ESANN 2022 - Proceedings

30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Cet ouvrage présente une première approche des phénomènes quantiques et nucléaires rédigée afin d'amener le lecteur à une lecture active au lieu d’une lecture passive.

Les faits physiques et les divers modèles théoriques qui ont été élaborés pour les interpréter sont présentés et le cheminement historique est rappelé au travers de compléments clairement individualisés. Le texte est régulièrement interrompu par des questions qui se veulent formatives, en amenant le lecteur à mettre en oeuvre ou à s’interroger sur ce qui vient de lui être exposé. Il est essentiel de s’arrêter sur ces questions et d’y répondre avant de poursuivre car le plus souvent elles préparent à ce qui les suit. Le texte est émaillé de quelques questions de niveau plus relevé qui peuvent être abordées plus tard et se termine par un questionnaire à choix multiples et vingt-cinq exercices qui permettent une première auto-évaluation des connaissances acquises et la mise en pratique des principales notions abordées dans le texte. L’ouvrage se termine par un formulaire. Le lecteur est supposé avoir quelques connaissances de base en mécanique et électromagnétisme.


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Spécifications


Éditeur
ESANN
Auteur
Collectif,
Langue
anglais
Catégorie (éditeur)
Sciences appliquées > Informatique
BISAC Subject Heading
TEC000000 TECHNOLOGY & ENGINEERING
BIC subject category (UK)
U Computing & information technology
Code publique Onix
06 Professionnel et académique
CLIL (Version 2013-2019 )
3193 INFORMATIQUE
Date de première publication du titre
12 avril 2016
Type d'ouvrage
Actes de colloque

Livre broché


Date de publication
08 décembre 2024
ISBN-13
9782390615231
Ampleur
Nombre de pages de contenu principal : 200
Code interne
107558
Format
16 x 24 cm
Poids
327 grammes
Type de packaging
Aucun emballage extérieur
Prix
21,00 €
ONIX XML
Version 2.1, Version 3

PDF


Date de publication
08 décembre 2024
ISBN-13
9782390615248
Ampleur
Nombre de pages de contenu principal : 200
Code interne
107558PDF
ONIX XML
Version 2.1, Version 3

Google Livres Aperçu


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Sommaire


Feature extraction & Prototype learning

Modular Representations for Weak Disentanglement

A. Valenti, D. Bacciu 

Feature selection for transfer learning using particle swarm optimization and complexity measures

V. Bolón-Canedo, G. Castillo García, L. Morán-Fernández

Supervised dimensionality reduction technique accounting for soft classes

S. Mustatea, M. Aupetit, J. Peltonen, S. Lespinats, D. Dutykh 

Graph-Induced Geodesics Approximation for Non-Euclidian K-Means

H. Frezza-Buet

A WiSARD-based conditional branch predictor

L. A. Q. Villon, Z. Susskind, A. T. L. Bacellar, I. D. S. Miranda, L. Santiago de Araújo, P. Lima, M. Breternitz Jr., L. John, F. França, D. L. Cadette Dutra 

Distributive Thermometer: A New Unary Encoding for Weightless Neural Networks

A. T. L. Bacellar, Z. Susskind, L. A. Q. Villon, I. D. S. Miranda, L. Santiago de Araújo, D. L. Cadette Dutra, M. Breternitz Jr., L. John, P. Lima, F. França 

Pruning Weightless Neural Networks

Z. Susskind, A. T. L. Bacellar, A. Arora, L. A. Q. Villon, R. Mendanha, L. Santiago de Araújo, D. L. Cadette Dutra, P. Lima, F. França, I. D. S. Miranda, M. Breternitz Jr., L. John 

Classification of preclinical markers in Alzheimer's disease via WiSARD classifier

M. De Gregorio, A. Di Costanzo, A. Motta, D. Paris, A. Sorgente 

A bayesian variational principle for dynamic self organizing maps A. Fillion, T. Kulak, F. Blayo 

The role of feature selection in personalized recommender systems

R. Bagué-Masanés, V. Bolón-Canedo, B. Remeseiro

Adaptive Gabor Filters for Interpretable Color Texture Classification

G. Luimstra, K. Bunte 

Continual Learning beyond classification

Tutorial - Continual Learning beyond classification

A. Gepperth, T. Lesort 

Continual Learning for Human State Monitoring

F. Matteoni, A. Cossu, C. Gallicchio, V. Lomonaco, D. Bacciu 

Continual Incremental Language Learning for Neural Machine Translation

M. Resta, D. Bacciu 

Diverse Memory for Experience Replay in Continual Learning

A. Krutsylo, P. Morawiecki 

Classification

Model Agnostic Local Explanations of Reject

A. Artelt, R. Visser, B. Hammer 

Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification

M. Münch, C. Raab, S. Heilig, M. Röder, F.-M. Schleif 

A Kernel Based Multilinear SVD Approach for Multiple Sclerosis Profiles Classification

B. Barile, P. Ashtari, F. Durand-Dubief, F. Maes, D. Sappey-Marinier, S. Van Huffel 

A Machine Learning Approach for School Dropout Prediction in Brazil

J. G. Corrêa Krüger, J. P. Barddal, A. de S. Britto Jr. 

An empirical comparison of generators in replay-based continual learning

N. Dzemidovich, A. Gepperth 

Machine learning for automated quality control in injection moulding manufacturing

S. Michiels, C. De Schryver, L. Houthuys, F. Vogeler, F. Desplentere

Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets

L. Oneto, S. Minisi, A. Garrone, R. Canepa, C. Dambra, D. Anguita 

Price direction prediction in financial markets, using Random Forest and Adaboost

M. Ghahramani, F. Aiolli

Learning theory and principles

Multioutput Regression Neural Network Training via Gradient Boosting

S. emami, G. Martínez-Muñoz 

Do We Really Need a New Theory to Understand the Double-Descent?

L. Oneto, S. Ridella, D. Anguita 

Filtering participants improves generalization in competitions and benchmarks

A. Pavao, I. Guyon, Z. Liu 

Sliced-Wasserstein normalizing flows: beyond maximum likelihood training

F. Coeurdoux, N. Dobigeon, P. Chainais

A Fast and Simple Evolution Strategy with Covariance Matrix Estimation

O. Kramer 

Constraint Guided Gradient Descent: Guided Training with Inequality Constraints

Q. Van Baelen, P. Karsmakers 

Bayes Point Rule Set Learning

M. Polato, F. Aiolli, L. Bergamin, T. Carraro 

Neural-network-based estimation of normal distributions in black-box optimization

J. Tumpach, J. Koza, M. Holeňa 

Deep learning, signal, image

Feature Compression Using Dynamic Switches in Multi-split CNNs

S. K. Kumaraswamy, A. Ozerov, N. Q. K. Duong, A. Lambert, F. Schnitzler, P. Fontaine 

Hyperspectral Wavelength Analysis with U-Net for Larynx Cancer Detection

F. Meyer-Veit, R. Rayyes, A. O. H. Gerstner, J. J. Steil 

Lightening CNN architectures by regularization driven weights' pruning

G. Bonetta, R. Cancelliere 

1D vs 2D convolutional neural networks for scalp high frequency oscillations identification

G. Milon-Harnois, N. Jrad, D. Schang, P. Van Bogaert, P.Chauvet 

Deep latent position model for node clustering in graphs

D. Liang, M. Corneli, C. Bouveyron, P. Latouche

Deep Convolutional Neural Networks with Sequentially Semiseparable Weight Matrices

M. Kissel, K. Diepold 

Deep networks with ReLU activation functions can be smooth statistical models

J. Rynkiewicz

PCA improves the adversarial robustness of neural networks

I. Megyeri, A. Al-Najjar 

Battery detection of XRay images using transfer learning

N. Abou Baker, D. Rohrschneider, U. Handmann 

Real-time capable Ensemble Estimation for 2D Object Detection

L. Enderich, S. Heming 

Appearance-Context aware Axial Attention for Fashion Landmark Detection

N. Kilari, G. Bhattacharya, P. K. Reddy K, J. Gubbi, A. Pal 

ROP inception: signal estimation with quadratic random sketching

R. Delogne, V. Schellekens, L. Jacques

Semi-synthetic Data for Automatic Drone Shadow Detection

M. E. A. Mokhtari, V. Vandenbulcke, S. Laraba, M. Mancas, E. Ennadifi, M. L. Tazir, B. Gosselin

Deep learning for Parkinson's disease symptom detection and severity evaluation using accelerometer signal

T. Gutowski 

Anomaly and change point detection

Challenges in anomaly and change point detection

M. Olteanu, F. Rossi, F. Yger 

Anomaly detections on the oil system of a turbofan engine by a neural autoencoder

J. Coussirou, T. Vanaret, J. Lacaille 

Contrasting Explanation of Concept Drift

F. Hinder, A. Artelt, V. Vaquet, B. Hammer 

Anomaly detection and representation learning in an instrumented railway bridge

Y. Bel-Hadj, W. Weijtjens, F. de Nolasco Santos

Deep Semantic Segmentation Models in Computer Vision

Deep Semantic Segmentation Models in Computer Vision

P. Andreini, G. M. Dimitri 

Deep Semantic Segmentation in Skin Detection

D. Cuza, A. Loreggia, A. Lumini, L. Nanni

A weakly supervised approach to skin lesion segmentation

S. Bonechi 

A Deep Learning approach for oocytes segmentation and analysis

P. Andreini, N. Pancino, F. Costanti, G. Eusepi, B. T. Corradini

Deep Learning Approaches for mice glomeruli segmentation

D. Meconcelli, S. Bonechi, G. M. Dimitri 

Detection and Localization of GAN Manipulated Multi-spectral Satellite Images

L. Abady, G. M. Dimitri, M. Barni

Regression and forecasting

Wind power forecasting based on bagging extreme learning machine ensemble model

M. H. Dal Molin Ribeiro, S. Rodrigues Moreno, R. G. da Silva, J. H. Kleinubing Larcher, C. Canton, V. C. Mariani, L. d. S. Coelho

Dynamics-aware Representation Learning via Multivariate Time Series Transformers

M. Potter, I. Yildiz Potter, O. Camps, M. Sznaier

Minkowski logarithmic error: A physics-informed neural network approach for wind turbine lifetime assessment

F. de Nolasco Santos, P. D'Antuono, N. Noppe, W. Weijtjens, C. Devriendt 

Improving Laplacian Pyramids Regression with Localization in Frequency and Time

N. Rabin, B. Hen, A. Fernández

Gap filling in air temperature series by matrix completion methods

B. Loucheur, P.-A. Absil, M. Journée

Predicting Test Execution Times with Asymmetric Random Forests

F. Pereira, H. Silva, J. Gomes, J. Machado

Recurrent learning and reservoir computing

Orthogonality in Additive Echo State Networks

A. Ceni, C. Gallicchio 

Towards Better Transition Modeling in Recurrent Neural Networks: the Case of Sign Language Tokenization

P. Poitier, J. Fink, B. Frénay 

Federated Adaptation of Reservoirs via Intrinsic Plasticity

V. De Caro, C. Gallicchio, D. Bacciu 

Recurrent Restricted Kernel Machines for Time-series Forecasting

A. Pandey, H. De Meulemeester, H. De Plaen, B. De Moor, J. Suykens

Input Routed Echo State Networks

L. Argentieri, C. Gallicchio, A. Micheli 

Natural language processing, and recommender systems

Attention-based Ingredient Phrase Parser

Z. Shi, P. Ni, M. Wang, T. E. Kim, A. Lipani 

Neural Architecture Search for Sentence Classification with BERT

P. Kenneweg, S. Schröder, B. Hammer 

High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits

D. Young, D. Leith

Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine

Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine

T. Villmann, J. Almeida, J. Lee, S. Vinga

Interactive dual projections for gene expression analysis

I. Diaz-Blanco, J. M. Enguita-Gonzalez, D. Garcia-Perez, A. Gonzalez-Muñiz, A. A. Cuadrado-Vega, M. D. Chiara-Romero, N. Valdes-Gallego

Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features

K. S. Bohnsack, M. Kaden, J. Voigt, T. Villmann 

Interactive visual analytics for medical data: application to COVID-19 clinical information during the first wave

I. Diaz-Blanco, J. M. Enguita-Gonzalez, D. Garcia-Perez, M. D. Chiara-Romero, N. Valdes-Gallego, A. Gonzalez-Muñiz, A. A. Cuadrado-Vega 

Improving Intensive Care Chest X-Ray Classification by Transfer Learning and Automatic Label Generation

H. Schneider, D. Biesner, S. Nowak, Y. Layer, M. Theis, W. Block, B. Wulff, A. M. Sprinkart, U. I. Attenberger, R. Sifa 

Concept drift

Federated learning vector quantization for dealing with drift between nodes

J. Brinkrolf, V. Vaquet, F. Hinder, P. Menz, U. Seiffert, B. Hammer 

From hyperspectral to multispectral sensing – from simulation to reality: A comprehensive approach for calibration model transfer

P. Menz, V. Vaquet, B. Hammer, U. Seiffert 

Data stream generation through real concept's interpolation

J. Komorniczak, P. Ksieniewicz 

Deep Learning for Graphs

Deep Learning for Graphs

D. Bacciu, F. Errica, N. Navarin, L. Pasa, D. Zambon 

Beyond Homophily with Graph Echo State Networks

D. Tortorella, A. Micheli 

Biased Edge Dropout in NIFTY for Fair Graph Representation Learning

F. Caldart, L. Pasa, L. Oneto, A. Sperduti, N. Navarin 

Embedding-based next song recommendation for playlists

R. Romero, T. De Bie

Graph Neural Networks for Propositional Model Counting

G. Saveri 

Revisiting Edge Pooling in Graph Neural Networks

F. Landolfi

Reinforcement learning

Size Scaling in Self-Play Reinforcement Learning

O. Neumann, C. Gros 

Improving Zorro Explanations for Sparse Observations with Dense Proxy Data

A. Mazur, A. Artelt, B. Hammer

Reinforcement learning for constructing low density sign representations of Boolean functions

O. Yapar, E. Oztop

Developmental Modular Reinforcement Learning

J. Xue, F. Alexandre 

Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning

Y. Zhao, R. Boney, A. Ilin, J. Kannala, J. Pajarinen

Author index 

Committees