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		<TitleText textcase="01">ESANN 2018 - Proceedings</TitleText>
		
		<Subtitle textcase="01">26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning</Subtitle>
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		<Text textformat="02">&lt;p&gt;Deep learning and image processing&lt;br /&gt;
A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial&lt;br /&gt;
Expression Recognition&lt;br /&gt;
H. Siqueira, P. Barros, S. Magg, C. Weber, S. Wermter&lt;br /&gt;
Interpretation of convolutional neural networks for speech regression from&lt;br /&gt;
electrocorticography&lt;br /&gt;
M. Angrick, C. Herff, G. Johnson, J. Shih, D. Krusienski, T. Schultz&lt;br /&gt;
Transferring style in motion capture sequences with adversarial learning&lt;br /&gt;
Q. Wang, M. Chen, T. Artières, L. Denoyer&lt;br /&gt;
Properties of adv-1 – Adversarials of Adversarials&lt;br /&gt;
N. Worzyk, O. Kramer&lt;br /&gt;
An analysis of subtask-dependency in robot command interpretation with&lt;br /&gt;
dilated CNNs&lt;br /&gt;
M. Eppe, T. Alpay, F. Abawi, S. Wermter&lt;br /&gt;
Image retrieval and ranking through Deep Comparative Neural Networks&lt;br /&gt;
A. Cherif, S. Jouili&lt;br /&gt;
Incremental learning with deep neural networks using a test-time oracle&lt;br /&gt;
A. Gepperth, S. Abdullah Gondal&lt;br /&gt;
Image-to-Text Transduction with Spatial Self-Attention&lt;br /&gt;
S. Springenberg, E. Lakomkin, C. Weber, S. Wermter&lt;br /&gt;
Hierarchical Recurrent Filtering for Fully Convolutional DenseNets&lt;br /&gt;
J. Wagner, V. Fischer, M. Herman, S. Behnke&lt;br /&gt;
Towards cognitive automotive environment modelling: reasoning based on&lt;br /&gt;
vector representations&lt;br /&gt;
F. Mirus, T. C. Stewart, J. Conradt&lt;br /&gt;
Inferencing based on unsupervised learning of disentangled representations&lt;br /&gt;
T. Hinz, S. Wermter&lt;br /&gt;
Dynamic autonomous image segmentation based on Grow Cut&lt;br /&gt;
A.-I. Marinescu, Z. Bálint, L. Dioşan, A. Andreica&lt;/p&gt;

&lt;p&gt;P. Springstübe, S. Heinrich, S. Wermter&lt;br /&gt;
Active Learning based on Transfer Learning Techniques for Image&lt;br /&gt;
Classification&lt;br /&gt;
D. Onita, A. Birlutiu&lt;br /&gt;
Near-optimal facial emotion classification using a WiSARD-based weightless&lt;br /&gt;
system&lt;br /&gt;
L. Lusquino Filho, F. França, P. Lima&lt;br /&gt;
Spatial pooling as feature selection method for object recognition&lt;br /&gt;
M. Kirtay, L. Vannucci, U. Albanese, A. Ambrosano, E. Falotico, C. Laschi&lt;br /&gt;
Interaction and User Integration in Machine Learning for&lt;br /&gt;
Information Visualisation&lt;br /&gt;
Information visualisation and machine learning: latest trends towards&lt;br /&gt;
convergence&lt;br /&gt;
B. Frenay, B. Dumas, J. A. Lee&lt;br /&gt;
VisCoDeR: A tool for visually comparing dimensionality reduction algorithms&lt;br /&gt;
R. Cutura, S. Holzer, M. Aupetit, M. Sedlmair&lt;br /&gt;
G-Rap: interactive text synthesis using recurrent neural network suggestions&lt;br /&gt;
U. Schlegel, E. Cakmak, J. Buchmüller, D. Keim&lt;br /&gt;
Interactive dimensionality reduction of large datasets using interpolation&lt;br /&gt;
I. Diaz-Blanco, D. Perez, A. A. Cuadrado, D. Garcia-Perez, D. Manuel&lt;br /&gt;
Nonlinear dimensionality reduction&lt;br /&gt;
Perplexity-free t-SNE and twice Student tt-SNE&lt;br /&gt;
C. de Bodt, D. Mulders, M. Verleysen, J. A. Lee&lt;br /&gt;
Generative Kernel PCA&lt;br /&gt;
J. Schreurs, J. Suykens&lt;br /&gt;
Extensive assessment of Barnes-Hut t-SNE&lt;br /&gt;
C. de Bodt, D. Mulders, M. Verleysen, J. A. Lee&lt;br /&gt;
Understanding wafer patterns in semiconductor production with variational&lt;br /&gt;
auto-encoders&lt;br /&gt;
T. Santos, R. Kern&lt;br /&gt;
Feature noise tuning for resource efficient Bayesian Network Classifiers&lt;br /&gt;
L. I. Galindez Olascoaga, J. Vlasselaer, W. Meert, M. Verhelst&lt;br /&gt;
Reliable Patient Classification in Case of Uncertain Class Labels Using a&lt;br /&gt;
Cross-Entropy Approach&lt;br /&gt;
A. Villmann, M. Kaden, S. Saralajew, W. Hermann, T. Villmann&lt;br /&gt;
Behaviour-based working memory capacity classification using recurrent&lt;br /&gt;
neural networks&lt;br /&gt;
M. Salous, F. Putze&lt;br /&gt;
Structuring and Solving Multi-Criteria Decision Making Problems using&lt;br /&gt;
Artificial Neural Networks: a smartphone recommendation case&lt;br /&gt;
V. Amaral De Sousa, A. Simonofski, M. Snoeck, I. Jureta&lt;br /&gt;
Efficient accuracy estimation for instance-based incremental active learning&lt;br /&gt;
C. Limberg, H. Wersing, H. Ritter&lt;br /&gt;
Boolean kernels for interpretable kernel machines&lt;br /&gt;
M. Polato, F. Aiolli&lt;br /&gt;
The minimum effort maximum output principle applied to Multiple Kernel&lt;br /&gt;
Learning&lt;br /&gt;
I. Lauriola, M. Polato, F. Aiolli&lt;br /&gt;
One-class Autoencoder approach to classify Raman spectra outliers&lt;br /&gt;
K. Hofer-Schmitz, P.-H. Nguyen, K. Berwanger&lt;br /&gt;
Radar Based Pedestrian Detection using Support Vector Machine and the&lt;br /&gt;
Micro Doppler Effect&lt;br /&gt;
J. V. Bruneti Severino, A. Zimmer, L. dos Santos Coelho, R. Zanetti Freire&lt;br /&gt;
Opposite neighborhood: a new method to select reference points of minimal&lt;br /&gt;
learning machines&lt;br /&gt;
M. Dias, L. Sousa, A. Rocha Neto, A. Souza Júnior&lt;br /&gt;
A neural network cost function for highly class-imbalanced data sets&lt;br /&gt;
D. Twomey, D. Gorse&lt;br /&gt;
Self-learning assembly systems during ramp-up&lt;br /&gt;
R. Schönherr, M. Knaller, M. Philipp&lt;br /&gt;
Feasibility based Large Margin Nearest Neighbor metric learning&lt;br /&gt;
B. Hosseini, B. Hammer&lt;/p&gt;

&lt;p&gt;Combining latent tree modeling with a random forest-based approach, for&lt;br /&gt;
genetic association studies&lt;br /&gt;
C. Sinoquet, K. Mekhnacha&lt;br /&gt;
Graph based neural networks for automatic classification of multiple sclerosis&lt;br /&gt;
clinical courses&lt;br /&gt;
F. Calimeri, A. Marzullo, C. Stamile, G. Terracina&lt;br /&gt;
Regression and recommendation systems&lt;br /&gt;
Extreme Minimal Learning Machine&lt;br /&gt;
T. Kärkkäinen&lt;br /&gt;
Learning with a Fisher surrogate loss in a small data regime&lt;br /&gt;
M. Djerrab, A. Garcia, F. D'Alché-Buc&lt;br /&gt;
Fast Power system security analysis with Guided Dropout&lt;br /&gt;
B. Donnot, I. Guyon, A. Marot, M. Schoenauer, P. Panciatici&lt;br /&gt;
Neural Networks for Implicit Feedback Datasets&lt;br /&gt;
J. Feigl, M. Bogdan&lt;/p&gt;

&lt;p&gt;Regularize and explicit collaborative filtering with textual attention&lt;br /&gt;
C.-E. Dias, V. Guigue, P. Gallinari&lt;br /&gt;
Adaptive random forests for data stream regression&lt;br /&gt;
H. M. Gomes, J. P. Barddal, L. E. Boiko, A. Bifet&lt;br /&gt;
Cache-efficient Gradient Descent Algorithm&lt;br /&gt;
I. Chakroun, T. Vander Aa, T. Ashby&lt;br /&gt;
Sensitivity analysis for predictive uncertainty&lt;br /&gt;
S. Depeweg, J. M. Hernández-Lobato, S. Udluft, T. Runkler&lt;br /&gt;
Revisiting FISTA for Lasso: Acceleration Strategies Over The Regularization&lt;br /&gt;
Path&lt;br /&gt;
A. Catalina, C. M. Alaíz, J. R. Dorronsoro&lt;br /&gt;
Shallow and Deep models for transfer learning and domain&lt;br /&gt;
adaptation&lt;br /&gt;
Shallow and Deep Models for Domain Adaptation problems&lt;br /&gt;
S. Mehrkanoon, M. Blaschko, J. Suykens&lt;/p&gt;

&lt;p&gt;Unsupervised domain adaptation of deep object detectors&lt;br /&gt;
D. Majumdar, V. Namboodiri&lt;br /&gt;
Machine Learning and Data Analysis in Astroinformatics&lt;br /&gt;
Machine learning and data analysis in astroinformatics&lt;br /&gt;
M. Biehl, K. Bunte, G. Longo, P. Tino&lt;br /&gt;
Anomaly detection in star light curves using hierarchical Gaussian processes&lt;br /&gt;
H. Chen, T. Diethe, N. Twomey, P. Flach&lt;br /&gt;
Latent representations of transient candidates from an astronomical image&lt;br /&gt;
difference pipeline using Variational Autoencoders&lt;br /&gt;
P. Huijse, N. Astorga, P. Estevez, G. Pignata&lt;br /&gt;
Globular Cluster Detection in the Gaia Survey&lt;br /&gt;
M. Mohammadi, R. Peletier, F.-M. Schleif, N. Petkov, K. Bunte&lt;br /&gt;
Stellar formation rates in galaxies using machine learning models&lt;br /&gt;
M. Delli Veneri, S. Cavuoti, M. Brescia, G. Riccio, G. Longo&lt;br /&gt;
Prototype-based analysis of GAMA galaxy catalogue data&lt;br /&gt;
A. Nolte, L. Wang, M. Biehl&lt;br /&gt;
Deep Learning in Bioinformatics and Medicine&lt;br /&gt;
Bioinformatics and medicine in the era of deep learning&lt;br /&gt;
D. Bacciu, P. Lisboa, J. D. Martin, R. Stoean, A. Vellido&lt;br /&gt;
Controlling biological neural networks with deep reinforcement learning&lt;br /&gt;
J. Wülfing, S. Saseendran Kumar, J. Boedecker, M. Riedmiller, U. Egert&lt;br /&gt;
Learning compressed representations of blood samples time series with&lt;br /&gt;
missing data&lt;br /&gt;
F. M. Bianchi, K. Ø. Mikalsen, R. Jenssen&lt;br /&gt;
Sleep staging with deep learning: a convolutional model&lt;br /&gt;
I. Fernández-Varela, D. Athanasakis, S. Parsons, E. Hernández-Pereira,&lt;br /&gt;
V. Moret-Bonillo&lt;br /&gt;
Interpreting deep learning models for ordinal problems&lt;br /&gt;
J. P. Amorim, I. Domingues, P. H. Abreu, J. Santos&lt;/p&gt;

&lt;p&gt;Non-negative Matrix Factorization for Medical Imaging&lt;br /&gt;
M. Atencia, R. Stoean&lt;br /&gt;
Multi-omics data integration using cross-modal neural networks&lt;br /&gt;
I. Bica, P. Velickovic, H. Xiao, P. Lio'&lt;br /&gt;
DEEP: decomposition feature enhancement procedure for graphs&lt;br /&gt;
V. D. Tran, N. Navarin, A. Sperduti&lt;br /&gt;
Deep Echo State Networks for Diagnosis of Parkinson's Disease&lt;br /&gt;
C. Gallicchio, A. Micheli, L. Pedrelli&lt;br /&gt;
Capturing variabilities from Computed Tomography images with Generative&lt;br /&gt;
Adversarial Networks (GANs)&lt;br /&gt;
U. Javaid, J. A. Lee&lt;br /&gt;
Pollen grain recognition using convolutional neural network&lt;br /&gt;
N. Khanzhina, E. Putin, A. Filchenkov, E. Zamyatina&lt;br /&gt;
Randomized Neural Networks&lt;br /&gt;
Randomized Recurrent Neural Networks&lt;br /&gt;
C. Gallicchio, A. Micheli, P. Tino&lt;br /&gt;
Bidirectional deep-readout echo state networks&lt;br /&gt;
F. M. Bianchi, S. Scardapane, S. Løkse, R. Jenssen&lt;br /&gt;
Forecasting Business Failure in Highly Imbalanced Distribution based on&lt;br /&gt;
Delay Line Reservoir&lt;br /&gt;
A. Rodan, P. A. Castillo, H. Faris, A. M. Al-Zoubi, A.M. Mora, H. Jawazneh&lt;br /&gt;
Estimation of the Human Concentration using Echo State Networks&lt;br /&gt;
H. Dashdamirov, S. Basterrech&lt;br /&gt;
Quantifying the Reservoir Quality using Dimensionality Reduction Techniques&lt;br /&gt;
T. Burianek, S. Basterrech&lt;br /&gt;
Clustering and feature selection&lt;br /&gt;
Scalable robust clustering method for large and sparse data&lt;br /&gt;
J. Hämäläinen, T. Kärkkäinen, T. Rossi&lt;br /&gt;
Clustering with decision trees: divisive and agglomerative approach&lt;br /&gt;
L. Castin, B. Frenay&lt;/p&gt;

&lt;p&gt;Comparison of cluster validation indices with missing data&lt;br /&gt;
M. Niemelä, S. Äyrämö, T. Kärkkäinen&lt;br /&gt;
Efficient approximate representations for computationally expensive features&lt;br /&gt;
R. Santos-Rodriguez, N. Twomey&lt;br /&gt;
Regularised maximum-likelihood inference of mixture of experts for regression&lt;br /&gt;
and clustering&lt;br /&gt;
B. T. Huynh, F. Chamroukhi&lt;br /&gt;
Feature selection for label ranking&lt;br /&gt;
N. Sánchez-Maroño, B. Pérez-Sánchez&lt;br /&gt;
A novel filter algorithm for unsupervised feature selection based on a space&lt;br /&gt;
filling measure&lt;br /&gt;
M. Laib, M. Kanevski&lt;br /&gt;
Mathematical aspects of learning, and reinforcement learning&lt;br /&gt;
Asymptotic statistics for multilayer perceptron with ReLu hidden units&lt;br /&gt;
J. Rynkiewicz&lt;br /&gt;
Local Rademacher Complexity Machine&lt;br /&gt;
L. Oneto, S. Ridella, D. Anguita&lt;br /&gt;
A sharper bound on the Rademacher complexity of margin multi-category&lt;br /&gt;
classifiers&lt;br /&gt;
K. Musayeva, F. Lauer, Y. Guermeur&lt;br /&gt;
Slowness-based neural visuomotor control with an Intrinsically motivated&lt;br /&gt;
Continuous Actor-Critic&lt;br /&gt;
M. B. Hafez, M. Kerzel, C. Weber, S. Wermter&lt;br /&gt;
A variable projection method for block term decomposition of higher-order&lt;br /&gt;
tensors&lt;br /&gt;
G. Olikier, P.-A. Absil, L. De Lathauwer&lt;br /&gt;
Reinforcement Learning for High-Frequency Market Making&lt;br /&gt;
Y.-S. Lim, D. Gorse&lt;/p&gt;

&lt;p&gt;Emerging trends in machine learning: beyond conventional&lt;br /&gt;
methods and data&lt;br /&gt;
Emerging trends in machine learning: beyond conventional methods and data&lt;br /&gt;
L. Oneto, N. Navarin, M. Donini, D. Anguita&lt;br /&gt;
Finding the most interpretable MDS rotation for sparse linear models based on&lt;br /&gt;
external features&lt;br /&gt;
A. Bibal, R. Marion, B. Frenay&lt;br /&gt;
Mixture of Hidden Markov Model as Tree Encoder&lt;br /&gt;
D. Bacciu, D. Castellana&lt;br /&gt;
Set point thresholds from topological data analysis and an outlier detector&lt;br /&gt;
A. Carrega&lt;br /&gt;
Differential private relevance learning&lt;br /&gt;
J. Brinkrolf, K. Berger, B. Hammer&lt;br /&gt;
On aggregation in ranking median regression&lt;br /&gt;
S. Clémençon, A. Korba&lt;br /&gt;
Temporal transfer learning for drift adaptation&lt;br /&gt;
D. Won, P. Jansen, J. Carbonell&lt;br /&gt;
LANN-DSVD: A privacy-preserving distributed algorithm for machine&lt;br /&gt;
learning&lt;br /&gt;
O. Fontenla-Romero, B. Guijarro-Berdiñas, B. Pérez-Sánchez,&lt;br /&gt;
M. Gómez-Casal&lt;br /&gt;
Vector Field Based Neural Networks&lt;br /&gt;
D. Vieira, F. Rangel, F. Firmino, J. Paixao&lt;br /&gt;
Temporal data, sequences and incremental learning&lt;br /&gt;
Non-Negative Tensor Dictionary Learning&lt;br /&gt;
A. Traoré, M. Berar, A. Rakotomamonjy&lt;br /&gt;
An extension of nonstationary fuzzy sets to heteroskedastic fuzzy time series&lt;br /&gt;
M. A. Alves, P. Cândido de Lima e Silva, C. A. Severiano Junior,&lt;br /&gt;
G. Linhares Vieira, F. Gadelha Guimarães, H. Javedani Sadaei&lt;br /&gt;
Surprisal-based activation in recurrent neural networks&lt;br /&gt;
T. Alpay, F. Abawi, S. Wermter&lt;/p&gt;

&lt;p&gt;K-spectral centroid: extension and optimizations&lt;br /&gt;
B. Conan-Guez, A. Gély, L. Boudjeloud-Assala, A. Blansché&lt;br /&gt;
Temporal modeling of ALS using longitudinal data and long-short term&lt;br /&gt;
memory-based algorithm&lt;br /&gt;
A. Nahon, B. Lerner&lt;/p&gt;

&lt;p&gt;Meerkats-inspired Algorithm for Global Optimization Problems&lt;br /&gt;
C. E. Klein, L. dos Santos Coelho&lt;br /&gt;
Cheetah Based Optimization Algorithm: A Novel Swarm Intelligence&lt;br /&gt;
Paradigm&lt;br /&gt;
C. E. Klein, V. Cocco Mariani, L. dos Santos Coelho&lt;br /&gt;
Evolutionary Composition of Customized Fault Localization Heuristics&lt;br /&gt;
D. de-Freitas, L.-J. Plinio, C. Camilo-Junior, R. Harrison&lt;br /&gt;
Order Crossover for the Inventory Routing Problem&lt;br /&gt;
M. S. Amri Sakhri, M. Tlili, H. Allaoui, O. Korbaa&lt;br /&gt;
Person Identification and Discovery With Wrist Worn Accelerometer Data&lt;br /&gt;
R. McConville, R. Santos-Rodriguez, N. Twomey&lt;br /&gt;
CDTW-based classification for Parkinson's Disease diagnosis&lt;br /&gt;
N. Khoury, F. Attal, Y. Amirat, A. Chibani, S. Mohammed&lt;br /&gt;
Personalizing human activity recognition models using incremental learning&lt;br /&gt;
P. Siirtola, H. Koskimäki, J. Röning&lt;br /&gt;
Short-term Memory of Deep RNN&lt;br /&gt;
C. Gallicchio&lt;br /&gt;
Effect of context in swipe gesture-based continuous authentication on&lt;br /&gt;
smartphones&lt;br /&gt;
P. Siirtola, J. Komulainen, V. Kellokumpu&lt;br /&gt;
Impact of Biases in Big Data&lt;br /&gt;
Impact of Biases in Big Data&lt;br /&gt;
P. Glauner, P. Valtchev, R. State&lt;br /&gt;
Analysis of imputation bias for feature selection with missing data&lt;br /&gt;
B. Seijo-Pardo, A. Alonso-Betanzos, K. Bennett, V. Bolon-Canedo, I. Guyon,&lt;br /&gt;
J. Josse, M. Saeed&lt;br /&gt;
Systematics aware learning : a case study in high energy physics&lt;br /&gt;
V. Estrade, C. Germain, I. Guyon, D. Rousseau&lt;br /&gt;
Optimization and metaheuristics&lt;br /&gt;
Evolutionary RL for Container Loading&lt;br /&gt;
S. Saikia, R. Verma, P. Agarwal, G. Shroff, L. Vig, A. Srinivasan&lt;br /&gt;
Enhancement of a stochastic Markov-blanket framework with ant colony&lt;br /&gt;
optimization, to uncover epistasis in genetic association studies&lt;br /&gt;
C. Sinoquet, C. Niel&lt;/p&gt;

&lt;p&gt;Meerkats-inspired Algorithm for Global Optimization Problems&lt;br /&gt;
C. E. Klein, L. dos Santos Coelho&lt;br /&gt;
Cheetah Based Optimization Algorithm: A Novel Swarm Intelligence&lt;br /&gt;
Paradigm&lt;br /&gt;
C. E. Klein, V. Cocco Mariani, L. dos Santos Coelho&lt;br /&gt;
Evolutionary Composition of Customized Fault Localization Heuristics&lt;br /&gt;
D. de-Freitas, L.-J. Plinio, C. Camilo-Junior, R. Harrison&lt;br /&gt;
Order Crossover for the Inventory Routing Problem&lt;br /&gt;
M. S. Amri Sakhri, M. Tlili, H. Allaoui, O. Korbaa&lt;/p&gt;</Text>
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