default search action
30th ESANN 2022: Bruges, Belgium
- 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2022, Bruges, Belgium, October 5-7, 2022. 2022
- Andrea Valenti, Davide Bacciu:
Modular Representations for Weak Disentanglement. - Verónica Bolón-Canedo, Guillermo Castillo García, Laura Morán-Fernández:
Feature selection for transfer learning using particle swarm optimization and complexity measures. - Sorina Mustatea
, Michaël Aupetit, Jaakko Peltonen, Sylvain Lespinats, Denys Dutykh:
Supervised dimensionality reduction technique accounting for soft classes. - Hervé Frezza-Buet:
Graph-Induced Geodesics Approximation for Non-Euclidian K-Means. - Luis A. Q. Villon, Zachary Susskind, Alan T. L. Bacellar, Igor D. S. Miranda, Leandro Santiago de Araújo, Priscila M. V. Lima, Maurício Breternitz Jr.
A WiSARD-based conditional branch predictor. - Alan T. L. Bacellar, Zachary Susskind, Luis A. Q. Villon, Igor D. S. Miranda, Leandro Santiago de Araújo, Diego Leonel Cadette Dutra, Maurício Breternitz Jr.
Distributive Thermometer: A New Unary Encoding for Weightless Neural Networks. - Zachary Susskind, Alan T. L. Bacellar, Aman Arora
Pruning Weightless Neural Networks. - Massimo De Gregorio, Alfonso Di Costanzo, Andrea Motta, Debora Paris, Antonio Sorgente:
Classification of preclinical markers in Alzheimer's disease via WiSARD classifier. - Anthony Fillion, Thibaut Kulak, François Blayo:
A bayesian variational principle for dynamic self organizing maps. - Roger Bagué-Masanés, Verónica Bolón-Canedo, Beatriz Remeseiro:
The role of feature selection in personalized recommender systems. - Gerrit Luimstra, Kerstin Bunte:
Adaptive Gabor Filters for Interpretable Color Texture Classification.
Continual Learning beyond classification
- Alexander Gepperth, Timothée Lesort:
Tutorial - Continual Learning beyond classification. - Federico Matteoni, Andrea Cossu
Continual Learning for Human State Monitoring. - Michele Resta, Davide Bacciu:
Continual Incremental Language Learning for Neural Machine Translation. - Andrii Krutsylo, Pawel Morawiecki:
Diverse Memory for Experience Replay in Continual Learning.
Classification
- André Artelt, Roel Visser, Barbara Hammer:
Model Agnostic Local Explanations of Reject. - Maximilian Münch, Christoph Raab, Simon Heilig, Manuel Röder, Frank-Michael Schleif
Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification. - Berardino Barile, Pooya Ashtari, Françoise Durand-Dubief, Frederik Maes
A Kernel Based Multilinear SVD Approach for Multiple Sclerosis Profiles Classification. - João Gabriel Corrêa Krüger, Jean Paul Barddal, Alceu de Souza Britto Jr.:
A Machine Learning Approach for School Dropout Prediction in Brazil. - Nadzeya Dzemidovich, Alexander Gepperth:
An empirical comparison of generators in replay-based continual learning. - Steven Michiels, Cédric De Schryver, Lynn Houthuys, Frederik Vogeler, Frederik Desplentere:
Machine learning for automated quality control in injection moulding manufacturing. - Luca Oneto, Simone Minisi, Andrea Garrone, Renzo Canepa, Carlo Dambra
Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets. - Mohammadmahdi Ghahramani, Fabio Aiolli:
Price direction prediction in financial markets, using Random Forest and Adaboost.
Learning theory and principles
- Seyedsaman Emami
Multioutput Regression Neural Network Training via Gradient Boosting. - Luca Oneto, Sandro Ridella, Davide Anguita:
Do We Really Need a New Theory to Understand the Double-Descent? - Adrien Pavão, Isabelle Guyon, Zhengying Liu:
Filtering participants improves generalization in competitions and benchmarks. - Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais:
Sliced-Wasserstein normalizing flows: beyond maximum likelihood training. - Oliver Kramer:
A Fast and Simple Evolution Strategy with Covariance Matrix Estimation. - Quinten Van Baelen
Constraint Guided Gradient Descent: Guided Training with Inequality Constraints. - Mirko Polato, Fabio Aiolli, Luca Bergamin, Tommaso Carraro:
Bayes Point Rule Set Learning. - Jirí Tumpach, Jan Koza, Martin Holena:
Neural-network-based estimation of normal distributions in black-box optimization.
Deep learning, signal, image
- Suresh Kirthi Kumaraswamy, Alexey Ozerov, Ngoc Q. K. Duong, Anne Lambert, François Schnitzler, Patrick Fontaine:
Feature Compression Using Dynamic Switches in Multi-split CNNs. - Felix Meyer-Veit, Rania Rayyes, Andreas O. H. Gerstner, Jochen J. Steil:
Hyperspectral Wavelength Analysis with U-Net for Larynx Cancer Detection. - Giovanni Bonetta, Rossella Cancelliere:
Lightening CNN architectures by regularization driven weights' pruning. - Gaëlle Milon-Harnois, Nisrine Jrad, Daniel Schang, Patrick Van Bogaert, Pierre Chauvet:
1D vs 2D convolutional neural networks for scalp high frequency oscillations identification. - Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche:
Deep latent position model for node clustering in graphs. - Matthias Kissel, Klaus Diepold:
Deep Convolutional Neural Networks with Sequentially Semiseparable Weight Matrices. - Joseph Rynkiewicz:
Deep networks with ReLU activation functions can be smooth statistical models. - István Megyeri, Ammar Al-Najjar
PCA improves the adversarial robustness of neural networks. - Nermeen Abou Baker
Battery detection of XRay images using transfer learning. - Lukas Enderich, Simon Heming:
Real-time capable Ensemble Estimation for 2D Object Detection. - Nikhil Kilari, Gaurab Bhattacharya, K. Pavan Kumar Reddy, Jayavardhana Gubbi, Arpan Pal:
Appearance-Context aware Axial Attention for Fashion Landmark Detection. - Rémi Delogne, Vincent Schellekens, Laurent Jacques:
ROP inception: signal estimation with quadratic random sketching. - Mohammed El Amine Mokhtari, Virginie Vandenbulcke, Sohaib Laraba, Matei Mancas, Elias Ennadifi, Mohamed Lamine Tazir, Bernard Gosselin:
Semi-synthetic Data for Automatic Drone Shadow Detection. - Tomasz Gutowski
Deep learning for Parkinson's disease symptom detection and severity evaluation using accelerometer signal.
Anomaly and change point detection
- Madalina Olteanu, Fabrice Rossi, Florian Yger:
Challenges in anomaly and change point detection. - Jean Coussirou, Thomas Vanaret, Jérôme Lacaille:
Anomaly detections on the oil system of a turbofan engine by a neural autoencoder. - Fabian Hinder, André Artelt, Valerie Vaquet, Barbara Hammer:
Contrasting Explanation of Concept Drift. - Yacine Bel-Hadj, Wout Weijtjens, Francisco de Nolasco Santos:
Anomaly detection and representation learning in an instrumented railway bridge.
Deep Semantic Segmentation Models in Computer Vision
- Paolo Andreini, Giovanna Maria Dimitri
Deep Semantic Segmentation Models in Computer Vision. - Daniela Cuza, Andrea Loreggia, Alessandra Lumini, Loris Nanni:
Deep Semantic Segmentation in Skin Detection. - Simone Bonechi:
A weakly supervised approach to skin lesion segmentation. - Paolo Andreini, Niccolò Pancino, Filippo Costanti, Gabriele Eusepi, Barbara Toniella Corradini:
A Deep Learning approach for oocytes segmentation and analysis. - Duccio Meconcelli, Simone Bonechi, Giovanna Maria Dimitri
Deep Learning Approaches for mice glomeruli segmentation. - Lydia Abady, Giovanna Maria Dimitri
Detection and Localization of GAN Manipulated Multi-spectral Satellite Images.
Regression and forecasting
- Matheus Henrique Dal Molin Ribeiro, Sinvaldo Rodrigues Moreno, Ramon Gomes da Silva, José Henrique Kleinübing Larcher, Cristiane Canton, Viviana Cocco Mariani, Leandro dos Santos Coelho:
Wind power forecasting based on bagging extreme learning machine ensemble model. - Michael Potter, Ilkay Yildiz Potter, Octavia I. Camps, Mario Sznaier:
Dynamics-aware Representation Learning via Multivariate Time Series Transformers. - Francisco de Nolasco Santos
Minkowski logarithmic error: A physics-informed neural network approach for wind turbine lifetime assessment. - Neta Rabin, Ben Hen, Ángela Fernández:
Improving Laplacian Pyramids Regression with Localization in Frequency and Time. - Benoît Loucheur, Pierre-Antoine Absil, Michel Journée:
Gap filling in air temperature series by matrix completion methods. - Francisco Pereira, Helio Silva, João Gomes, Javam C. Machado:
Predicting Test Execution Times with Asymmetric Random Forests.
Recurrent learning and reservoir computing
- Andrea Ceni, Claudio Gallicchio:
Orthogonality in Additive Echo State Networks. - Pierre Poitier, Jérôme Fink, Benoît Frénay:
Towards Better Transition Modeling in Recurrent Neural Networks: the Case of Sign Language Tokenization. - Valerio De Caro, Claudio Gallicchio, Davide Bacciu:
Federated Adaptation of Reservoirs via Intrinsic Plasticity. - Arun Pandey
Recurrent Restricted Kernel Machines for Time-series Forecasting. - Luca Argentieri, Claudio Gallicchio, Alessio Micheli
Input Routed Echo State Networks.
Natural language processing, and recommender systems
- Zhengxiang Shi
Attention-based Ingredient Phrase Parser. - Philip Kenneweg
Neural Architecture Search for Sentence Classification with BERT. - David Young, Douglas J. Leith
High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits.
Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine
- Thomas Villmann, Jonas S. Almeida, John A. Lee, Susana Vinga:
Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine. - Ignacio Díaz Blanco, José M. Enguita, Diego García-Pérez, Ana González-Muñiz, Abel Alberto Cuadrado Vega, Maria Dolores Chiara-Romero, Nuria Valdés:
Interactive dual projections for gene expression analysis. - Katrin Sophie Bohnsack, Marika Kaden, Julius Voigt, Thomas Villmann:
Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features. - Ignacio Díaz Blanco, José M. Enguita, Diego García-Pérez, Maria Dolores Chiara-Romero, Nuria Valdés, Ana González-Muñiz, Abel Alberto Cuadrado Vega:
Interactive visual analytics for medical data: application to COVID-19 clinical information during the first wave. - Helen Schneider, David Biesner, Sebastian Nowak, Yannik C. Layer, Maike Theis, Wolfgang Block, Benjamin Wulff, Alois M. Sprinkart
Improving Intensive Care Chest X-Ray Classification by Transfer Learning and Automatic Label Generation.
Concept drift
- Johannes Brinkrolf, Valerie Vaquet, Fabian Hinder, Patrick Menz, Udo Seiffert, Barbara Hammer:
Federated learning vector quantization for dealing with drift between nodes. - Patrick Menz, Valerie Vaquet, Barbara Hammer, Udo Seiffert:
From hyperspectral to multispectral sensing - from simulation to reality: A comprehensive approach for calibration model transfer. - Joanna Komorniczak
Data stream generation through real concept's interpolation.
Deep Learning for Graphs
- Davide Bacciu, Federico Errica, Nicolò Navarin, Luca Pasa, Daniele Zambon:
Deep Learning for Graphs. - Domenico Tortorella
Beyond Homophily with Graph Echo State Networks. - Federico Caldart, Luca Pasa, Luca Oneto, Alessandro Sperduti, Nicolò Navarin:
Biased Edge Dropout in NIFTY for Fair Graph Representation Learning. - Raphaël Romero, Tijl De Bie:
Embedding-based next song recommendation for playlists. - Gaia Saveri:
Graph Neural Networks for Propositional Model Counting. - Francesco Landolfi:
Revisiting Edge Pooling in Graph Neural Networks.
Reinforcement learning
- Oren Neumann, Claudius Gros:
Size Scaling in Self-Play Reinforcement Learning. - Andreas Mazur, André Artelt, Barbara Hammer:
Improving Zorro Explanations for Sparse Observations with Dense Proxy Data. - Oytun Yapar, Erhan Öztop:
Reinforcement learning for constructing low density sign representations of Boolean functions. - Jianyong Xue, Frédéric Alexandre:
Developmental Modular Reinforcement Learning. - Yi Zhao, Rinu Boney, Alexander Ilin, Juho Kannala, Joni Pajarinen
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning.
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-02-15 00:23 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: