WorldCat Identities

Villa, Alessandro E. P.

Overview
Works: 29 works in 129 publications in 3 languages and 2,428 library holdings
Genres: Conference papers and proceedings 
Roles: Editor, htt, Thesis advisor, Author, Other, Opponent, Contributor
Classifications: QA76.87, 006.32
Publication Timeline
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Most widely held works by Alessandro E. P Villa
Artificial neural networks and machine learning - ICANN 2017 : 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017, proceedings by International Conference on Artificial Neural Networks (European Neural Network Society)( )

23 editions published in 2017 in English and German and held by 618 WorldCat member libraries worldwide

The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks, ICANN 2017, held in Alghero, Italy, in September 2017. The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions. They were organized in topical sections named: From Perception to Action; From Neurons to Networks; Brain Imaging; Recurrent Neural Networks; Neuromorphic Hardware; Brain Topology and Dynamics; Neural Networks Meet Natural and Environmental Sciences; Convolutional Neural Networks; Games and Strategy; Representation and Classification; Clustering; Learning from Data Streams and Time Series; Image Processing and Medical Applications; Advances in Machine Learning. There are 63 short paper abstracts that are included in the back matter of the volume
Artificial neural networks and machine learning - ICANN 2012 : 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings by ICANN 2012( )

16 editions published in 2012 in English and held by 400 WorldCat member libraries worldwide

Annotation
Artificial Neural Networks and Machine Learning - Icann 2012 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part I by Alessandro E. P Villa( )

13 editions published in 2012 in English and German and held by 388 WorldCat member libraries worldwide

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting
Artificial Neural Networks and Machine Learning - ICANN 2016 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II by International Conference on Artificial Neural Networks (European Neural Network Society)( )

17 editions published in 2016 in English and held by 333 WorldCat member libraries worldwide

The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume
Artificial Neural Networks and Machine Learning - ICANN 2016 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part I by ICANN( )

11 editions published in 2016 in English and held by 321 WorldCat member libraries worldwide

The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume
Advances in Cognitive Neurodynamics (VII) : Proceedings of the Seventh International Conference on Cognitive Neurodynamics - 2019 by Alessandra Lintas( )

6 editions published in 2021 in English and held by 161 WorldCat member libraries worldwide

This book contains original articles submitted to the Seventh International Conference on Cognitive Neurodynamics (ICCN 2019). The brain is an endless case study of a complex system characterized by multiple levels of integration, multiple time scales of activity, and multiple coding and decoding properties. The contribution of several disciplines, mathematics, physics, computer science, neurobiology, pharmacology, physiology, and behavioral and clinical sciences, is necessary in order to cope with such seemingly unattainable complexity that transforms the experimental information into a tricky puzzle which hides the correspondence with model predictions. This conference gathered active participants to discuss ideas and pose new questions from different viewpoints, ranging from single neurons and neural networks to animal/human behavior in theoretical and experimental studies. The conference is organized with plenary lectures, mini-symposia, interdisciplinary round tables, and oral and poster sessions
Artificial neural networks and machine learning -- ICANN 2013 : 23rd International Conference on Artificial Neural Networks Sofia, Bulgaria, September 10-13, 2013 : proceedings by Valeri Mladenov( )

8 editions published in 2013 in English and held by 101 WorldCat member libraries worldwide

The book constitutes the proceedings of the 23rd International Conference on Artificial Neural Networks, ICANN 2013, held in Sofia, Bulgaria, in September 2013. The 78 papers included in the proceedings were carefully reviewed and selected from 128 submissions. The focus of the papers is on following topics: neurofinance graphical network models, brain machine interfaces, evolutionary neural networks, neurodynamics, complex systems, neuroinformatics, neuroengineering, hybrid systems, computational biology, neural hardware, bioinspired embedded systems, and collective intelligence
Artificial neural networks and machine learning - ICANN 2014 : 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014 : proceedings by Stefan Wermter( )

11 editions published in 2014 in 3 languages and held by 73 WorldCat member libraries worldwide

The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications
Emergence of oriented circuits driven by synaptic pruning associated with spike-timing-dependent plasticity (STDP) by Javier Iglesias( Book )

2 editions published in 2005 in English and held by 3 WorldCat member libraries worldwide

Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre, and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 1,000,000 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation
Selected papers presented at the 5th International Workshop on Neural Coding : Aula, Italy, September 20-23, 2003 by International Workshop on Neural Coding( Book )

1 edition published in 2005 in English and held by 3 WorldCat member libraries worldwide

Détection de patterns d'activité bioélectrique simulée et modélisation de réseaux neuraux bioinspirés par l'expression génique by Vladyslav Shaposhnyk( )

1 edition published in 2011 in French and held by 2 WorldCat member libraries worldwide

L'architecture modulaire est une caractéristique distinctive des circuits cérébraux. En particulier, il a été observé l'existence de connexions réciproques entre des zones fonctionnellement interconnectées dans le cortex, et qui par ailleurs sont hiérarchiquement organisées. De plus, le développement évolutif est une autre caractéristique distinctive des espèces vivantes ; même les virus sont capables d'adaptation pour mieux répondre à de nouvelles conditions environnementales. En tenant compte de ces deux importants aspects, nous avons construit un nouvel et unique outil de simulation permettant de modéliser et d'étudier l'évolution des circuits multi-modulaires hiérarchiques. Dans ce modèle, chaque module est représenté par des réseaux de neurones impulsionels et caractérisé à la fois par des changements d'activités neurales imbriquées et par la plasticité synaptique. La morte cellulaire, la plasticité synaptique et l'apoptose intégrés dans le modèle créent des liens auto-associatifs au sein des modules. Ces liens peuvent générer une activité zonale qui reflète l'évolution de la connectivité fonctionnelle à l'intérieur comme à l'extérieur des modules, et donc entre les plusieurs modules neuronaux. L'activité bioélectrique de chaque module est enregistrée au moyen des électrodes virtuelles. Les signaux, electrochipogrammes (EChG), sont analysés par les méthodes fréquentiels et les méthodes de potentiels évoqués afin de trouver des généralités dans le comportement émergeant. En plus de ces méthodes conventionnelles, nous proposons une nouvelle approche de régression non-linéaire structurelle afin de fournir des outils plus puissants et mieux adaptés aux données habituellement analysées dans ce domaine. Nous avons donc testé l'effet d'un stimulus externe sur le développement de liens fonctionnels d'un réseau neuronaux. Le circuit est structuré hiérarchiquement avec un unique module sensoriel et d'autres modules constitués de deux voies parallèles organisées aussi de façon hiérarchique. Nos résultats montrent que les circuits modélisés manifestent un comportement similaire que les circuits biologiques réels. En particulier, tous les éléments du circuit peuvent traiter et maintenir des patterns d'activité liés à la disparition du stimulus. Les résultats obtenus dans nos expériences apportent un éclairage sur les processus émergents et coordonnés de l'activité électrique enregistrée par des EEG de circuits inter-corticaux hiérarchiques et évolutifs qui sont artificiels ou réels. Plus généralement, notre approche concernant les signaux EEG pourrait être étendue à la modélisation d'une vaste variété des processus cognitifs et comportementaux
Fast combinatorial methods to estimate the probability of complex temporal patterns of spikes by Igor V Tetko( )

1 edition published in 1997 in English and held by 2 WorldCat member libraries worldwide

Selective proliferative response of microglia to alternative polarization signals by Giovanna Pepe( )

1 edition published in 2017 in English and held by 2 WorldCat member libraries worldwide

Complex temporal patterns processing by a neural mass model of a cortical column by Daniel Malagarriga( )

1 edition published in 2019 in English and held by 2 WorldCat member libraries worldwide

Artificial neural networks and machine learning( Book )

1 edition published in 2012 in English and held by 2 WorldCat member libraries worldwide

The topology of the directed clique complex as a network invariant by Paolo Masulli( )

1 edition published in 2016 in English and held by 2 WorldCat member libraries worldwide

Artificial neural networks and machine learning( Book )

1 edition published in 2012 in English and held by 2 WorldCat member libraries worldwide

Interactions fonctionnelles dans les ganglions de la base étudiées par l'enregistrement simultané des activités unitaires discriminées par un algorithme non supervisé de tri de potentiels d'action by Olga Chibirova( Book )

2 editions published in 2006 in English and held by 2 WorldCat member libraries worldwide

La thèse porte sur une nouvelle méthode de tri non supervisé de potentiels d'action et sur son application à l'analyse de l'activité neuronale des ganglions de la base. Le développement de nouvelles approches au tri de potentiels d'action est actuel en vue de nouveaux outils nécessaires à l'électrophysiologie effectuée pendent la neurochirurgie fonctionnelle, autant que pour l'efficacité des l'expériences électrophysiologiques en temps réel. La méthode présentée dans la première partie de cette thèse est une nouvelle approche à ce problème qui décrit les potentiels d'action à l'aide des équations différentielles avec perturbation caractérisant la variation interne de leur forme. Le logiciel permettant le tri de potentiels d'action non supervisé développé à partir de cette méthode comprends un algorithme automatique d'évaluation d'étalons de classes et de leurs rayons. La seconde partie présente l'application de la méthode à l'analyse de l'activité neuronale des ganglions de la base. Les donnés pour les analyses ont été recueillis au bloque chirurgical du département de neurochirurgie de l'Hôpital Universitaire de Grenoble pendent l'électrophysiologie intra chirurgicale et représentent le STN (950 enregistrements), le GPI (183) et le SNR (105) de 13 patients parkinsoniens et 2 patients souffrant de dystonie. Les analyses sont destinées à définir les formes typiques de potentiel d'action et à révéler un parallèle entre la nature de l'activité neuronale et la gravité des symptômes de la maladie de Parkinson
Mathematical models for the study of synchronization phenomena in neuronal networks by Roberta Sirovich( Book )

2 editions published in 2006 in English and held by 2 WorldCat member libraries worldwide

The spike train, i.e. the sequence of the action potential timings of a single unit, is the usual data that is analyzed in electrophysiological recordings for the description of the firing pattern which is supposed to characterize a certain type of cell.. We present the results obtained describing the firing activity of a small network of neurons with a mathematical jump diffusion model. That is the membrane potential as a function of time is given by the sum of a stochastic diffusion process and two counting processes that provoke jumps of constant sizes at discrete random times. Different distributions are considered for such processes. Two main results emerge. The first one is that interspike intervals (ISI) histograms show more than one peak (multimodality) and exhibit a resonant like behavior. This fact suggests that in correspondence of each mode (i.e. the lag of the maxima) the cell has a higher probability of firing such that the the lags become characteristic times of the cell which could be modulated under physiological conditions. The second main result concerns the role of inhibition in neuronal coding. Indeed we show that the inhibitory inputs may facilitate the transmission of the spikes generated by the excitatory inputs. This fact suggests that inhibitory cells are not only involved in keeping balanced the excitability of the cell but that they may also play a key role in the information process. Such kind of models requires to improve the algorithms to simulate the first passage time through a threshold of a stochastic process. So that the second part of this manuscript is dedicated to a a purely theoretical study on multidimensional bridge processes
Artificial Neural Networks and Machine Learning {u2013} ICANN 2014 : 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings by Stefan Wermter( Book )

1 edition published in 2014 in English and held by 1 WorldCat member library worldwide

The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications
 
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Artificial neural networks and machine learning - ICANN 2017 : 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017, proceedings
Covers
Artificial neural networks and machine learning - ICANN 2012 : 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, ProceedingsArtificial Neural Networks and Machine Learning - Icann 2012 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part IArtificial Neural Networks and Machine Learning - ICANN 2016 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part IIArtificial Neural Networks and Machine Learning - ICANN 2016 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part IArtificial neural networks and machine learning -- ICANN 2013 : 23rd International Conference on Artificial Neural Networks Sofia, Bulgaria, September 10-13, 2013 : proceedingsArtificial neural networks and machine learning - ICANN 2014 : 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014 : proceedingsArtificial neural networks and machine learningArtificial neural networks and machine learning
Alternative Names
Alessandro E.P Villa wetenschapper

Villa, A. E. P. (Alessandro E. P.)

Villa, Alessandro 1961-

Languages
English (115)

German (3)

French (1)