2014 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to neural networks and machine learning models for pattern recognition
2001 - IEEE Fellow For contributions to the theory of recurrent neural networks, and applications of neural network-based technologies.
His main research concerns Artificial intelligence, Artificial neural network, Theoretical computer science, Graph theory and Information retrieval. His studies deal with areas such as Machine learning, Maxima and minima and Pattern recognition as well as Artificial intelligence. His Artificial neural network study typically links adjacent topics like Learning environment.
His Graph theory research incorporates elements of Graph and Graph. His work deals with themes such as Supervised learning and Directed acyclic graph, which intersect with Graph. Marco Gori interconnects Web page, Data mining and Data set in the investigation of issues within Information retrieval.
Marco Gori mostly deals with Artificial intelligence, Artificial neural network, Machine learning, Theoretical computer science and Deep learning. His biological study spans a wide range of topics, including Natural language processing and Pattern recognition. His Artificial neural network research incorporates themes from Directed acyclic graph, Directed graph and Graph.
The concepts of his Theoretical computer science study are interwoven with issues in Graph theory and Graph. His work in Deep learning addresses subjects such as Inference, which are connected to disciplines such as Probabilistic logic. His Backpropagation study combines topics in areas such as Algorithm, Mathematical optimization and Maxima and minima.
The scientist’s investigation covers issues in Artificial intelligence, Deep learning, Artificial neural network, Theoretical computer science and Inference. His Artificial intelligence study combines topics from a wide range of disciplines, such as Scheme and Machine learning. His studies in Deep learning integrate themes in fields like Training set, Convergence, Field, Crowdsourcing and Probabilistic logic.
His work in the fields of Backpropagation overlaps with other areas such as Action. His biological study spans a wide range of topics, including Computational linguistics, Doors, Scheme, Set and Algebraic number. The various areas that Marco Gori examines in his Inference study include Graphical model, Feature, Optimization problem and Model checking.
His primary areas of investigation include Artificial intelligence, Deep learning, Inference, Artificial neural network and Machine learning. His work deals with themes such as Scheme and Cognition, which intersect with Artificial intelligence. His Deep learning study integrates concerns from other disciplines, such as Theoretical computer science, Training set, Natural language processing, Contextual image classification and Cognitive science.
His Theoretical computer science research includes themes of Fragment, Quadratic programming and Kernel. The Artificial neural network study combines topics in areas such as Initialization and Feature extraction. In Supervised learning, Marco Gori works on issues like Graph, which are connected to Logical reasoning.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The Graph Neural Network Model
F. Scarselli;M. Gori;Ah Chung Tsoi;M. Hagenbuchner.
IEEE Transactions on Neural Networks (2009)
Focused Crawling Using Context Graphs
Michelangelo Diligenti;Frans Coetzee;Steve Lawrence;C. Lee Giles.
very large data bases (2000)
On the problem of local minima in backpropagation
M. Gori;A. Tesi.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1992)
A new model for learning in graph domains
M. Gori;G. Monfardini;F. Scarselli.
international joint conference on neural network (2005)
Inside PageRank
Monica Bianchini;Marco Gori;Franco Scarselli.
ACM Transactions on Internet Technology (TOIT) (2005)
A general framework for adaptive processing of data structures
P. Frasconi;M. Gori;A. Sperduti.
IEEE Transactions on Neural Networks (1998)
Learning without local minima in radial basis function networks
M. Bianchini;P. Frasconi;M. Gori.
IEEE Transactions on Neural Networks (1995)
ItemRank: a random-walk based scoring algorithm for recommender engines
Marco Gori;Augusto Pucci.
international joint conference on artificial intelligence (2007)
Local feedback multilayered networks
Paolo Frasconi;Marco Gori;Giovanni Soda.
Neural Computation (1992)
A survey of hybrid ANN/HMM models for automatic speech recognition
Edmondo Trentin;Marco Gori.
Neurocomputing (2001)
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