Frontiers Robotics AI 5: 42 (2018) - [c63]Luca Franceschi, Paolo Frasconi, Saverio Salzo, Riccardo Grazzi, Massimiliano Pontil:
Bilevel Programming for Hyperparameter Optimization and Meta-Learning. ICML 2018: 1563-1572 - [i10]Tijn Borghuis, Alessandro Tibo, Simone Conforti, Luca Canciello, Lorenzo Brusci, Paolo Frasconi:
Off the Beaten Track: Using Deep Learning to Interpolate Between Music Genres. CoRR abs/1804.09808 (2018) - [i9]Luca Franceschi, Paolo Frasconi, Saverio Salzo, Massimiliano Pontil:
Bilevel Programming for Hyperparameter Optimization and Meta-Learning. CoRR abs/1806.04910 (2018) - [i8]Luca Franceschi, Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo, Paolo Frasconi:
Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning. CoRR abs/1806.04941 (2018) - [i7]Alessandro Tibo, Manfred Jaeger, Paolo Frasconi:
Learning and Interpreting Multi-Multi-Instance Learning Networks. CoRR abs/1810.11514 (2018) - 2017
- [j52]Francesco Orsini, Paolo Frasconi, Luc De Raedt:
kProbLog: an algebraic Prolog for machine learning. Mach. Learn. 106(12): 1933-1969 (2017) - [c62]Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil:
On Hyperparameter Optimization in Learning Systems. ICLR (Workshop) 2017 - [c61]Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil:
Forward and Reverse Gradient-Based Hyperparameter Optimization. ICML 2017: 1165-1173 - [c60]Alessandro Tibo, Paolo Frasconi, Manfred Jaeger:
A Network Architecture for Multi-Multi-Instance Learning. ECML/PKDD (1) 2017: 737-752 - [i6]Francesco Orsini, Daniele Baracchi, Paolo Frasconi:
Shift Aggregate Extract Networks. CoRR abs/1703.05537 (2017) - [i5]Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil:
A Bridge Between Hyperparameter Optimization and Larning-to-learn. CoRR abs/1712.06283 (2017) - 2016
- [j51]Gianluca Corrado, Toma Tebaldi, Fabrizio Costa, Paolo Frasconi, Andrea Passerini:
RNAcommender: genome-wide recommendation of RNA-protein interactions. Bioinform. 32(23): 3627-3634 (2016) - [e7]Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I. Lecture Notes in Computer Science 9851, Springer 2016, ISBN 978-3-319-46127-4 [contents] - [e6]Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II. Lecture Notes in Computer Science 9852, Springer 2016, ISBN 978-3-319-46226-4 [contents] - 2015
- [c59]Paolo Soda, Ludovica Acciai, Ermanno Cordelli, Irene Costantini, Leonardo Sacconi, Francesco Saverio Pavone, Valerio Conti, Renzo Guerrini, Paolo Frasconi, Giulio Iannello:
Computer-based automatic identification of neurons in gigavoxel-sized 3D human brain images. EMBC 2015: 7724-7727 - [c58]Francesco Orsini, Paolo Frasconi, Luc De Raedt:
Graph Invariant Kernels. IJCAI 2015: 3756-3762 - [c57]Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave:
kLog: A Language for Logical and Relational Learning with Kernels (Extended Abstract). IJCAI 2015: 4183-4187 - [c56]Francesco Orsini, Paolo Frasconi, Luc De Raedt:
kProbLog: An Algebraic Prolog for Kernel Programming. ILP 2015: 152-165 - [i4]Marco Paciscopi, Ludovico Silvestri, Francesco Saverio Pavone, Paolo Frasconi:
Cell identification in whole-brain multiview images of neural activation. CoRR abs/1511.01168 (2015) - 2014
- [j50]Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave:
kLog: A language for logical and relational learning with kernels. Artif. Intell. 217: 117-143 (2014) - [j49]Paolo Frasconi, Ludovico Silvestri, Paolo Soda, Roberto Cortini, Francesco Pavone, Giulio Iannello:
Large-scale automated identification of mouse brain cells in confocal light sheet microscopy images. Bioinform. 30(17): 587-593 (2014) - [j48]Paolo Frasconi, Francesco Gabbrielli, Marco Lippi, Simone Marinai:
Markov Logic Networks for Optical Chemical Structure Recognition. J. Chem. Inf. Model. 54(8): 2380-2390 (2014) - [c55]Mathias Verbeke, Paolo Frasconi, Kurt De Grave, Fabrizio Costa, Luc De Raedt:
kLogNLP: Graph Kernel-based Relational Learning of Natural Language. ACL (System Demonstrations) 2014: 85-90 - [c54]Alessandro Bria, Giulio Iannello, Paolo Soda, Hanchuan Peng, Giovanni Erbacci, Giuseppe Fiameni, Giacomo Mariani, Roberto Mucci, Marco Rorro, Francesco Pavone, Ludovico Silvestri, Paolo Frasconi, Roberto Cortini:
A HPC infrastructure for processing and visualizing neuro-anatomical images obtained by Confocal Light Sheet Microscopy. HPCS 2014: 592-599 - 2013
- [j47]Manfred Jaeger, Marco Lippi, Andrea Passerini, Paolo Frasconi:
Type Extension Trees for feature construction and learning in relational domains. Artif. Intell. 204: 30-55 (2013) - [j46]Nicola Di Mauro, Paolo Frasconi, Fabrizio Angiulli, Davide Bacciu, Marco de Gemmis, Floriana Esposito, Nicola Fanizzi, Stefano Ferilli, Marco Gori, Francesca A. Lisi, Pasquale Lops, Donato Malerba, Alessio Micheli, Marcello Pelillo, Francesco Ricci, Fabrizio Riguzzi, Lorenza Saitta, Giovanni Semeraro:
Italian Machine Learning and Data Mining research: The last years. Intelligenza Artificiale 7(2): 77-89 (2013) - [j45]Marco Lippi, Matteo Bertini, Paolo Frasconi:
Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning. IEEE Trans. Intell. Transp. Syst. 14(2): 871-882 (2013) - [c53]Laura Antanas, McElory Hoffmann, Paolo Frasconi, Tinne Tuytelaars, Luc De Raedt:
A relational kernel-based approach to scene classification. WACV 2013: 133-139 - 2012
- [j44]Paolo Frasconi, Francesca A. Lisi:
Guest Editors' introduction - Special issue on inductive logic programming (ILP 2010). Mach. Learn. 86(1): 1-2 (2012) - [j43]Andrea Passerini, Marco Lippi, Paolo Frasconi:
Predicting Metal-Binding Sites from Protein Sequence. IEEE ACM Trans. Comput. Biol. Bioinform. 9(1): 203-213 (2012) - [c52]Mathias Verbeke, Vincent Van Asch, Roser Morante, Paolo Frasconi, Walter Daelemans, Luc De Raedt:
A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories. EMNLP-CoNLL 2012: 579-589 - [c51]Marco Lippi, Andrea Passerini, Marco Punta, Paolo Frasconi:
Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy. ECML/PKDD (2) 2012: 854-857 - [c50]Laura Antanas, Paolo Frasconi, Fabrizio Costa, Tinne Tuytelaars, Luc De Raedt:
A Relational Kernel-Based Framework for Hierarchical Image Understanding. SSPR/SPR 2012: 171-180 - [e5]Luc De Raedt, Christian Bessiere, Didier Dubois, Patrick Doherty, Paolo Frasconi, Fredrik Heintz, Peter J. F. Lucas:
ECAI 2012 - 20th European Conference on Artificial Intelligence. Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track, Montpellier, France, August 27-31 , 2012. Frontiers in Artificial Intelligence and Applications 242, IOS Press 2012, ISBN 978-1-61499-097-0 [contents] - [i3]Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave:
kLog: A Language for Logical and Relational Learning with Kernels. CoRR abs/1205.3981 (2012) - 2011
- [j42]Marco Lippi, Manfred Jaeger, Paolo Frasconi, Andrea Passerini:
Relational information gain. Mach. Learn. 83(2): 219-239 (2011) - [j41]Andrea Passerini, Marco Lippi, Paolo Frasconi:
MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence. Nucleic Acids Res. 39(Web-Server-Issue): 288-292 (2011) - [c49]Parisa Kordjamshidi, Paolo Frasconi, Martijn van Otterlo, Marie-Francine Moens, Luc De Raedt:
Relational Learning for Spatial Relation Extraction from Natural Language. ILP 2011: 204-220 - [c48]Mathias Verbeke, Paolo Frasconi, Vincent Van Asch, Roser Morante, Walter Daelemans, Luc De Raedt:
Kernel-Based Logical and Relational Learning with kLog for Hedge Cue Detection. ILP 2011: 347-357 - [e4]Paolo Frasconi, Francesca A. Lisi:
Inductive Logic Programming - 20th International Conference, ILP 2010, Florence, Italy, June 27-30, 2010. Revised Papers. Lecture Notes in Computer Science 6489, Springer 2011, ISBN 978-3-642-21294-9 [contents] - 2010
- [j40]Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi:
Fast learning of relational kernels. Mach. Learn. 78(3): 305-342 (2010) - [c47]Marco Lippi, Matteo Bertini, Paolo Frasconi:
Collective Traffic Forecasting. ECML/PKDD (2) 2010: 259-273
2000 – 2009
- 2009
- [j39]Marco Lippi, Paolo Frasconi:
Prediction of protein beta-residue contacts by Markov logic networks with grounding-specific weights. Bioinform. 25(18): 2326-2333 (2009) - 2008
- [j38]Fabrizio Costa, Andrea Passerini, Marco Lippi, Paolo Frasconi:
A semiparametric generative model for efficient structured-output supervised learning. Ann. Math. Artif. Intell. 54(1-3): 207-222 (2008) - [j37]Marco Lippi, Andrea Passerini, Marco Punta, Burkhard Rost, Paolo Frasconi:
MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence. Bioinform. 24(18): 2094-2095 (2008) - [j36]Marc Vincent, Andrea Passerini, Matthieu Labbé, Paolo Frasconi:
A simplified approach to disulfide connectivity prediction from protein sequences. BMC Bioinform. 9 (2008) - [c46]Alessandro Vullo, Andrea Passerini, Paolo Frasconi, Fabrizio Costa, Gianluca Pollastri:
On the Convergence of Protein Structure and Dynamics. Statistical Learning Studies of Pseudo Folding Pathways. EvoBIO 2008: 200-211 - [c45]Paolo Frasconi, Manfred Jaeger, Andrea Passerini:
Feature Discovery with Type Extension Trees. ILP 2008: 122-139 - [c44]Paolo Frasconi, Andrea Passerini:
Predicting the Geometry of Metal Binding Sites from Protein Sequence. NIPS 2008: 465-472 - [p2]Paolo Frasconi, Andrea Passerini:
Learning with Kernels and Logical Representations. Probabilistic Inductive Logic Programming 2008: 56-91 - [e3]Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen H. Muggleton:
Probabilistic Inductive Logic Programming - Theory and Applications. Lecture Notes in Computer Science 4911, Springer 2008, ISBN 978-3-540-78651-1 [contents] - 2007
- [j35]Alessio Ceroni, Fabrizio Costa, Paolo Frasconi:
Classification of small molecules by two- and three-dimensional decomposition kernels. Bioinform. 23(16): 2038-2045 (2007) - [j34]Andrea Passerini, Claudia Andreini, Sauro Menchetti, Antonio Rosato, Paolo Frasconi:
Predicting zinc binding at the proteome level. BMC Bioinform. 8 (2007) - [c43]Paolo Frasconi:
Learning with Kernels and Logical Representations. ILP 2007: 1-3 - [p1]Fabrizio Costa, Sauro Menchetti, Paolo Frasconi:
Comparing Sequence Classification Algorithms for Protein Subcellular Localization. Perspectives of Neural-Symbolic Integration 2007: 23-48 - [e2]Paolo Frasconi, Kristian Kersting, Koji Tsuda:
Mining and Learning with Graphs, MLG 2007, Firence, Italy, August 1-3, 2007, Proceedings. 2007 [contents] - 2006
- [j33]Paolo Frasconi, Alessandro Sperduti, Antonina Starita:
Kernel Machines, Neural Networks, and Graphical Models. Intelligenza Artificiale 3(1-2): 72-78 (2006) - [j32]Gianluca Pollastri, Alessandro Vullo, Paolo Frasconi, Pierre Baldi:
Modular DAG-RNN Architectures for Assembling Coarse Protein Structures. J. Comput. Biol. 13(3): 631-650 (2006) - [j31]Andrea Passerini, Paolo Frasconi, Luc De Raedt:
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. J. Mach. Learn. Res. 7: 307-342 (2006) - [j30]Alessio Ceroni, Andrea Passerini, Alessandro Vullo, Paolo Frasconi:
DISULFIND: a disulfide bonding state and cysteine connectivity prediction server. Nucleic Acids Res. 34(Web-Server-Issue): 177-181 (2006) - [c42]Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi:
kFOIL: Learning Simple Relational Kernels. AAAI 2006: 389-394 - [c41]Fabrizio Costa, Sauro Menchetti, Alessio Ceroni, Andrea Passerini, Paolo Frasconi:
Decomposition Kernels for Natural Language Processing. Learning Structured Information@EACL 2006 - [c40]Sauro Menchetti, Andrea Passerini, Paolo Frasconi, Claudia Andreini, Antonio Rosato:
Improving Prediction of Zinc Binding Sites by Modeling the Linkage Between Residues Close in Sequence. RECOMB 2006: 309-320 - 2005
- [j29]Alessio Ceroni, Paolo Frasconi, Gianluca Pollastri:
Learning protein secondary structure from sequential and relational data. Neural Networks 18(8): 1029-1039 (2005) - [j28]Sauro Menchetti, Fabrizio Costa, Paolo Frasconi, Massimiliano Pontil:
Wide coverage natural language processing using kernel methods and neural networks for structured data. Pattern Recognit. Lett. 26(12): 1896-1906 (2005) - [j27]Fabrizio Costa, Paolo Frasconi, Vincenzo Lombardo, Patrick Sturt, Giovanni Soda:
Ambiguity resolution analysis in incremental parsing of natural language. IEEE Trans. Neural Networks 16(4): 959-971 (2005) - [c39]Andrea Passerini, Paolo Frasconi, Luc De Raedt:
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. AAIP 2005: 37-48 - [c38]Sauro Menchetti, Fabrizio Costa, Paolo Frasconi:
Weighted decomposition kernels. ICML 2005: 585-592 - [c37]Andrea Passerini, Paolo Frasconi:
Kernels on Prolog Ground Terms. IJCAI 2005: 1626-1627 - [i2]Andrea Passerini, Paolo Frasconi, Luc De Raedt:
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. Probabilistic, Logical and Relational Learning 2005 - 2004
- [j26]Alessandro Vullo, Paolo Frasconi:
Disulfide connectivity prediction using recursive neural networks and evolutionary information. Bioinform. 20(5): 653-659 (2004) - [j25]Andrea Passerini, Massimiliano Pontil, Paolo Frasconi:
New results on error correcting output codes of kernel machines. IEEE Trans. Neural Networks 15(1): 45-54 (2004) - [j24]Gary William Flake, Paolo Frasconi, C. Lee Giles, Marco Maggini:
Guest editorial: Machine learning for the Internet. ACM Trans. Internet Techn. 4(2): 125-128 (2004) - [j23]Gary William Flake, Paolo Frasconi, C. Lee Giles, Marco Maggini:
Guest editorial: Machine learning for the Internet. ACM Trans. Internet Techn. 4(4): 341-343 (2004) - [c36]Alessio Ceroni, Paolo Frasconi, Alessandro Vullo:
Protein Structure Assembly from Knowledge of β -Sheet Motifs and Secondary Structure. WIRN 2004: 45-52 - [c35]Fabrizio Costa, Paolo Frasconi:
Distributed community crawling. WWW (Alternate Track Papers & Posters) 2004: 362-363 - 2003
- [b1]Pierre Baldi, Paolo Frasconi, Padhraic Smyth:
Modeling the Internet and the Web: Probabilistic Method and Algorithms. John Wiley 2003, ISBN 0-470-84906-1 - [j22]Fabrizio Costa, Paolo Frasconi, Vincenzo Lombardo, Giovanni Soda:
Towards Incremental Parsing of Natural Language Using Recursive Neural Networks. Appl. Intell. 19(1-2): 9-25 (2003) - [j21]Alessandro Vullo, Paolo Frasconi:
Prediction of Protein Coarse Contact Maps. J. Bioinform. Comput. Biol. 1(2): 411-431 (2003) - [j20]Michelangelo Diligenti, Paolo Frasconi, Marco Gori:
Hidden Tree Markov Models for Document Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 25(4): 519-523 (2003) - [j19]Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil, Paolo Frasconi, Fabio Roli:
Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines. Pattern Recognit. 36(2): 397-406 (2003) - [j18]Alessio Ceroni, Paolo Frasconi, Andrea Passerini, Alessandro Vullo:
Predicting the Disulfide Bonding State of Cysteines with Combinations of Kernel Machines. J. VLSI Signal Process. 35(3): 287-295 (2003) - [c34]Alessio Ceroni, Paolo Frasconi, Andrea Passerini, Alessandro Vullo:
A Combination of Support Vector Machines and Bidirectional Recurrent Neural Networks for Protein Secondary Structure Prediction. AI*IA 2003: 142-153 - [c33]Alessandro Vullo, Paolo Frasconi:
A Recursive Connectionist Approach for Predicting Disulfide Connectivity in Proteins. SAC 2003: 67-71 - 2002
- [j17]Paolo Frasconi, Marco Gori, Franz J. Kurfess, Alessandro Sperduti:
Special issue on integration of symbolic and connectionist systems. Cogn. Syst. Res. 3(2): 121-123 (2002) - [j16]Paolo Frasconi, Giovanni Soda, Alessandro Vullo:
Hidden Markov Models for Text Categorization in Multi-Page Documents. J. Intell. Inf. Syst. 18(2-3): 195-217 (2002) - [c32]Alessandro Vullo, Paolo Frasconi:
A Bi-Recursive Neural Network Architecture for the Prediction of Protein Coarse Contact Maps. CSB 2002: 187-196 - [c31]Andrea Passerini, Massimiliano Pontil, Paolo Frasconi:
From Margins to Probabilities in Multiclass Learning Problems. ECAI 2002: 400-404 - [c30]Fabrizio Costa, Paolo Frasconi, Vincenzo Lombardo, Patrick Sturt, Giovanni Soda:
Enhancing First-Pass Attachment Prediction. ECAI 2002: 508-512 - [c29]Gianluca Pollastri, Pierre Baldi, Alessandro Vullo, Paolo Frasconi:
Prediction of Protein Topologies Using Generalized IOHMMS and RNNs. NIPS 2002: 1449-1456 - [c28]Paolo Frasconi, Andrea Passerini, Alessandro Vullo:
A two-stage SVM architecture for predicting the disulfide bonding state of cysteines. NNSP 2002: 25-34 - 2001
- [c27]Andrea Passerini, Paolo Frasconi, Giovanni Soda:
Evaluation Methods for Focused Crawling. AI*IA 2001: 33-39 - [c26]Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil, Paolo Frasconi, Fabio Roli:
A New Machine Learning Approach to Fingerprint Classification. AI*IA 2001: 57-63 - [c25]Fabrizio Costa, Vincenzo Lombardo, Paolo Frasconi, Giovanni Soda:
Wide Coverage Incremental Parsing by Learning Attachment Preferences. AI*IA 2001: 297-307 - [c24]Gian Luca Marcialis, Fabio Roli, Paolo Frasconi:
Fingerprint Classification by Combination of Flat and Structural Approaches. AVBPA 2001: 241-246 - [c23]Yuan Yao, Paolo Frasconi, Massimiliano Pontil:
Fingerprint Classification with Combinations of Support Vector Machines. AVBPA 2001: 253-258 - [c22]Michelangelo Diligenti, Paolo Frasconi, Marco Gori:
Image Document Categorization Using Hidden Tree Markov Models and Structured Representations. ICAPR 2001: 147-156 - [c21]Paolo Frasconi, Giovanni Soda, Alessandro Vullo:
Text categorization for multi-page documents: a hybrid naive Bayes HMM approach. JCDL 2001: 11-20 - [c20]Pierre Baldi, Søren Brunak, Paolo Frasconi, Gianluca Pollastri, Giovanni Soda:
Bidirectional Dynamics for Protein Secondary Structure Prediction. Sequence Learning 2001: 80-104 - [e1]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
Guest Editors' Introduction: Special Section on Connectionist Models for Learning in Structured Domains. IEEE Trans. Knowl. Data Eng. 13(2): 145-147 (2001) - 2000
- [j15]Piero Cosi, Paolo Frasconi, Marco Gori, Luca Lastrucci, Giovanni Soda:
Competitive radial basis functions training for phone classification. Neurocomputing 34(1-4): 117-129 (2000) - [c19]Marco Gori, Paolo Frasconi, Alessandro Sperduti:
Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations. ECAI 2000: 301-305 - [c18]Fabrizio Costa, Paolo Frasconi, Vincenzo Lombardo, Giovanni Soda:
Learning incremental syntactic structures with recursive neural networks. KES 2000: 458-461
1990 – 1999
- 1999
- [j14]Pierre Baldi, Søren Brunak, Paolo Frasconi, Giovanni Soda, Gianluca Pollastri:
Exploiting the past and the future in protein secondary structure prediction. Bioinform. 15(11): 937-946 (1999) - [j13]Paolo Frasconi, Marco Gori, Giovanni Soda:
Data Categorization Using Decision Trellises. IEEE Trans. Knowl. Data Eng. 11(5): 697-712 (1999) - [c17]Fabrizio Costa, Paolo Frasconi, Giovanni Soda:
A topological transformation for hidden recursive modelsarchitecture networks. ESANN 1999: 51-56 - 1998
- [j12]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
A general framework for adaptive processing of data structures. IEEE Trans. Neural Networks 9(5): 768-786 (1998) - [c16]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
Integration of Graphical Rules with Adaptive Learning of Structured Information. Hybrid Neural Systems 1998: 211-225 - 1997
- [j11]Paolo Frasconi, Marco Gori, Giovanni Soda:
Links between LVQ and Backpropagation. Pattern Recognit. Lett. 18(4): 303-310 (1997) - [c15]Paolo Frasconi, Marco Gori, Marco Maggini, Enrico Martinelli, Giovanni Soda:
Inductive Inference of Tree Automata by Recursive Neural Networks. AI*IA 1997: 36-47 - [c14]Enrico Francesconi, Paolo Frasconi, Marco Gori, Simone Marinai, Jianqing Sheng, Giovanni Soda, Alessandro Sperduti:
Logo Recognition by Recursive Neural Networks. GREC 1997: 104-117 - [c13]Paolo Frasconi, Marco Gori, Stefano Fanelli, Marco Protasi:
Suspiciousness of loading problems. ICNN 1997: 1240-1245 - [c12]Paolo Frasconi, Marco Gori, Alessandro Sperduti:
On the Efficient Classification of Data Structures by Neural Networks. IJCAI 1997: 1066-1071 - [c11]Paolo Frasconi:
An Introduction to Learning Structured Information. Summer School on Neural Networks 1997: 99-120 - 1996
- [j10]Paolo Frasconi, Marco Gori, Marco Maggini, Giovanni Soda:
Representation of Finite State Automata in Recurrent Radial Basis Function Networks. Mach. Learn. 23(1): 5-32 (1996) - [j9]Yoshua Bengio, Paolo Frasconi:
Input-output HMMs for sequence processing. IEEE Trans. Neural Networks 7(5): 1231-1249 (1996) - [j8]Paolo Frasconi, Marco Gori:
Computational capabilities of local-feedback recurrent networks acting as finite-state machines. IEEE Trans. Neural Networks 7(6): 1521-1525 (1996) - [c10]Paolo Frasconi, Marco Gori, Giovanni Soda:
Decision Trellis Models for Tuple Categorization in Databases. SEBD 1996: 347-364 - 1995
- [j7]Yoshua Bengio, Paolo Frasconi:
Diffusion of Context and Credit Information in Markovian Models. J. Artif. Intell. Res. 3: 249-270 (1995) - [j6]Paolo Frasconi, Marco Gori, Giovanni Soda:
Recurrent neural networks and prior knowledge for sequence processing: a constrained nondeterministic approach. Knowl. Based Syst. 8(6): 313-332 (1995) - [j5]Paolo Frasconi, Marco Gori, Marco Maggini, Giovanni Soda:
Unified Integration of Explicit Knowledge and Learning by Example in Recurrent Networks. IEEE Trans. Knowl. Data Eng. 7(2): 340-346 (1995) - [j4]Monica Bianchini, Paolo Frasconi, Marco Gori:
Learning in multilayered networks used as autoassociators. IEEE Trans. Neural Networks 6(2): 512-515 (1995) - [j3]Monica Bianchini, Paolo Frasconi, Marco Gori:
Learning without local minima in radial basis function networks. IEEE Trans. Neural Networks 6(3): 749-756 (1995) - [i1]Yoshua Bengio, Paolo Frasconi:
Diffusion of Context and Credit Information in Markovian Models. CoRR abs/cs/9510101 (1995) - 1994
- [j2]Yoshua Bengio, Patrice Y. Simard, Paolo Frasconi:
Learning long-term dependencies with gradient descent is difficult. IEEE Trans. Neural Networks 5(2): 157-166 (1994) - [c9]Marco Gori, Paolo Frasconi, Marco Maggini, Giovanni Soda:
Inductive Inference of Regular Grammars Using Recurrent Networks: A Critical Analysis. ICLP Workshop: Logic and Reasoning with Neural Networks 1994 - [c8]Paolo Frasconi, Yoshua Bengio:
An EM approach to grammatical inference: input/output HMMs. ICPR (2) 1994: 289-294 - [c7]Yoshua Bengio, Paolo Frasconi:
An Input Output HMM Architecture. NIPS 1994: 427-434 - [c6]Yoshua Bengio, Paolo Frasconi:
Diffusion of Credit in Markovian Models. NIPS 1994: 553-560 - 1993
- [c5]Yoshua Bengio, Paolo Frasconi, Patrice Y. Simard:
The problem of learning long-term dependencies in recurrent networks. ICNN 1993: 1183-1188 - [c4]Paolo Frasconi, Marco Gori, Alberto Tesi:
Backpropagation for linearly-separable patterns: A detailed analysis. ICNN 1993: 1818-1822 - [c3]Yoshua Bengio, Paolo Frasconi:
Credit Assignment through Time: Alternatives to Backpropagation. NIPS 1993: 75-82 - 1992
- [j1]Paolo Frasconi, Marco Gori, Giovanni Soda:
Local Feedback Multilayered Networks. Neural Comput. 4(1): 120-130 (1992) - [c2]Piero Cosi, Paolo Frasconi, Marco Gori, N. Griggio:
Phonetic recognition experiments with recurrent neural networks. ICSLP 1992: 1335-1338 - 1991
- [c1]Paolo Frasconi, Marco Gori, Marco Maggini, Giovanni Soda:
KL: A Neural Model for Capturing Structure in Speech. AI*IA 1991: 450-454
Coauthor Index
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