ESANN 2023 - Proceedings

Contents

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Graph Representation Learning

Graph Representation Learning

D. Bacciu, F. Errica, A. Micheli, N. Navarin, L. Pasa, M. Podda, D. Zambon ....... 

Richness of Node Embeddings in Graph Echo State Networks

D. Tortorella, A. Micheli ....................................................................................... 

An Empirical Study of Over-Parameterized Neural Models based on Graph

Random Features

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

Convolutional Transformer via Graph Embeddings for Few-shot Toxicity and

Side Effect Prediction

L. Torres, B. Ribeiro, J. Arrais ..............................................................................

Hidden Markov Models for Temporal Graph Representation Learning

F. Errica, A. Gravina, D. Bacciu, A. Micheli ........................................................

A Tropical View of Graph Neural Networks

F. Landolfi, D. Bacciu, D. Numeroso ....................................................................

Graph-based Categorical Embedding

W. Wang, S. Bromuri, M. Dumontier .....................................................................

FouriER: Link Prediction by Mixing Tokens with Fourier-enhanced

MetaFormer

T. Vu, H. Ngo, B. Le, T. Le .................................................................................... 

 

Feature selection and dimension reduction

Feature Selection for Concept Drift Detection

F. Hinder, B. Hammer ........................................................................................... 

Improved Interpretation of Feature Relevances: Iterated Relevance Matrix

Analysis (IRMA)

M. Biehl, S. Lövdal ................................................................................................ 

Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed

Landmark Selection

M. Münch, K. S. Bohnsack, A. Engelsberger, F.-M. Schleif, T. Villmann ............. 

Improved the locally aligned ant technique (LAAT) strategy to recover

manifolds embedded in strong noise

F. Contreras, K. Bunte, R. Peletier ........................................................................ 

Nesterov momentum and gradient normalization to improve t-SNE convergence

and neighborhood preservation, without early exaggeration

P. Lambert, J. Lee, E. Couplet, C. de Bodt ............................................................ 

On Feature Removal for Explainability in Dynamic Environments

F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer .................................... 

Robust Feature Selection and Robust Training to Cope with Hyperspectral

Sensor Shifts

V. Vaquet, J. Brinkrolf, B. Hammer ....................................................................... 

A Counterexample to Ockham's Razor and the Curse of Dimensionality:

Marginalising Complexity and Dimensionality for GMMs

B. Frénay ............................................................................................................... 

Feature Selection for Multi-label Classification with Minimal Learning

Machine

J. Linja, J. Hämäläinen, T. Kärkkäinen ............................................................... 

Learning with Boosting Decision Stumps for Feature Selection in Evolving

Data Streams

D. Nowak-Assis .................................................................................................... 

 

Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness

Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness

M. Pintor, A. Demontis, B. Biggio ....................................................................... 

Secure Federated Learning with Kernel Affine Hull Machines

M. Kumar, B. Moser, L. Fischer .......................................................................... 

Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization

G. Piras, G. Floris, R. Mura, L. Scionis, M. Pintor, B. Biggio, A. Demontis ...... 

On the Limitations of Model Stealing with Uncertainty Quantification Models

D. Pape, S. Däubener, T. Eisenhofer, A. E. Cinà, L. Schönherr..........................

Towards Randomized Algorithms and Models that We Can Trust:

a Theoretical Perspective

L. Oneto, S. Ridella, D. Anguita ..........................................................................

Single-pass uncertainty estimation with layer ensembling for regression:

application to proton therapy dose prediction for head and neck cancer

A. M. Barragan Montero, R. Tilman, M. Huet-Dastarac, J. Lee .........................

 

Fairness and Interpretability, Clustering, and NLP

Mixture of stochastic block models for multiview clustering

K. De Santiago, M. Szafranski, C. Ambroise .......................................................

Fine-tuning is not (always) overfitting artifacts

J. Bogaert, E. Jean, C. de Bodt, F.-X. Standaert ................................................. 

On Instance Weighted Clustering Ensembles

P. Moggridge, N. Helian, Y. Sun, M. Lilley ......................................................... 

Rethink the Effectiveness of Text Data Augmentation: An Empirical Analysis

Z. Shi, A. Lipani ................................................................................................... 

Similarity versus Supervision: Best Approaches for HS Code Prediction

S. Stassin, O. Amel, S. A. Mahmoudi, X. Siebert .................................................. 

Multimodal Approach for Harmonized System Code Prediction

O. Amel, S. Stassin, S. A. Mahmoudi, X. Siebert .................................................. 

Mitigating Robustness Bias: Theoretical Results and Empirical Evidences

D. Franco, L. Oneto, D. Anguita ......................................................................... 

End-to-End Neural Network Training for Hyperbox-Based Classification

D. Martins, C. Lülf, F. Gieseke ............................................................................ 

TabSRA: An Attention based Self-Explainable Model for Tabular Learning

K. M. Amekoe, M. D. Dilmi, H. Azzag, Z. Chelly Dagdia, M. Lebbah, G. Jaffre 

Improving Fairness via Intrinsic Plasticity in Echo State Networks

A. Ceni, D. Bacciu, V. De Caro, C. Gallicchio, L. Oneto .................................... 

Is Boredom an Indicator on the way to Singularity of Artificial Intelligence?

Hypotheses as Thought-Provoking Impulse

M. Bogdan ........................................................................................................... 

Adversarial Auditing of Machine Learning Models under Compound Shift

K. Bhanot, D. Wei, I. Baldini, K. Bennett ............................................................ 

Language Modeling in Logistics: Customer Calling Prediction

X. Chen, G. Anerdi, D. Tan, S. Bromuri .............................................................. 

Combining Stochastic Explainers and Subgraph Neural Networks can Increase

Expressivity and Interpretability

I. Spinelli, M. Guerra, F. Bianchi, S. Scardapane ...............................................

 

Quantum Artificial Intelligence

Quantum Artificial Intelligence: A tutorial

J. D. Martín-Guerrero, L. Lamata, T. Villmann .................................................. 

Quantum Feature Selection with Variance Estimation

A. Poggiali, A. Bernasconi, A. Berti, G. Del Corso, R. Guidotti ......................... 

Logarithmic Quantum Forking

A. Berti ................................................................................................................. 

Quantum-ready vector quantization: Prototype learning as a binary

optimization problem

A. Engelsberger, T. Villmann .............................................................................. 

Potential analysis of a Quantum RL controller in the context of autonomous

driving

M. L. Hickmann, A. Raulf, F. Köster, F. Schwenker, H.-M. Rieser ..................... 

 

Green Machine Learning

Green Machine Learning

V. Bolón-Canedo, L. Morán-Fernández, B. Cancela, A. Alonso-Betanzos .........

Logarithmic division for green feature selection: an information-theoretic

approach

S. Suárez-Marcote, L. Morán-Fernández, V. Bolón-Canedo ...............................

Efficient feature selection for domain adaptation using Mutual Information

Maximization

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

Automated green machine learning for condition-based maintenance

A. Lourenco, C. Ferraz, J. Meira, G. Marreiros, V. Bolón-Canedo,

A. Alonso-Betanzos .............................................................................................. 

Multispectral Texture Classification in Agriculture

M. Shumska, K. Bunte ..........................................................................................

 

Reinforcement learning and Evolutionary computation

DEFENDER: DTW-Based Episode Filtering Using Demonstrations for

Enhancing RL Safety

A. Correia, L. Alexandre...................................................................................... 

Automatic Trade-off Adaptation in Offline RL

P. Swazinna, S. Udluft, T. Runkler....................................................................... 

Enhancing Evolution Strategies with Evolution Path Bias

O. Kramer ............................................................................................................ 

Multi-Fidelity Reinforcement Learning with Control Variates

S. Khairy, P. Balaprakash ...................................................................................

Sun Tracking using a Weightless Q-Learning Neural Network

G. Souza, P. Lima, F. França .............................................................................. 

A model-based approach to meta-Reinforcement Learning: Transformers and

tree search

B. Pinon, R. Jungers, J.-C. Delvenne................................................................... 

Derivative-Free Optimization Approaches for Force Polytopes Prediction

G. Laisné, N. Rezzoug, J.-M. Salotti ....................................................................

Policy-Based Reinforcement Learning in the Generalized Rock-Paper-Scissors

Game

I. G. Mali, G. Czibula .......................................................................................... 

 

Classification

Performance Evaluation of Activation Functions in Extreme Learning Machine

K. Struniawski, A. Konopka, R. Kozera ............................................................... 

Evaluating Curriculum Learning Strategies for Pancreatic Cancer Prediction

E. Mosqueira-Rey, D. Vázquez-Lema, E. Hernández-Pereira ............................. 

Improving the DRASiW performance by exploiting its own "Mental Images"

G. Coda, M. De Gregorio, A. Sorgente, P. Vanacore .......................................... 

Efficient Knowledge Aggregation Methods for Weightless Neural Networks

O. Napoli, A. M. de Almeida, J. M. S. Dias, L. B. Rosário, E. Borin,

M. Breternitz Jr.................................................................................................... 

Learning Vector Quantization in Context of Information Bottleneck Theory

M. Mohannazadeh Bakhtiari, D. Staps, T. Villmann ........................................... 

SOM-based Classification and a Novel Stopping Criterion for Astroparticle

Applications

L. Sanchez, E. Merényi, C. Tunnell ..................................................................... 

WiSARD-based Ensemble Learning

L. Lusquino Filho, F. França, P. Lima ................................................................ 

 

Deep learning and Computer vision

Entropy Based Regularization Improves Performance in the Forward-Forward

Algorithm

M. Pardi, D. Tortorella, A. Micheli .....................................................................

On the number of latent representations in deep neural networks for tabular

data

E. Couplet, P. Lambert, M. Verleysen, J. Lee, C. de Bodt ...................................

CRE: Circle relationship embedding of patches in vision transformer

Z. Yu, J. Triesch ................................................................................................... 

Introducing Convolutional Channel-wise Goodness in Forward-Forward

Learning

A. Papachristodoulou, C. Kyrkou, S. Timotheou, T. Theocharides ..................... 

An Alternating Minimization Algorithm with Trajectory for Direct Exoplanet

Detection

H. Daglayan, S. Vary, P.-A. Absil ........................................................................

On Transformer Autoregressive Decoding for Multivariate Time Series

Forecasting

M. Aldosari, J. Miller ..........................................................................................

Don't waste SAM

N. Abou Baker, U. Handmann ............................................................................. 

Layered Neural Networks with GELU Activation, a Statistical Mechanics

Analysis

F. Richert, M. Straat, E. Oostwal, M. Biehl ......................................................... 

Real-time Detection of Evoked Potentials by Deep Learning: a Case Study

L. Amato, M. Maschietto, A. Leparulo, M. Tambaro, S. Vassanelli,

A. Sperduti ........................................................................................................... 

Coordinate descent on the Stiefel manifold for deep neural network training

E. Massart, V. Abrol ............................................................................................ 

Action-Based ADHD Diagnosis in Video

Y. Li, Y. Yang, R. Nair, M. Naqvi ......................................................................... 

Hierarchical priors for Hyperspherical Prototypical Networks

S. Fonio, L. Paletto, M. Cerrato, D. Ienco, R. Esposito ......................................

Segmentation and Analysis of Lumbar Spine MRI Scans for Vertebral Body

Measurements

H. Schneider, D. Biesner, A. Ashokan, M. Broß, R. Kador, S. Halscheidt,

G. Bagyo, P. Dankerl, H. Ragab, J. Yamamura, C. Labisch, R. Sifa................... 

Retinal blood vessel segmentation from high resolution fundus image using

deep learning architecture

H. boudegga, Y. Elloumi, A. Ben Abdallah, R. Kachouri, M. H. Bedoui .............

Graph for Transformer Feature: A New Approach for Face Anti-Spoofing

Q.-H. Trinh, H. Nguyen, V. Nguyen, X.-M. Nguyen, H.-D. Nguyen .................... 

Temporal Ensembling-based Deep k-Nearest Neighbours for Learning with

Noisy Labels

A.-I. Albu ............................................................................................................. 

Evaluation of Contrastive Learning for Electronic Component Detection

L. Silva, A. Freire, B. Fernandes, G. Azevedo, S. Oliveira .................................. 

 

Sequential data, and Meta-learning

Revisiting the Mark Conditional Independence Assumption in Neural Marked

Temporal Point Processes

T. Bosser, S. Ben Taieb ........................................................................................ 

A Protocol for Continual Explanation of SHAP

A. Cossu, F. Spinnato, R. Guidotti, D. Bacciu ..................................................... 

Residual Reservoir Computing Neural Networks for Time-series Classification

C. Gallicchio, A. Ceni .......................................................................................... 

Probabilistic Adaptation for Meta-Learning

T. Adel..................................................................................................................

A hidden Markov model with Hawkes process-derived contextual variables to

improve time series prediction. Case study in medical simulation.

F. Dama, C. Sinoquet, C. Lejus-Bourdeau .......................................................... 

Deep dynamic co-clustering of streams of count data: a new online Zip-dLBM

G. Marchello, M. Corneli, C. Bouveyron ............................................................ 

Communication-Efficient Ridge Regression in Federated Echo State Networks

V. De Caro, A. Di Mauro, D. Bacciu, C. Gallicchio ...........................................

Simultaneous failures classification in a predictive maintenance case

A. Hubermont, E. tuci, N. De Quattro ................................................................. 

Hybrid modelling of dynamic anaerobic digestion process in full-scale with

LSTM NN and BMP measurements

A. Meola, S. Weinrich .......................................................................................... 

Wind Power Prediction with ETSformer

O. Kramer, J. Baumann ....................................................................................... 

Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?

R. Egele, I. Guyon, Y. Sun, P. Balaprakash ......................................................... 

 

Machine Learning Applied to Sign Language

Trends and Challenges for Sign Language Recognition with Machine Learning

J. Fink, M. De Coster, J. Dambre, B. Frénay ......................................................

Multimodal Recognition of Valence, Arousal and Dominance via Late-Fusion

of Text, Audio and Facial Expressions

F. Nunnari, A. Rios, U. Reichel, C. Bhuvaneshwara, P. Filntisis, P. Maragos,

F. Burkhardt, F. Eyben, B. Schuller, S. Ebling .................................................... 

Exploring Strategies for Modeling Sign Language Phonology

L. Kezar, T. Srinivasan, R. Carlin, J. Thomason, Z. Sevcikova Sehyr,

N. Caselli ............................................................................................................. 

Exploring the Importance of Sign Language Phonology for a Deep Neural

Network

J. Martinez Rodriguez, M. Larson, L. ten Bosch .................................................

Large-scale dataset and benchmarking for hand and face detection focused on

sign language

A. L. Cavalcante Carneiro, D. H. Pinheiro Salvadeo, L. Brito Silva ..................

Disambiguating Signs: Deep Learning-based Gloss-level Classification for

German Sign Language by Utilizing Mouth Actions

D. N. Pham, V. Czehmann, E. Avramidis ............................................................ 

 

Efficient Learning in Spiking Neural Networks

Efficient Learning in Spiking Models

A. Rast, M. A. Aoun, E. Elia, N. Crook ................................................................ 

Spiking neural networks with Hebbian plasticity for unsupervised

representation learning

N. B. Ravichandran, A. Lansner, P. Herman ....................................................... 

Functional Resonant Synaptic Clusters for Decoding Time-Structured Spike

Trains

N. Crook, A. Rast, E. Elia, M. A. Aoun ................................................................

Pattern Recognition Spiking Neural Network for Classification of Chinese

Characters

N. Russo, W. Yuzhong, T. Madsen, K. Nikolic ..................................................... 

Energy-efficient detection of a spike sequence

L. Le Coeur, N. Riedman, S. Sarup, K. Boahen ...................................................

 

Anomaly Detection, and Learning Algorithms

Anomaly detection in irregular image sequences for concentrated solar power

plants

S. Patra, T. K. H. Le, S. Ben Taieb ...................................................................... 

Knowledge Distillation for Anomaly Detection

A. A. Pol, E. Govorkova, S. Gronroos, N. Chernyavskaya, P. Harris,

M. Pierini, I. Ojalvo, P. Elmer............................................................................. 

Comparative study of the synfire chain and ring attractor model for timing in

the premotor nucleus in male Zebra Finches

F. Hyseni, N. Rougier, A. Leblois ........................................................................ 

Don't skip the skips: autoencoder skip connections improve latent

representation discrepancy for anomaly detection

A.-S. Collin, C. de Bodt, D. Mulders, C. De Vleeschouwer ................................. 

Variants of Neural Gas for Regression Learning

T. Villmann, R. Schubert, M. Kaden ....................................................................

Hybrid Deep Learning-Based Air and Water Quality Prediction Model

J. Yoon, D. Yu, Y. lee ...........................................................................................

Sleep analysis in a CLIS patient using soft-clustering: a case study

S. Adama, M. Bogdan .......................................................................................... 

FairBayRank: A Fair Personalized Bayesian Ranker

A. Noulapeu Ngaffo, J. Albert, B. Frénay, G. Perrouin ....................................... 

Robust and Cheap Safety Measure for Exoskeletal Learning Control with

Estimated Uniform PAC (EUPAC)

F. Weiske, J. Jäkel ............................................................................................... 

Author index ................................................................................................ 

Committees ...................................................................................................

 

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