Paolo Frasconi

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Marco GoriProfessor of Computer Science, University of SienaVerified email at dii.unisi.it
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Massimiliano PontilIstituto Italiano di Tecnologia & University College LondonVerified email at iit.it
Marco LippiUniversity of Modena and Reggio EmiliaVerified email at unimore.it
Pierre BaldiProfessor, University of California, IrvineVerified email at ics.uci.edu
Alessio CeroniSoftware Engineer at Genedata GmbHVerified email at genedata.com
Gianluca PollastriAssociate Professor, University College DublinVerified email at ucd.ie
Juergen SchmidhuberKing Abdullah University of Science and Technology / The Swiss AI Lab, IDSIA / University of LuganoVerified email at kaust.edu.sa
Padhraic SmythProfessor, Computer Science, University of California IrvineVerified email at ics.uci.edu
Søren BrunakProfessor of Disease Systems Biology, University of CopenhagenVerified email at cpr.ku.dk
Burkhard RostProfessor of Computer Science & Computational Biology & Bioinformatics, TUM, MunichVerified email at tum.de
Fabio RoliProfessor, University of Genova, ItalyVerified email at unige.it
Niels LandwehrProfessor, University of HildesheimVerified email at uni-hildesheim.de
Stephen MuggletonImperial College LondonVerified email at imperial.ac.uk
Antonio RosatoUniversity of FlorenceVerified email at cerm.unifi.it
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de

Paolo Frasconi

Professor of Computer Science, Università di Firenze

Verified email at dsi.unifi.it - Homepage

Machine Learning Neural Networks Relational Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learning long-term dependencies with gradient descent is difficult Y Bengio, P Simard, P Frasconi IEEE transactions on neural networks 5 (2), 157-166, 1994	10676	1994
Gradient flow in recurrent nets: the difficulty of learning long-term dependencies S Hochreiter, Y Bengio, P Frasconi, J Schmidhuber A field guide to dynamical recurrent neural networks. IEEE Press, 2001	2341	2001
Exploiting the past and the future in protein secondary structure prediction P Baldi, S Brunak, P Frasconi, G Soda, G Pollastri Bioinformatics 15 (11), 937-946, 1999	650	1999
Short-term traffic flow forecasting: An experimental comparison of time-series analysis and supervised learning M Lippi, M Bertini, P Frasconi IEEE Transactions on Intelligent Transportation Systems 14 (2), 871-882, 2013	641	2013
A general framework for adaptive processing of data structures P Frasconi, M Gori, A Sperduti IEEE transactions on Neural Networks 9 (5), 768-786, 1998	599	1998
Bilevel programming for hyperparameter optimization and meta-learning L Franceschi, P Frasconi, S Salzo, R Grazzi, M Pontil International Conference on Machine Learning, 1568-1577, 2018	527	2018
An input output HMM architecture Y Bengio, P Frasconi Advances in neural information processing systems 7, 1994	510	1994
Modeling the Internet and the Web P Baldi, P Frasconi, P Smyth Wiley, 2003	499	2003
Input-output HMMs for sequence processing Y Bengio, P Frasconi IEEE Transactions on Neural Networks 7 (5), 1231-1249, 1996	430	1996
DISULFIND: a disulfide bonding state and cysteine connectivity prediction server A Ceroni, A Passerini, A Vullo, P Frasconi Nucleic acids research 34 (suppl_2), W177-W181, 2006	404	2006
Learning without local minima in radial basis function networks M Bianchini, P Frasconi, M Gori IEEE transactions on neural networks 6 (3), 749-756, 1995	387	1995
The problem of learning long-term dependencies in recurrent networks Y Bengio, P Frasconi, P Simard IEEE international conference on neural networks, 1183-1188, 1993	329	1993
Forward and reverse gradient-based hyperparameter optimization L Franceschi, M Donini, P Frasconi, M Pontil International Conference on Machine Learning, 1165-1173, 2017	315	2017
Local feedback multilayered networks P Frasconi, M Gori, G Soda Neural computation 4 (1), 120-130, 1992	276	1992
Disulfide connectivity prediction using recursive neural networks and evolutionary information A Vullo, P Frasconi Bioinformatics 20 (5), 653-659, 2004	199	2004
New results on error correcting output codes of kernel machines A Passerini, M Pontil, P Frasconi IEEE transactions on neural networks 15 (1), 45-54, 2004	196	2004
Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines Y Yao, GL Marcialis, M Pontil, P Frasconi, F Roli Pattern Recognition 36 (2), 397-406, 2003	158	2003
Hidden tree Markov models for document image classification M Diligenti, P Frasconi, M Gori IEEE Transactions on pattern analysis and machine intelligence 25 (4), 519-523, 2003	154	2003
Representation of finite state automata in recurrent radial basis function networks P Frasconi, M Gori, M Maggini, G Soda Machine Learning 23, 5-32, 1996	142	1996
kFOIL: Learning simple relational kernels N Landwehr, A Passerini, L De Raedt, P Frasconi Aaai 6, 389-394, 2006	137	2006

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