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ORCIDEdmondo Trentin
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- affiliation: Università di Siena, Italy
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2020 – today
- 2024
[c36]Duccio Meconcelli, Edmondo Trentin:
Gaussian-Mixture Neural Networks. ANNPR 2024: 13-24- [c35]Natasha Sharma, Sona Balogova, Lucia Noskovicova, Françoise Montravers, Jean-Noël Talbot, Edmondo Trentin:
Automatic Interpretation of 18F-Fluorocholine PET/CT Findings in Patients with Primary Hyperparathyroidism: A Novel Dataset with Benchmarks. ANNPR 2024: 75-86 - [e6]Ching Yee Suen, Adam Krzyzak, Mirco Ravanelli, Edmondo Trentin, Cem Subakan, Nicola Nobile:
Artificial Neural Networks in Pattern Recognition - 11th IAPR TC3 Workshop, ANNPR 2024, Montreal, QC, Canada, October 10-12, 2024, Proceedings. Lecture Notes in Computer Science 15154, Springer 2024, ISBN 978-3-031-71601-0 [contents] - 2023
- [j26]Vincenzo Laveglia
, Edmondo Trentin:
Downward-Growing Neural Networks. Entropy 25(5): 733 (2023) - [j25]Edmondo Trentin:
Multivariate Density Estimation with Deep Neural Mixture Models. Neural Process. Lett. 55(7): 9139-9154 (2023) - [e5]Neamat El Gayar, Edmondo Trentin, Mirco Ravanelli, Hazem Abbas:
Artificial Neural Networks in Pattern Recognition - 10th IAPR TC3 Workshop, ANNPR 2022, Dubai, United Arab Emirates, November 24-26, 2022, Proceedings. Lecture Notes in Computer Science 13739, Springer 2023, ISBN 978-3-031-20649-8 [contents] - 2022
- [c34]Marco Benini, Pietro Bongini, Edmondo Trentin:
A Novel Representation of Graphical Patterns for Graph Convolution Networks. ANNPR 2022: 16-27 - 2021
- [i2]Sara Papi, Edmondo Trentin, Roberto Gretter, Marco Matassoni, Daniele Falavigna:
Mixtures of Deep Neural Experts for Automated Speech Scoring. CoRR abs/2106.12475 (2021) - 2020
- [c33]Sara Papi, Edmondo Trentin, Roberto Gretter, Marco Matassoni, Daniele Falavigna:
Mixtures of Deep Neural Experts for Automated Speech Scoring. INTERSPEECH 2020: 3845-3849 - [i1]Edmondo Trentin:
Multivariate Density Estimation with Deep Neural Mixture Models. CoRR abs/2012.03391 (2020)
2010 – 2019
- 2018
- [j24]Edmondo Trentin, Ernesto Di Iorio:
Nonparametric small random networks for graph-structured pattern recognition. Neurocomputing 313: 14-24 (2018) - [j23]Edmondo Trentin, Luca Lusnig, Fabio Cavalli:
Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology. Neural Networks 97: 137-151 (2018) - [j22]Edmondo Trentin, Friedhelm Schwenker, Neamat El Gayar, Hazem M. Abbas:
Off the Mainstream: Advances in Neural Networks and Machine Learning for Pattern Recognition. Neural Process. Lett. 48(2): 643-648 (2018) - [j21]Marco Bongini, Antonino Freno, Vincenzo Laveglia, Edmondo Trentin:
Dynamic Hybrid Random Fields for the Probabilistic Graphical Modeling of Sequential Data: Definitions, Algorithms, and an Application to Bioinformatics. Neural Process. Lett. 48(2): 733-768 (2018) - [j20]Edmondo Trentin:
Soft-Constrained Neural Networks for Nonparametric Density Estimation. Neural Process. Lett. 48(2): 915-932 (2018) - [j19]Marco Bongini, Leonardo Rigutini, Edmondo Trentin:
Recursive Neural Networks for Density Estimation Over Generalized Random Graphs. IEEE Trans. Neural Networks Learn. Syst. 29(11): 5441-5458 (2018) - [c32]Vincenzo Laveglia, Edmondo Trentin:
A Refinement Algorithm for Deep Learning via Error-Driven Propagation of Target Outputs. ANNPR 2018: 78-89 - [c31]Edmondo Trentin:
Maximum-Likelihood Estimation of Neural Mixture Densities: Model, Algorithm, and Preliminary Experimental Evaluation. ANNPR 2018: 178-189 - [e4]Luca Pancioni, Friedhelm Schwenker, Edmondo Trentin:
Artificial Neural Networks in Pattern Recognition - 8th IAPR TC3 Workshop, ANNPR 2018, Siena, Italy, September 19-21, 2018, Proceedings. Lecture Notes in Computer Science 11081, Springer 2018, ISBN 978-3-319-99977-7 [contents] - 2016
- [c30]Edmondo Trentin:
Soft-Constrained Nonparametric Density Estimation with Artificial Neural Networks. ANNPR 2016: 68-79 - [c29]Marco Bongini, Vincenzo Laveglia, Edmondo Trentin:
A Hybrid Recurrent Neural Network/Dynamic Probabilistic Graphical Model Predictor of the Disulfide Bonding State of Cysteines from the Primary Structure of Proteins. ANNPR 2016: 257-268 - [e3]Friedhelm Schwenker, Hazem M. Abbas, Neamat El Gayar, Edmondo Trentin:
Artificial Neural Networks in Pattern Recognition - 7th IAPR TC3 Workshop, ANNPR 2016, Ulm, Germany, September 28-30, 2016, Proceedings. Lecture Notes in Computer Science 9896, Springer 2016, ISBN 978-3-319-46181-6 [contents] - 2015
- [j18]Marco Aste, Massimo Boninsegna, Antonino Freno, Edmondo Trentin:
Techniques for dealing with incomplete data: a tutorial and survey. Pattern Anal. Appl. 18(1): 1-29 (2015) - [j17]Edmondo Trentin, Stefan Scherer, Friedhelm Schwenker:
Emotion recognition from speech signals via a probabilistic echo-state network. Pattern Recognit. Lett. 66: 4-12 (2015) - [j16]Edmondo Trentin:
Maximum-likelihood normalization of features increases the robustness of neural-based spoken human-computer interaction. Pattern Recognit. Lett. 66: 71-80 (2015) - 2014
- [j15]Friedhelm Schwenker, Edmondo Trentin:
Partially supervised learning for pattern recognition. Pattern Recognit. Lett. 37: 1-3 (2014) - [j14]Friedhelm Schwenker, Edmondo Trentin:
Pattern classification and clustering: A review of partially supervised learning approaches. Pattern Recognit. Lett. 37: 4-14 (2014) - [j13]Ilaria Castelli, Edmondo Trentin:
Combination of supervised and unsupervised learning for training the activation functions of neural networks. Pattern Recognit. Lett. 37: 178-191 (2014) - 2013
- [c28]Michael Glodek, Edmondo Trentin, Friedhelm Schwenker, Günther Palm:
Hidden Markov models with graph densities for action recognition. IJCNN 2013: 1-6 - 2012
- [c27]Edmondo Trentin, Marco Bongini:
Towards a Novel Probabilistic Graphical Model of Sequential Data: Fundamental Notions and a Solution to the Problem of Parameter Learning. ANNPR 2012: 72-81 - [c26]Marco Bongini, Edmondo Trentin:
Towards a Novel Probabilistic Graphical Model of Sequential Data: A Solution to the Problem of Structure Learning and an Empirical Evaluation. ANNPR 2012: 82-92 - [e2]Nadia Mana, Friedhelm Schwenker, Edmondo Trentin:
Artificial Neural Networks in Pattern Recognition - 5th INNS IAPR TC 3 GIRPR Workshop, ANNPR 2012, Trento, Italy, September 17-19, 2012. Proceedings. Lecture Notes in Computer Science 7477, Springer 2012, ISBN 978-3-642-33211-1 [contents] - [e1]Friedhelm Schwenker, Edmondo Trentin:
Partially Supervised Learning - First IAPR TC3 Workshop, PSL 2011, Ulm, Germany, September 15-16, 2011, Revised Selected Papers. Lecture Notes in Computer Science 7081, Springer 2012, ISBN 978-3-642-28257-7 [contents] - 2011
- [b1]Antonino Freno, Edmondo Trentin:
Hybrid Random Fields - A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models. Intelligent Systems Reference Library 15, Springer 2011, ISBN 978-3-642-20307-7, pp. 1-167 - [c25]Ilaria Castelli, Edmondo Trentin:
Supervised and Unsupervised Co-training of Adaptive Activation Functions in Neural Nets. PSL 2011: 52-61 - [c24]Ilaria Castelli, Edmondo Trentin:
Semi-unsupervised Weighted Maximum-Likelihood Estimation of Joint Densities for the Co-training of Adaptive Activation Functions. PSL 2011: 62-71 - [c23]Edmondo Trentin, Luca Lusnig, Fabio Cavalli:
Comparison of Combined Probabilistic Connectionist Models in a Forensic Application. PSL 2011: 128-137 - 2010
- [c22]Edmondo Trentin, Shujia Zhang, Markus Hagenbuchner:
Recognition of Sequences of Graphical Patterns. ANNPR 2010: 48-59 - [c21]Edmondo Trentin, Stefan Scherer, Friedhelm Schwenker:
Maximum Echo-State-Likelihood Networks for Emotion Recognition. ANNPR 2010: 60-71 - [c20]Antonino Freno, Edmondo Trentin, Marco Gori:
Kernel-Based Hybrid Random Fields for Nonparametric Density Estimation. ECAI 2010: 427-432
2000 – 2009
- 2009
- [j12]Edmondo Trentin, Ernesto Di Iorio:
Classification of graphical data made easy. Neurocomputing 73(1-3): 204-212 (2009) - [j11]Antonino Freno, Edmondo Trentin, Marco Gori:
A hybrid random field model for scalable statistical learning. Neural Networks 22(5-6): 603-613 (2009) - [c19]Edmondo Trentin, Leonardo Rigutini:
A Maximum-Likelihood Connectionist Model for Unsupervised Learning over Graphical Domains. ICANN (1) 2009: 40-49 - [c18]Antonino Freno, Edmondo Trentin, Marco Gori:
Scalable statistical learning: A modular bayesian/markov network approach. IJCNN 2009: 890-897 - [c17]Edmondo Trentin, Antonino Freno:
Unsupervised nonparametric density estimation: A neural network approach. IJCNN 2009: 3140-3147 - [c16]Antonino Freno, Edmondo Trentin, Marco Gori:
Scalable pseudo-likelihood estimation in hybrid random fields. KDD 2009: 319-328 - [p1]Edmondo Trentin, Antonino Freno:
Probabilistic Interpretation of Neural Networks for the Classification of Vectors, Sequences and Graphs. Innovations in Neural Information Paradigms and Applications 2009: 155-182 - 2008
- [c15]Edmondo Trentin, Ernesto Di Iorio:
Classification of molecular structures made easy. IJCNN 2008: 3241-3246 - 2007
- [j10]Pasquale Fiengo, Giovanni Giambene, Edmondo Trentin:
Neural-based downlink scheduling algorithm for broadband wireless networks. Comput. Commun. 30(2): 207-218 (2007) - [c14]Edmondo Trentin, Ernesto Di Iorio:
Unbiased SVM Density Estimation with Application to Graphical Pattern Recognition. ICANN (2) 2007: 271-280 - [c13]Edmondo Trentin, Ernesto Di Iorio:
A Simple and Effective Neural Model for the Classification of Structured Patterns. KES (1) 2007: 9-16 - 2006
- [j9]Edmondo Trentin, Marco Gori:
Inversion-based nonlinear adaptation of noisy acoustic parameters for a neural/HMM speech recognizer. Neurocomputing 70(1-3): 398-408 (2006) - [c12]Edmondo Trentin:
Simple and Effective Connectionist Nonparametric Estimation of Probability Density Functions. ANNPR 2006: 1-10 - [c11]Edmondo Trentin:
A Novel Connectionist-Oriented Feature Normalization Technique. ICANN (2) 2006: 410-416 - 2005
- [c10]Edmondo Trentin, Marco Gori:
Feature Normalization via ANN/HMM Inversion for Speech Recognition Under Noisy Conditions. MMSP 2005: 1-4 - 2003
- [j8]Edmondo Trentin, Marco Matassoni:
Noise-tolerant speech recognition: the SNN-TA approach. Inf. Sci. 156(1-2): 55-69 (2003) - [j7]Edmondo Trentin, Marco Gori:
Robust combination of neural networks and hidden Markov models for speech recognition. IEEE Trans. Neural Networks 14(6): 1519-1531 (2003) - [c9]Edmondo Trentin, Marco Matassoni, Marco Gori:
Evaluation on the Aurora 2 database of acoustic models that are less noise-sensitive. INTERSPEECH 2003: 1805-1808 - [c8]Edmondo Trentin:
Nonparametric Hidden Markov Models: Principles and Applications to Speech Recognition. WIRN 2003: 3-21 - 2001
- [j6]Edmondo Trentin, Marco Gori:
A survey of hybrid ANN/HMM models for automatic speech recognition. Neurocomputing 37(1-4): 91-126 (2001) - [j5]Edmondo Trentin, Diego Giuliani:
A Mixture of Recurrent Neural Networks for Speaker Normalisation. Neural Comput. Appl. 10(2): 120-135 (2001) - [j4]Edmondo Trentin:
Networks with trainable amplitude of activation functions. Neural Networks 14(4-5): 471-493 (2001) - [c7]Edmondo Trentin, Marco Gori:
Continuous Speech Recognition with a Robust Connectionist/Markovian Hybrid Model. ICANN 2001: 577-582 - [c6]Edmondo Trentin, Marco Gori:
Toward noise-tolerant acoustic models. INTERSPEECH 2001: 889-892 - 2000
- [c5]Edmondo Trentin, Marco Matassoni:
The Regularized SNN-TA Model for Recognition of Noisy Speech. IJCNN (5) 2000: 97-102
1990 – 1999
- 1999
- [j3]Edmondo Trentin, Roldano Cattoni:
Learning Perception for Indoor Robot Navigation with a Hybrid Hidden Markov Model/Recurrent Neural Networks Approach. Connect. Sci. 11(3-4): 243-265 (1999) - [c4]Edmondo Trentin:
Activation functions with learnable amplitude. IJCNN 1999: 1794-1798 - 1997
- [j2]Cesare Furlanello, Diego Giuliani, Edmondo Trentin, Stefano Merler:
Speaker Normalization and Model Selection of Combined Neural Networks. Connect. Sci. 9(1): 31-50 (1997) - [j1]Massimo Boninsegna, Tarcisio Coianiz, Edmondo Trentin:
Estimating the crowding level with a neuro-fuzzy classifier. J. Electronic Imaging 6(3): 319-328 (1997) - [c3]Edmondo Trentin, Diego Giuliani:
Speaker normalization with a mixture of recurrent networks. ESANN 1997 - 1995
- [c2]Cesare Furlanello, Diego Giuliani, Edmondo Trentin, Daniele Falavigna:
Application of Generalized Radial Basis Functions In Speaker Normalization and Identification. ISCAS 1995: 1704-1707 - 1994
- [c1]Cesare Furlanello, Diego Giuliani, Edmondo Trentin:
Connectionist Speaker Normalization with Generalized Resource Allocating Networks. NIPS 1994: 865-874
Coauthor Index
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last updated on 2024-09-30 21:57 CEST by the dblp team
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