Edmondo Trentin

Edmondo Trentin, Ernesto Di Iorio, E. Trentin, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A Maximum-Likelihood Connectionist Model for Unsupervised Learning over Graphical Domains

Edmondo Trentin, Leonardo Rigutini, 2009, ICANN.

Semi-unsupervised Weighted Maximum-Likelihood Estimation of Joint Densities for the Co-training of Adaptive Activation Functions

Edmondo Trentin, Ilaria Castelli, E. Trentin, 2011, PSL.

The regularized SNN-TA model for recognition of noisy speech

Marco Matassoni, Edmondo Trentin, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Combining Neural Networks and Hidden Markov Models for Speech Recognition

Marco Gori, Edmondo Trentin, E. Trentin, 1999 .

Inversion-based nonlinear adaptation of noisy acoustic parameters for a neural/HMM speech recognizer

Marco Gori, Edmondo Trentin, E. Trentin, 2006, Neurocomputing.

Soft-Constrained Nonparametric Density Estimation with Artificial Neural Networks

Edmondo Trentin, E. Trentin, 2016, ANNPR.

Robust combination of neural networks and hidden Markov models for speech recognition

Marco Gori, Edmondo Trentin, E. Trentin, 2003, IEEE Trans. Neural Networks.

Recognition of Sequences of Graphical Patterns

Markus Hagenbuchner, Shujia Zhang, Edmondo Trentin, 2010, ANNPR.

Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology

Edmondo Trentin, Fabio Cavalli, Luca Lusnig, 2018, Neural Networks.

Speaker normalization with a mixture of recurrent networks

Diego Giuliani, Edmondo Trentin, 1997, ESANN.

Toward a modular connectionist model of local chlorophyll concentration from satellite images

Edmondo Trentin, L. Magnoni, A. Andronico, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

Proceedings of the 7th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition

Friedhelm Schwenker, Edmondo Trentin, Hm Abbas, 2016 .

Asymptotic Convergence of Soft-Constrained Neural Networks for Density Estimation

Edmondo Trentin, E. Trentin, 2020, Mathematics.

Scalable pseudo-likelihood estimation in hybrid random fields

Marco Gori, Edmondo Trentin, Antonino Freno, 2009, KDD.

Emotion recognition from speech signals via a probabilistic echo-state network

Friedhelm Schwenker, Stefan Scherer, Edmondo Trentin, 2015, Pattern Recognit. Lett..

Off the Mainstream: Advances in Neural Networks and Machine Learning for Pattern Recognition

Friedhelm Schwenker, Hazem M. Abbas, Edmondo Trentin, 2018, Neural Processing Letters.

Probabilistic Interpretation of Neural Networks for the Classification of Vectors, Sequences and Graphs

Edmondo Trentin, Antonino Freno, E. Trentin, 2009, Innovations in Neural Information Paradigms and Applications.

A Novel Connectionist System for Unconstrained Handwriting Recognition

Edmondo Trentin, J. Schmidhuber, A. Graves, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Use of pattern recognition and neural networks for non-metric sex diagnosis from lateral shape of calvarium: an innovative model for computer-aided diagnosis in forensic and physical anthropology

Edmondo Trentin, Fabio Cavalli, Luca Lusnig, 2016, International Journal of Legal Medicine.

Towards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation

Edmondo Trentin, Marco Bongini, 2012, ANNPR.

Classification of graphical data made easy

Edmondo Trentin, Ernesto Di Iorio, E. Trentin, 2009, Neurocomputing.

Supervised and Unsupervised Co-training of Adaptive Activation Functions in Neural Nets

Edmondo Trentin, Ilaria Castelli, 2011, PSL.

Continuous Speech Recognition with a Robust Connectionist/Markovian Hybrid Model

Marco Gori, Edmondo Trentin, 2001, ICANN.

Proceedings of the First IAPR TC3 conference on Partially Supervised Learning

Friedhelm Schwenker, Edmondo Trentin, 2011 .

A Refinement Algorithm for Deep Learning via Error-Driven Propagation of Target Outputs

Edmondo Trentin, Vincenzo Laveglia, E. Trentin, 2018, ANNPR.

Learning Perception for Indoor Robot Navigation with a Hybrid Hidden Markov Model/Recurrent Neural Networks Approach

Edmondo Trentin, Roldano Cattoni, E. Trentin, 1999, Connect. Sci..

Unsupervised nonparametric density estimation: A neural network approach

Edmondo Trentin, Antonino Freno, E. Trentin, 2009, 2009 International Joint Conference on Neural Networks.

Dynamic Hybrid Random Fields for the Probabilistic Graphical Modeling of Sequential Data: Definitions, Algorithms, and an Application to Bioinformatics

Edmondo Trentin, Marco Bongini, Antonino Freno, 2018, Neural Processing Letters.

On Semi-Supervised Clustering

Friedhelm Schwenker, Edmondo Trentin, Marco Bongini, 2015 .

Maximum-Likelihood Estimation of Neural Mixture Densities: Model, Algorithm, and Preliminary Experimental Evaluation

Edmondo Trentin, E. Trentin, 2018, ANNPR.

Hidden Markov models with graph densities for action recognition

Günther Palm, Friedhelm Schwenker, Michael Glodek, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).