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ORCID24th ESANN 2016: Bruges, Belgium
- 24th European Symposium on Artificial Neural Networks, ESANN 2016, Bruges, Belgium, April 27-29, 2016. 2016
Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints
- Luca Oneto, Nicolò Navarin, Michele Donini, Fabio Aiolli, Davide Anguita:
Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints. - Fabio Aiolli, Mirko Polato:
Kernel based collaborative filtering for very large scale top-N item recommendation. - Fabrizio Costa, Parastou Kohvaei, Robert Kleinkauf:
RNAsynth: constraints learning for RNA inverse folding. - Luca Oneto, Nicolò Navarin, Michele Donini, Alessandro Sperduti, Fabio Aiolli, Davide Anguita:
Measuring the Expressivity of Graph Kernels through the Rademacher Complexity. - Davide Bacciu, Claudio Gallicchio, Alessio Micheli:
A reservoir activation kernel for trees. - Giorgio Gnecco, Marco Gori, Stefano Melacci, Marcello Sanguineti:
Learning with hard constraints as a limit case of learning with soft constraints. - Benjamin Paassen, Christina Göpfert, Barbara Hammer:
Gaussian process prediction for time series of structured data. - Piyush Bhardwaj, Harish Karnick:
Efficient low rank approximation via alternating least squares for scalable kernel learning.
Regression and mathematical models
- Witali Aswolinskiy, René Felix Reinhart, Jochen J. Steil:
Modelling of parameterized processes via regression in the model space. - Ángela Fernández, Neta Rabin, Dalia Fishelov, José R. Dorronsoro:
Auto-adaptive Laplacian Pyramids. - Diego P. P. Mesquita, Antônio C. Araújo Neto, Jose Queiroz Neto, João P. P. Gomes, Leonardo Ramos Rodrigues:
Using Robust Extreme Learning Machines to Predict Cotton Yarn Strength and Hairiness. - Mauro Dragone, Claudio Gallicchio, Roberto Guzmán, Alessio Micheli:
RSS-based Robot Localization in Critical Environments using Reservoir Computing. - Adrien Bibal, Benoît Frénay:
Interpretability of machine learning models and representations: an introduction. - Faicel Chamroukhi:
Bayesian mixture of spatial spline regressions. - Cynthia Faure, Jean-Marc Bardet, Madalina Olteanu, Jérôme Lacaille:
Comparison of three algorithms for parametric change-point detection. - Pierre-Antoine Absil, Pierre-Yves Gousenbourger, Paul Striewski, Benedikt Wirth:
Differentiable piecewise-Bézier interpolation on Riemannian manifolds. - Estelle M. Massart, Julien M. Hendrickx, Pierre-Antoine Absil:
Extending a two-variable mean to a multi-variable mean. - Gaetano Liborio Aiello:
neuro-percolation as a superposition of random-walks.
Indefinite proximity learning
- Frank-Michael Schleif
, Peter Tiño, Yingyu Liang:
Learning in indefinite proximity spaces - recent trends. - Alexander Schulz, Barbara Hammer:
Discriminative dimensionality reduction in kernel space. - Gaëlle Loosli:
Study on the loss of information caused by the "positivation" of graph kernels for 3D shapes. - Marika Kaden, David Nebel, Thomas Villmann:
Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities.
Deep learning, text, image and signal processing
- Soufiane Belharbi, Romain Hérault, Clément Chatelain, Sébastien Adam:
Deep multi-task learning with evolving weights. - Thomas Burwick, Luke Ewig:
Deep neural network analysis of go games: which stones motivate a move? - Martin Mundt, Sebastian Blaes, Thomas Burwick:
Feature binding in deep convolution networks with recurrences, oscillations, and top-down modulated dynamics. - Ryo Karakida, Masato Okada, Shun-ichi Amari:
Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold. - Fábio Medeiros Rangel, Fabrício Firmino de Faria, Priscila M. V. Lima, Jonice Oliveira:
Semi-Supervised Classification of Social Textual Data Using WiSARD. - Thiago de Paulo Faleiros, Alneu de Andrade Lopes:
On the equivalence between algorithms for Non-negative Matrix Factorization and Latent Dirichlet Allocation. - Pyry Takala:
Word Embeddings for Morphologically Rich Languages. - Nooshin Maghsoodi, Hossein Sameti, Hossein Zeinali:
Localized discriminative Gaussian process latent variable model for text-dependent speaker verification. - Gueorgui Pironkov, Stéphane Dupont, Thierry Dutoit:
Multi-task learning for speech recognition: an overview. - Albert Vilamala, Alfredo Vellido, Lluís A. Belanche:
Bayesian semi non-negative matrix factorisation. - Stephanie Alvarez Fernandez, Romis Attux, Denis G. Fantinato, Jugurta Montalvão, Daniel G. Silva:
An Immune-Inspired, Dependence-Based Approach to Blind Inversion of Wiener Systems. - Romain Huet, Nicolas Courty, Sébastien Lefèvre:
A new penalisation term for image retrieval in clique neural networks. - Eleni Tsironi, Pablo V. A. Barros, Stefan Wermter:
Gesture Recognition with a Convolutional Long Short-Term Memory Recurrent Neural Network.
Machine learning for medical applications
- Verónica Bolón-Canedo, Beatriz Remeseiro, Amparo Alonso-Betanzos, Aurélio Campilho:
Machine learning for medical applications. - Isaac Fernández-Varela, Elena Hernández-Pereira, Diego Álvarez-Estévez, Vicente Moret-Bonillo:
Automatic detection of EEG arousals. - Sofia Fernandes, Ricardo Gamelas Sousa, Renato Socodato, Luís M. Silva:
Stacked denoising autoencoders for the automatic recognition of microglial cells' state. - Victor Mocioiu, Nuno Miguel Pedrosa de Barros, Sandra Ortega-Martorell, Johannes Slotboom, Urspeter Knecht, Carles Arús, Alfredo Vellido, Margarida Julià-Sapé:
A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases. - Luis Gonçalves, Jorge Novo, Aurélio Campilho:
Feature definition, analysis and selection for lung nodule classification in chest computerized tomography images. - Albert Pla, Beatriz López, Cristofor Nogueira, Natalia Mordvaniuk, Taco J. Blokhuis, Herman R. Holtslag:
Bag-of-Steps: predicting lower-limb fracture rehabilitation length. - Nicolas Sauwen, Marjan Acou, Halandur Nagaraja Bharath, Diana Maria Sima, Jelle Veraart, Frederik Maes, Uwe Himmelreich, Eric Achten, Sabine Van Huffel:
Initializing nonnegative matrix factorization using the successive projection algorithm for multi-parametric medical image segmentation. - María Luisa Sánchez Brea, Noelia Barreira-Rodríguez, Noelia Sánchez-Maroño, Antonio Mosquera González, Carlos García-Resúa, Eva Yebra-Pimentel:
On the analysis of feature selection techniques in a conjunctival hyperemia grading framework. - Borja Seijo-Pardo, Verónica Bolón-Canedo, Amparo Alonso-Betanzos:
Using a feature selection ensemble on DNA microarray datasets. - Oscar Fontenla-Romero, Bertha Guijarro-Berdiñas, Beatriz Pérez-Sánchez, Diego Rego-Fernández, David Martínez-Rego:
A fast learning algorithm for high dimensional problems: an application to microarrays. - Laura Morán-Fernández, Verónica Bolón-Canedo, Amparo Alonso-Betanzos:
Data complexity measures for analyzing the effect of SMOTE over microarrays. - Fernando Mateo, Emilio Soria-Olivas, Marcelino Martínez-Sober, Maria Tellez-Plaza, Juan Gómez-Sanchís, Josep Redon:
Multi-step strategy for mortality assessment in cardiovascular risk patients with imbalanced data. - Emilie Renard, Andrew E. Teschendorff, Pierre-Antoine Absil:
Spatiotemporal ICA improves the selection of differentially expressed genes. - Samaneh Nasiri Ghosheh Bolagh, Mohammad Bagher Shamsollahi, Christian Jutten, Marco Congedo:
Unsupervised Cross-Subject BCI Learning and Classification using Riemannian Geometry. - Silvia Sanromà, Antonio Moreno, Aïda Valls, Pedro Romero-Aroca, Sofia de la Riva-Fernandez, Ramon Sagarra-Alamo:
Assessment of diabetic retinopathy risk with random forests.
Physics and Machine Learning: Emerging Paradigms
- José David Martín-Guerrero, Paulo J. G. Lisboa, Alfredo Vellido:
Physics and Machine Learning: Emerging Paradigms. - Pantita Palittapongarnpim, Peter Wittek, Barry C. Sanders:
Controlling adaptive quantum-phase estimation with scalable reinforcement learning. - Claire Adam-Bourdarios, Glen Cowan, Cécile Germain, Isabelle Guyon, Balázs Kégl, David Rousseau:
How machine learning won the Higgs boson challenge. - Raúl V. Casaña Eslava, José David Martín-Guerrero, Ian H. Jarman, Paulo J. G. Lisboa:
Performance assessment of quantum clustering in non-spherical data distributions. - Leonardo Banchi, Nicola Pancotti, Sougato Bose:
Supervised quantum gate "teaching" for quantum hardware design. - Jacob M. Taylor, Hans J. Briegel, Vedran Dunjko:
Enhanced learning for agents in quantum-accessible environments.
Incremental learning algorithms and applications
- Alexander Gepperth, Barbara Hammer:
Incremental learning algorithms and applications. - Viktor Losing, Barbara Hammer, Heiko Wersing:
Choosing the best algorithm for an incremental on-line learning task. - Oscar Fontenla-Romero, Beatriz Pérez-Sánchez, Bertha Guijarro-Berdiñas, Diego Rego-Fernández:
Distributed learning algorithm for feedforward neural networks. - Christoph Käding, Erik Rodner, Alexander Freytag, Joachim Denzler:
Watch, Ask, Learn, and Improve: a lifelong learning cycle for visual recognition. - Pierre-Xavier Loeffel, Christophe Marsala, Marcin Detyniecki:
Memory management for data streams subject to concept drift. - Thomas Hecht, Alexander Gepperth:
Towards incremental deep learning: multi-level change detection in a hierarchical visual recognition architecture.
Classification
- Guillaume Berger, Clément Peyrard, Moez Baccouche:
Boosting face recognition via neural Super-Resolution. - Kai Lars Polsterer, Fabian Gieseke, Christian Igel, Bernd Doser, Nikolaos Gianniotis:
Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. - David Clifte da S. Vieira, Ajalmar R. da Rocha Neto, Antonio Wendell De Oliveira Rodrigues:
Sparse Least Squares Support Vector Machines via Multiresponse Sparse Regression. - Mina Abdel-Sayed, Daniel Duclos, Gilles Faÿ, Jérôme Lacaille, Mathilde Mougeot:
anomaly detection on spectrograms using data-driven and fixed dictionary representations. - Prateek Veeranna Sappadla, Jinseok Nam, Eneldo Loza Mencía, Johannes Fürnkranz:
Using semantic similarity for multi-label zero-shot classification of text documents. - Tom Diethe, Niall Twomey, Peter A. Flach:
Active transfer learning for activity recognition. - Luca Oneto, Sandro Ridella, Davide Anguita:
Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data. - Ilenia Orlandi, Luca Oneto, Davide Anguita:
Random Forests Model Selection. - Massimo De Gregorio, Maurizio Giordano:
The WiSARD Classifier. - Aurélia Léon, Ludovic Denoyer:
Policy-gradient methods for Decision Trees. - Paavo Nieminen, Tommi Kärkkäinen:
Multicriteria optimized MLP for imbalanced learning. - Luiza Mici, Xavier Hinaut, Stefan Wermter:
Activity recognition with echo state networks using 3D body joints and objects category. - Pekka Siirtola, Heli Koskimäki, Juha Röning:
From User-independent to Personal Human Activity Recognition Models Using Smartphone Sensors. - Diego Fernández-Francos, Oscar Fontenla-Romero, Amparo Alonso-Betanzos:
One-class classification algorithm based on convex hull. - Meriem El Azami, Carole Lartizien, Stéphane Canu:
Converting SVDD scores into probability estimates.
Deep learning
- Plamen Angelov, Alessandro Sperduti:
Challenges in Deep Learning. - Claudio Gallicchio, Alessio Micheli:
Deep Reservoir Computing: A Critical Analysis. - Harm de Vries, Roland Memisevic, Aaron C. Courville:
Deep Learning Vector Quantization. - Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke:
Multispectral Pedestrian Detection using Deep Fusion Convolutional Neural Networks. - Julien Rebetez, Héctor F. Satizábal, Matteo Mota, Dorothea Noll, Lucie Büchi, Marina Wendling, Bertrand Cannelle, Andrés Pérez-Uribe, Stéphane Burgos:
Augmenting a convolutional neural network with local histograms - A case study in crop classification from high-resolution UAV imagery. - Mathias Berglund:
Stochastic gradient estimate variance in contrastive divergence and persistent contrastive divergence. - Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal:
An Experiment in Pre-Emphasizing Diversified Deep Neural Classifiers. - Tommi Kärkkäinen, Jan Hänninen:
Comparison of Four- and Six-Layered Configurations for Deep Network Pretraining. - Ali Ziat, Gabriella Contardo, Nicolas Baskiotis, Ludovic Denoyer:
Learning Embeddings for Completion and Prediction of Relationnal Multivariate Time-Series. - Jonas Degrave, Sander Dieleman, Joni Dambre, Francis Wyffels:
Spatial Chirp-Z Transformer Networks.
Clustering and feature selection
- Tung Pham, Trung Le, Thai Hoang Le, Dat Tran:
Fast Support Vector Clustering. - Rocco Langone, Raghvendra Mall, Vilen Jumutc, Johan A. K. Suykens:
Fast in-memory spectral clustering using a fixed-size approach. - Xiucai Ye, Kaiyang Ji, Tetsuya Sakurai:
Spectral clustering and discriminant analysis for unsupervised feature selection. - Lynn Houthuys, Rocco Langone, Johan A. K. Suykens:
Clustering from two data sources using a kernel-based approach with weight coupling. - Abul Hashem Beg, Md Zahidul Islam:
Genetic Algorithm with Novel Crossover, Selection and Health Check for Clustering. - Bo Zhu, Alberto Mozo, Bruno Ordozgoiti:
PSCEG: an unbiased parallel subspace clustering algorithm using exact grids. - Joonas Hämäläinen, Tommi Kärkkäinen:
Initialization of big data clustering using distributionally balanced folding. - Michael J. Siers, Md Zahidul Islam:
RBClust: High quality class-specific clustering using rule-based classification. - Diego P. P. Mesquita, João P. P. Gomes, Leonardo Ramos Rodrigues:
K-means for Datasets with Missing Attributes: Building Soft Constraints with Observed and Imputed Values. - Gabriel Prat-Masramon, Lluís A. Belanche:
Instance and feature weighted k-nearest-neighbors algorithm. - Zahra Karevan, Johan A. K. Suykens:
Spatio-temporal feature selection for black-box weather forecasting. - Bruno Ordozgoiti, Sandra Gómez Canaval, Alberto Mozo:
Parallelized unsupervised feature selection for large-scale network traffic analysis.
Information Visualisation and Machine Learning: Techniques, Validation and Integration
- Benoît Frénay, Bruno Dumas:
Information visualisation and machine learning: characteristics, convergence and perspective. - Cagatay Turkay, Aidan Slingsby, Kaisa Lahtinen, Sarah Butt, Jason Dykes:
Enhancing a social science model-building workflow with interactive visualisation. - Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodríguez, Bo Kang:
Informative data projections: a framework and two examples. - Dominik Sacha, Michael Sedlmair, Leishi Zhang, John Aldo Lee, Daniel Weiskopf, Stephen C. North, Daniel A. Keim:
Human-centered machine learning through interactive visualization: review and open challenges. - Ignacio Díaz Blanco, Abel Alberto Cuadrado Vega, Michel Verleysen:
A state-space model on interactive dimensionality reduction. - Trevor Barron, Matthew Whitehead:
Visualizing stacked autoencoder language learning. - Frédéric Rayar, Sabine Barrat, Fatma Bouali, Gilles Venturini:
Incremental hierarchical indexing and visualisation of large image collections.
Robotics and reinforcement learning
- Francisco Cruz, German Ignacio Parisi, Stefan Wermter:
Learning contextual affordances with an associative neural architecture. - Matthieu Zimmer, Yann Boniface, Alain Dutech:
Neural fitted actor-critic. - Michael Herman, Tobias Gindele, Jörg Wagner, Felix Schmitt, Wolfram Burgard:
Simultaneous estimation of rewards and dynamics from noisy expert demonstrations. - Juliano Pierezan, Roberto Zanetti Freire, Lucas Weihmann, Gilberto Reynoso-Meza, Leandro dos Santos Coelho:
On the improvement of static force capacity of humanoid robots based on plants behavior. - Alban Laflaquière, Michaël Garcia Ortiz, Ahmed Faraz Khan:
Grounding the experience of a visual field through sensorimotor contingencies. - Johannes Twiefel, Xavier Hinaut, Stefan Wermter:
Semantic Role Labelling for Robot Instructions using Echo State Networks. - Felipe Martins, Marc de Groot, Xeryus Stokkel, Marco A. Wiering:
Human detection and classification of landing sites for search and rescue drones.
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