P. Frasconi

Yoshua Bengio, Paolo Frasconi, Yoshua Bengio, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

Modular DAG-RNN Architectures for Assembling Coarse Protein Structures

Pierre Baldi, Paolo Frasconi, Alessandro Vullo, 2006, J. Comput. Biol..

Ambiguity resolution in incremental parsing of natural language

P. Frasconi, G. Soda, P. Sturt, 2003 .

Input / Output HMMs : A RecurrentBayesian Network

P. Frasconi, 2007 .

YPERPARAMETER O PTIMIZATION IN L EARNING S YSTEMS

P. Frasconi, M. Pontil, Luca Franceschi, 2017 .

Identifying cysteines and histidines in transition‐metal‐binding sites using support vector machines and neural networks

B. Rost, P. Frasconi, Andrea Passerini, 2006, Proteins.

Chapter 16. Insertion of Prior Knowledge

C. Lee Giles, P. Frasconi, M. Gori, 2001 .

An unified approach for integrating explicit knowledge and learning by example in recurrent networks

Giovanni Soda, Paolo Frasconi, Marco Gori, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Predicting zinc binding at the proteome level

P. Frasconi, A. Rosato, S. Menchetti, 2007, BMC Bioinformatics.

Whole-Brain Vasculature Reconstruction at the Single Capillary Level

A. L. Allegra Mascaro, A. P. Di Giovanna, P. Frasconi, 2017, Scientific Reports.

Data and text mining RNAcommender : genome-wide recommendation of RNA – protein interactions

P. Frasconi, Fabrizio Costa, T. Tebaldi, 2016 .

Characterization of metalloproteins by high-throughput X-ray absorption spectroscopy.

Paolo Frasconi, Marco Punta, Andrea Passerini, 2011, Genome research.

Appendix A: Mathematical Complements

P. Baldi, Padhraic Smyth, P. Frasconi, 2003 .

Executable logic for dialogical argumentation

P. Frasconi, L. D. Raedt, F. Heintz, 2012 .

Representation of Finite State Automata in Recurrent Radial Basis Function Networks

P. Frasconi, M. Gori, Marco Maggini, 1996, Machine Learning.

Local Feedback Multi-Layered Networks

P. Frasconi, M. Gori, G. Soda, 1992 .

absorption spectroscopy Characterization of metalloproteins by high-throughput X-ray Material

B. Rost, P. Frasconi, J. M. Sauder, 2011 .

Classification of Cancer Pathology Reports: A Large-Scale Comparative Study

Paolo Frasconi, Stefano Martina, Leonardo Ventura, 2020, IEEE Journal of Biomedical and Health Informatics.

Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines RID G-2944-2010

Gian Luca Marcialis, Fabio Roli, Paolo Frasconi, 2003 .

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016

Paolo Frasconi, Jilles Vreeken, Giuseppe Manco, 2016 .

ECAI 2002: 15th European conference on artificial intelligence

Giovanni Soda, Paolo Frasconi, Patrick Sturt, 2002 .

Special issue on connectionist models for learning in structured domains

Paolo Frasconi, P. Frasconi, 2001 .

Kernel Machines, Neural Networks, and Graphical Models

Alessandro Sperduti, Paolo Frasconi, Antonina Starita, 2006, Intelligenza Artificiale.

Proof Tree Kernels : a Candidate Ingredient for Intelligent Optimization

P. Frasconi, Andrea Passerini, 2007 .

Model Revision from Temporal Logic Properties in Computational Systems Biology

S. Muggleton, P. Frasconi, K. Kersting, 2019 .

Brain-wide charting of neuronal activation maps with cellular resolution

P. Frasconi, B. Hyman, F. Pavone, 2015 .

Optimal learning in artificial neural networks: A theoretical view

Paolo Frasconi, Marco Gori, Marco Maggini, 1998 .

Guest Editors' Introduction: Special Section on Connectionist Models for Learning in Structured Domains

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 2001, IEEE Trans. Knowl. Data Eng..

Suspiciousness of loading problems

P. Frasconi, M. Gori, M. Protasi, 1996, Proceedings of IEEE 5th International Fuzzy Systems.

Hidden Tree Markov Models for Image Document Classification

Paolo Frasconi, Marco Gori, Michelangelo Diligenti, 2003 .

Phonetic recognition experiments with recurrent neural networks

Piero Cosi, Paolo Frasconi, Marco Gori, 1992, ICSLP.

Commerce on the Web: Models and Applications

Pierre Baldi, Paolo Frasconi, Padhraic Smyth, 2003 .

Marthe: Scheduling the Learning Rate Via Online Hypergradients

Paolo Frasconi, Massimiliano Pontil, Luca Franceschi, 2019, IJCAI.

Learning Type Extension Trees for Metal Bonding State Prediction

P. Frasconi, M. Jaeger, Andrea Passerini, 2008 .

On Hyperparameter Optimization in Learning Systems

Paolo Frasconi, Massimiliano Pontil, Luca Franceschi, 2017, ICLR.

Proceedings of the 20th European Conference on Artificial Intelligence

Luc De Raedt, Didier Dubois, Christian Bessiere, 2012 .

Neural Networks and Kernel Machines for Vector and Structured Data

Paolo Frasconi, P. Frasconi, 2005 .

Advanced Crawling Techniques

Pierre Baldi, Paolo Frasconi, Padhraic Smyth, 2003 .

Predicting zinc binding at the proteome level

P. Frasconi, A. Rosato, S. Menchetti, 2007, BMC Bioinformatics.

Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2016)

Paolo Frasconi, Jilles Vreeken, Giuseppe Manco, 2016 .

Learning with Kernels and Logical Representations

Paolo Frasconi, Andrea Passerini, P. Frasconi, 2007, Probabilistic Inductive Logic Programming.

Learning first-pass structural attachment preferences with dynamic grammars and recursive neural networks

P. Frasconi, P. Sturt, V. Lombardo, 2003, Cognition.

Modeling and Understanding Human Behavior on the Web

Pierre Baldi, Paolo Frasconi, Padhraic Smyth, 2003 .

RNA secondary structure prediction by mapping Zuker ’ s algorithm into Markov logic

P. Frasconi, Marco Lippi, L. Popenda, 2009 .

Learning and Interpreting Multi-Multi-Instance Learning Networks

P. Frasconi, M. Jaeger, Alessandro Tibo, 2018, J. Mach. Learn. Res..

A Network Architecture for Multi-Multi-Instance Learning

Paolo Frasconi, Manfred Jaeger, Alessandro Tibo, 2017, ECML/PKDD.

Shift Aggregate Extract Networks

Paolo Frasconi, Francesco Orsini, Daniele Baracchi, 2017, Front. Robot. AI.

Type Extension Trees for feature construction and learning in relational domains

Paolo Frasconi, Andrea Passerini, Manfred Jaeger, 2013, Artif. Intell..

Italian Machine Learning and Data Mining research: The last years

Fabrizio Riguzzi, Donato Malerba, Davide Bacciu, 2013, Intelligenza Artificiale.

Fast learning of relational kernels

Luc De Raedt, Paolo Frasconi, Andrea Passerini, 2010, Machine Learning.

Prediction of protein beta-residue contacts by Markov logic networks with grounding-specific weights

Paolo Frasconi, Marco Lippi, P. Frasconi, 2009, Bioinform..

Representation of finite state automata in Recurrent Radial Basis Function networks

Giovanni Soda, Paolo Frasconi, Marco Gori, 2004, Machine Learning.

Injecting Nondeterministic Finite State Automata into RecurrentNeural NetworksPaolo

P. Frasconi, M. Gori, G. Soda, 1993 .

Bidirectional IOHMMs and Recurrent Neural Networks for Protein Secondary Structure Prediction

Paolo Frasconi, Gianluca Pollastri, Søren Brunak, 2000 .

Bilevel Programming for Hyperparameter Optimization and Meta-Learning pdf

Paolo Frasconi, Massimiliano Pontil, Luca Franceschi, 2018, ICML.

Towards Incremental Parsing of Natural Language Using Recursive Neural Networks

Giovanni Soda, Paolo Frasconi, Vincenzo Lombardo, 2003, Applied Intelligence.

Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines

Yuan Yao, Gian Luca Marcialis, Fabio Roli, 2003, Pattern Recognit..

Special issue on integration of symbolic and connectionist systems

Franz J. Kurfess, Alessandro Sperduti, Paolo Frasconi, 2002, Cognitive Systems Research.

Learning incremental syntactic structures with recursive neural networks

Giovanni Soda, Paolo Frasconi, Vincenzo Lombardo, 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).

Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 2000, ECAI.

Integration of Graphical Rules with Adaptive Learning of Structured Information

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 1998, Hybrid Neural Systems.

An Introduction to Learning Structured Information

Paolo Frasconi, P. Frasconi, 1997, Summer School on Neural Networks.

On the Efficient Classification of Data Structures by Neural Networks

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 1997, IJCAI.

Ambiguity resolution analysis in incremental parsing of natural language

Giovanni Soda, Paolo Frasconi, Vincenzo Lombardo, 2005, IEEE Transactions on Neural Networks.

Relational information gain

Paolo Frasconi, Andrea Passerini, Manfred Jaeger, 2011, Machine Learning.

Learning with Kernels and Logical Representations

Paolo Frasconi, P. Frasconi, Andrea Passerini, 2007, Probabilistic Inductive Logic Programming.

Learning to discriminate between ligand-bound and disulfide-bound cysteines.

Paolo Frasconi, Andrea Passerini, P. Frasconi, 2004, Protein engineering, design & selection : PEDS.

New results on error correcting output codes of kernel machines

Paolo Frasconi, Andrea Passerini, Massimiliano Pontil, 2004, IEEE Transactions on Neural Networks.

A recursive connectionist approach for predicting disulfide connectivity in proteins

Paolo Frasconi, Alessandro Vullo, P. Frasconi, 2003, SAC '03.

Modeling the Internet and the Web: Probabilistic Method and Algorithms

Pierre Baldi, Paolo Frasconi, Padhraic Smyth, 2002 .

Mining and Learning with Graphs, MLG 2007, Firence, Italy, August 1-3, 2007, Proceedings

Kristian Kersting, Paolo Frasconi, Koji Tsuda, 2007, Mining and Learning with Graphs.

Modeling the Internet and the Web: Probabilistic Method and Algorithms

Pierre Baldi, Paolo Frasconi, Padhraic Smyth, 2003 .

DISULFIND: a disulfide bonding state and cysteine connectivity prediction server

Alessio Ceroni, Paolo Frasconi, Andrea Passerini, 2006, Nucleic Acids Res..

International Program Committee/Local Organizing Committee/Sponsors

Italy, P. Frasconi, L. Milanesi, 2013 .

Merit Award Winners

Paolo Frasconi, Andrea Passerini, Antonio Rosato, 2004, BMC Bioinformatics.

Whole-Brain Vasculature Reconstruction at the Single Capillary Level

A. L. Allegra Mascaro, A. P. Di Giovanna, P. Frasconi, 2017, bioRxiv.

A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories

Roser Morante, Luc De Raedt, Walter Daelemans, 2012, EMNLP.

Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting

Luc De Raedt, Paolo Frasconi, Andrea Passerini, 2006, J. Mach. Learn. Res..

Machine Learning and Knowledge Discovery in Databases

Paolo Frasconi, Jilles Vreeken, Niels Landwehr, 2016, Lecture Notes in Computer Science.

Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning

Paolo Frasconi, Marco Lippi, Matteo Bertini, 2013, IEEE Transactions on Intelligent Transportation Systems.

Data Categorization Using Decision Trellises

G. Soda, P. Frasconi, M. Gori, 1999, IEEE Trans. Knowl. Data Eng..

Decision Trellis Models for Tuple Categorization in Databases

Giovanni Soda, Paolo Frasconi, Marco Gori, 1996, SEBD.

Markov Logic Networks for Optical Chemical Structure Recognition

Paolo Frasconi, Marco Lippi, Simone Marinai, 2014, J. Chem. Inf. Model..

Hidden Tree Markov Models for Document Image Classification

Paolo Frasconi, Marco Gori, Michelangelo Diligenti, 2003, IEEE Trans. Pattern Anal. Mach. Intell..

Statistical Learning and Kernel Methods in Bioinformatics

Isabelle Guyon, Bernhard Schölkopf, Jason Weston, 2003 .

Links between LVQ and Backpropagation

Giovanni Soda, Paolo Frasconi, Marco Gori, 1997, Pattern Recognit. Lett..

A Bridge Between Hyperparameter Optimization and Larning-to-learn pdf

Paolo Frasconi, Massimiliano Pontil, Luca Franceschi, 2017, ArXiv.

Probabilistic Inductive Logic Programming - Theory and Applications

Luc De Raedt, Kristian Kersting, Stephen Muggleton, 2008, Probabilistic Inductive Logic Programming.

Kernel-Based Logical and Relational Learning with kLog for Hedge Cue Detection

Roser Morante, Luc De Raedt, Walter Daelemans, 2011, ILP.

Declarative Kernels

Stephen Muggleton, Paolo Frasconi, Andrea Passerini, 2004 .

Quantitative neuroanatomy of all Purkinje cells with light sheet microscopy and high-throughput image analysis

P. Frasconi, G. Iannello, F. Pavone, 2015, Front. Neuroanat..

Large-scale automated identification of mouse brain cells in confocal light sheet microscopy images

Paolo Frasconi, Giulio Iannello, Ludovico Silvestri, 2014, Bioinform..

A HPC infrastructure for processing and visualizing neuro-anatomical images obtained by Confocal Light Sheet Microscopy

Paolo Frasconi, Hanchuan Peng, Giulio Iannello, 2014, 2014 International Conference on High Performance Computing & Simulation (HPCS).

Optimal staining and clearing protocol for whole mouse brain vasculature imaging with light-sheet microscopy

Paolo Frasconi, Francesco Saverio Pavone, Ludovico Silvestri, 2017, European Conference on Biomedical Optics.

Universal autofocus for quantitative volumetric microscopy of whole mouse brains

A. P. Di Giovanna, P. Frasconi, A. Kreshuk, 2021, Nature Methods.

kProbLog: an algebraic Prolog for machine learning

Luc De Raedt, Paolo Frasconi, Francesco Orsini, 2017, Machine Learning.

kFOIL: Learning Simple Relational Kernels

Luc De Raedt, Paolo Frasconi, Andrea Passerini, 2006, AAAI.

Software Tools for Efficient Processing of High-Resolution 3D Images of Macroscopic Brain Samples

Francesco S. Pavone, Paolo Frasconi, Ludovico Silvestri, 2018 .

Collective Traffic Forecasting

Paolo Frasconi, Marco Lippi, Matteo Bertini, 2010, ECML/PKDD.

MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence

Paolo Frasconi, Andrea Passerini, P. Frasconi, 2011, Nucleic Acids Res..

KL: A Neural Model for Capturing Structure in Speech

Giovanni Soda, Paolo Frasconi, Marco Gori, 1991, AI*IA.

Computer-based automatic identification of neurons in gigavoxel-sized 3D human brain images

Paolo Frasconi, Giulio Iannello, Irene Costantini, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Learning Structured Outputs via Kernel Dependency Estimation and Stochastic Grammars

P. Frasconi, Andrea Passerini, Fabrizio Costa, 2006 .

Pattern-Based Music Generation with Wasserstein Autoencoders and PRC Descriptions

Paolo Frasconi, Luca Angioloni, Valentijn Borghuis, 2020, IJCAI.

MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence

Burkhard Rost, Paolo Frasconi, Andrea Passerini, 2008, Bioinform..

A simplified approach to disulfide connectivity prediction from protein sequences

Paolo Frasconi, Andrea Passerini, Marc Vincent, 2008, BMC Bioinformatics.

Improving Prediction of Zinc Binding Sites by Modeling the Linkage Between Residues Close in Sequence

Paolo Frasconi, Andrea Passerini, Antonio Rosato, 2006, RECOMB.

Predicting the Disulfide Bonding State of Cysteines with Combinations of Kernel Machines

Alessio Ceroni, Paolo Frasconi, Andrea Passerini, 2003, J. VLSI Signal Process..

A Combination of Support Vector Machines and Bidirectional Recurrent Neural Networks for Protein Secondary Structure Prediction

Alessio Ceroni, Paolo Frasconi, Andrea Passerini, 2003, AI*IA.

A two-stage SVM architecture for predicting the disulfide bonding state of cysteines

Paolo Frasconi, Andrea Passerini, Alessandro Vullo, 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

From Margins to Probabilities in Multiclass Learning Problems

Paolo Frasconi, Andrea Passerini, Massimiliano Pontil, 2002, ECAI.

On Tuning Hyper-Parameters of Multiclass Margin Classifiers

Paolo Frasconi, Andrea Passerini, Massimiliano Pontil, 2002 .

Hidden Markov Models for Text Categorization in Multi-Page Documents

Giovanni Soda, Paolo Frasconi, Alessandro Vullo, 2002, Journal of Intelligent Information Systems.

Learning without local minima in radial basis function networks

Paolo Frasconi, Marco Gori, Monica Bianchini, 1995, IEEE Trans. Neural Networks.

Graph Invariant Kernels

Luc De Raedt, Paolo Frasconi, Francesco Orsini, 2015, IJCAI.

RNAcommender: genome-wide recommendation of RNA-protein interactions

Paolo Frasconi, Andrea Passerini, Fabrizio Costa, 2016, Bioinform..

kProbLog: An Algebraic Prolog for Kernel Programming

Luc De Raedt, Paolo Frasconi, Francesco Orsini, 2015, ILP.

kLogNLP: Graph Kernel–based Relational Learning of Natural Language

Luc De Raedt, Paolo Frasconi, Fabrizio Costa, 2014, ACL.

A relational kernel-based approach to scene classification

Luc De Raedt, Paolo Frasconi, Tinne Tuytelaars, 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

A Relational Kernel-Based Framework for Hierarchical Image Understanding

Luc De Raedt, Paolo Frasconi, Tinne Tuytelaars, 2012, SSPR/SPR.

Employing logical languages for image understanding

Luc De Raedt, Paolo Frasconi, Tinne Tuytelaars, 2011 .

Spatial relation extraction using relational learning

Luc De Raedt, Marie-Francine Moens, Parisa Kordjamshidi, 2011, ILP 2011.

Feature Discovery with Type Extension Trees

Paolo Frasconi, Andrea Passerini, Manfred Jaeger, 2008, ILP.

Learning in multilayered networks used as autoassociators

Paolo Frasconi, Marco Gori, Monica Bianchini, 1995, IEEE Trans. Neural Networks.

Backpropagation for linearly-separable patterns: A detailed analysis

Paolo Frasconi, Alberto Tesi, Marco Gori, 1993, IEEE International Conference on Neural Networks.

Predicting Metal-Binding Sites from Protein Sequence

Paolo Frasconi, Andrea Passerini, Marco Lippi, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1 Short-Term Traffic Flow Forecasting: An Experimental

P. Frasconi, Marco Lippi, Matteo Bertini, 2022 .

Marthe: Scheduling the Learning Rate Via Online Hypergradients

Paolo Frasconi, Massimiliano Pontil, Luca Franceschi, 2019, IJCAI.

CONLON: A Pseudo-Song Generator Based on a New Pianoroll, Wasserstein Autoencoders, and Optimal Interpolations

Paolo Frasconi, Luca Angioloni, Valentijn Borghuis, 2020, ISMIR.

Off the Beaten Track: Using Deep Learning to Interpolate Between Music Genres pdf

Paolo Frasconi, Tijn Borghuis, Lorenzo Brusci, 2018, ArXiv.

Full-Band Music Genres Interpolations with Wasserstein Autoencoders

P. Frasconi, Alessandro Tibo, L. Brusci, 2019 .

Modeling the Internet and the Web: Probabilistic Methods and Algorithms: Baldi/Probabilistic

Pierre Baldi, Paolo Frasconi, Padhraic Smyth, 2002 .

Diffusion of Credit in Markovian Models

Yoshua Bengio, Paolo Frasconi, Yoshua Bengio, 1994, NIPS.

Classification of Cancer Pathology Reports: A Large-Scale Comparative Study

P. Frasconi, L. Ventura, S. Martina, 2020, IEEE Journal of Biomedical and Health Informatics.

A semiparametric generative model for efficient structured-output supervised learning

Paolo Frasconi, Andrea Passerini, Marco Lippi, 2008, Annals of Mathematics and Artificial Intelligence.

An Input Output HMM Architecture

Yoshua Bengio, P. Frasconi, 1994, NIPS.

Image Document Categorization Using Hidden Tree Markov Models and Structured Representations

Paolo Frasconi, Marco Gori, Michelangelo Diligenti, 2001, ICAPR.

Text categorization for multi-page documents: a hybrid naive Bayes HMM approach

Giovanni Soda, Paolo Frasconi, Alessandro Vullo, 2001, JCDL '01.

Learning Structured Information in Natural Language Applications

Carlo Strapparava, Walter Daelemans, Alessandro Moschitti, 2006 .

Fingerprint Classification with Combinations of Support Vector Machines

Yuan Yao, Paolo Frasconi, Massimiliano Pontil, 2001, AVBPA.

New Machine Learning Methods for the Prediction of Protein Topologies

Paolo Frasconi, Alessandro Vullo, Gianluca Pollastri, 2002 .

Inductive Inference of Tree Automata by Recursive Neural Networks

Giovanni Soda, Paolo Frasconi, Marco Gori, 1997, AI*IA.

Ambiguity resolution in incremental parsing of natural language

P. Frasconi, G. Soda, P. Sturt, 2003 .

Hidden Recursive Models

Alessandro Sperduti, Paolo Frasconi, Marco Gori, 1998 .

Scheduling the Learning Rate via Hypergradients: New Insights and a New Algorithm

P. Frasconi, M. Pontil, Luca Franceschi, 2019, ArXiv.

Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning pdf

Paolo Frasconi, Massimiliano Pontil, Riccardo Grazzi, 2018, ArXiv.

Recurrent neural networks and prior knowledge for sequence processing: a constrained nondeterministic approach

Giovanni Soda, Paolo Frasconi, Marco Gori, 1995, Knowl. Based Syst..

An Input Output HMM Architecture

Yoshua, Yoshua Bengio, P. Frasconi, 1994, Neural Information Processing Systems.

Learning protein secondary structure from sequential and relational data

Alessio Ceroni, Paolo Frasconi, Gianluca Pollastri, 2005, Neural Networks.

Wide coverage natural language processing using kernel methods and neural networks for structured data

Paolo Frasconi, Massimiliano Pontil, Fabrizio Costa, 2005, Pattern Recognit. Lett..

Comparing Convolution Kernels and Recursive Neural Networks for Learning Preferences on Structured Data

Paolo Frasconi, Massimiliano Pontil, Fabrizio Costa, 2003 .

Enhancing First-Pass Attachment Prediction

Giovanni Soda, Paolo Frasconi, Vincenzo Lombardo, 2002, ECAI.

Wide Coverage Incremental Parsing by Learning Attachment Preferences

Giovanni Soda, Paolo Frasconi, Vincenzo Lombardo, 2001, AI*IA.

Learning to Rank Structured Alternatives: An Application to Incremental Processing of Natural Language

Giovanni Soda, Paolo Frasconi, Vincenzo Lombardo, 2000, ICML 2000.

Logo Recognition by Recursive Neural Networks

P. Frasconi, M. Gori, G. Soda, 1997, GREC.

Computational capabilities of local-feedback recurrent networks acting as finite-state machines

Paolo Frasconi, Marco Gori, P. Frasconi, 1996, IEEE Trans. Neural Networks.

A bi-recursive neural network architecture for the prediction of protein coarse contact maps

Paolo Frasconi, Alessandro Vullo, P. Frasconi, 2002, Proceedings. IEEE Computer Society Bioinformatics Conference.

Representation of Finite State Automata inRecurrent Radial Basis Function NetworksPAOLO

P. Frasconi, 1996 .

Markov Logic Networks for Optical Chemical Structure Recognition

P. Frasconi, Marco Lippi, S. Marinai, 2014, J. Chem. Inf. Model..

Sound Generation via Cross-Modal Transcoding

P. Frasconi, Alessandro Tibo, Tibo, 2015 .

DAPHNE: DATA PARALLELISM NEURAL NETWORK SIMULATOR

Giovanni Soda, Paolo Frasconi, Marco Gori, 1993 .