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ORCID25th ESANN 2017: Bruges, Belgium
- 25th European Symposium on Artificial Neural Networks, ESANN 2017, Bruges, Belgium, April 26-28, 2017. 2017
Deep and kernel methods: best of two worlds
- Lluís Belanche, Marta R. Costa-jussà:
Bridging deep and kernel methods. - Dhanesh Ramachandram, Michal Lisicki, Timothy J. Shields, Mohamed R. Amer, Graham W. Taylor:
Structure optimization for deep multimodal fusion networks using graph-induced kernels. - Siamak Mehrkanoon, Andreas Zell, Johan A. K. Suykens:
Scalable Hybrid Deep Neural Kernel Networks. - Ivano Lauriola, Michele Donini, Fabio Aiolli:
Learning dot-product polynomials for multiclass problems. - Michiel van der Ree, Jos B. T. M. Roerdink, Christophe Phillips, Gaëtan Garraux, Eric Salmon, Marco A. Wiering:
Support vector components analysis. - Ehsan Sadrfaridpour, Sandeep Jeereddy, Ken Kennedy, André Luckow, Talayeh Razzaghi, Ilya Safro:
Algebraic multigrid support vector machines. - Stephan Baier, Sigurd Spieckermann, Volker Tresp:
Attention-based Information Fusion using Multi-Encoder-Decoder Recurrent Neural Networks. - Danut Ovidiu Pop, Alexandrina Rogozan, Fawzi Nashashibi, Abdelaziz Bensrhair:
Fusion of Stereo Vision for Pedestrian Recognition using Convolutional Neural Networks. - Alan Mosca, George D. Magoulas:
Training convolutional networks with weight-wise adaptive learning rates. - Muthuvel Murugan Issakkimuthu, K. V. Subrahmanyam:
Invariant representations of images for better learning. - Samuel Giatti Silva Filho, Roberto Zanetti Freire, Leandro dos Santos Coelho:
Feature Extraction for On-Road Vehicle Detection Based on Support Vector Machine. - Wolfgang Groß, Sascha Lange, Joschka Bödecker, Manuel Blum:
Predicting Time Series with Space-Time Convolutional and Recurrent Neural Networks.
Randomized Machine Learning approaches: analysis and developments
- Claudio Gallicchio, José David Martín-Guerrero, Alessio Micheli, Emilio Soria-Olivas:
Randomized Machine Learning Approaches: Recent Developments and Challenges. - Peter Tiño:
Fisher memory of linear Wigner echo state networks. - Luca Oneto, Sandro Ridella, Davide Anguita:
Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions. - Davide Bacciu, Michele Colombo, Davide Morelli, David Plans:
ELM Preference Learning for Physiological Data. - Anton Akusok, Emil Eirola, Yoan Miché, Andrey Gritsenko, Amaury Lendasse:
Advanced query strategies for Active Learning with Extreme Learning Machines. - Piotr Iwo Wójcik, Marcin Kurdziel:
Random projection initialization for deep neural networks.
Classification
- Tuan Do, James Pustejovsky:
Fine-grained event learning of human-object interaction with LSTM-CRF. - Bac Nguyen, Carlos Morell, Bernard De Baets:
Distance metric learning: a two-phase approach. - Benjamin Paassen, Alexander Schulz, Janne Hahne, Barbara Hammer:
An EM transfer learning algorithm with applications in bionic hand prostheses. - Luca Oneto, Anna Siri, Gianvittorio Luria, Davide Anguita:
Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach. - Eleonora D'Andrea, Fabio Di Francesco, Valentina Dini, Beatrice Lazzerini, Marco Romanelli, Pietro Salvo:
Physical activity recognition from sub-bandage sensors using both feature selection and extraction. - Romero F. A. B. de Morais, Péricles B. C. de Miranda, Ricardo M. A. Silva:
A multi-criteria meta-learning method to select under-sampling algorithms for imbalanced datasets. - Yasir Hamid, Ludovic Journaux, John Aldo Lee, Lucile Sautot, Nabi Bushra, M. Sugumaran:
Large-scale nonlinear dimensionality reduction for network intrusion detection. - Cem Karaoguz, Alexander Gepperth:
Acceleration of Prototype Based Models with Cascade Computation. - Rafael Adnet Pinho, Walkir Brito, Cláudia Lage Rebello da Motta, Priscila Lima:
Automatic crime report classi cation through a weightless neural network. - Danilo Silva de Carvalho, Minh-Le Nguyen:
Efficient Neural-based patent document segmentation with Term Order Probabilities.
Biomedical data analysis in translational research: integration of expert knowledge and interpretable models
- Gyan Bhanot, Michael Biehl, Thomas Villmann, Dietlind Zühlke:
Biomedical data analysis in translational research: integration of expert knowledge and interpretable models. - Christina Göpfert, Lukas Pfannschmidt, Barbara Hammer:
Feature Relevance Bounds for Linear Classification. - Olli-Pekka Rinta-Koski, Simo Särkkä, Jaakko Hollmén, Markus Leskinen, Sture Andersson:
Prediction of preterm infant mortality with Gaussian process classification. - Sreejita Ghosh, Elizabeth Sarah Baranowski, Rick van Veen, Gert-Jan de Vries, Michael Biehl, Wiebke Arlt, Peter Tiño, Kerstin Bunte:
Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders.
Environmental signal processing: new trends and applications
- Matthieu Puigt, Gilles Delmaire, Gilles Roussel:
Environmental signal processing: new trends and applications. - John Murray-Bruce, Pier Luigi Dragotti:
Solving Inverse Source Problems for Sources with Arbitrary Shapes using Sensor Networks. - Manuel Lopez-Radcenco, Abdeldjalil Aïssa-El-Bey, Pierre Ailliot, Ronan Fablet:
Non-negative decomposition of geophysical dynamics. - Charlotte Revel, Yannick Deville, Véronique Achard, Xavier Briottet:
Impact of the initialisation of a blind unmixing method dealing with intra-class variability. - Michalis Giannopoulos, Sofia Savvaki, Grigorios Tsagkatakis, Panagiotis Tsakalides:
Application of Tensor and Matrix Completion on Environmental Sensing Data. - Rachid Ouaret, Anda Ionescu, Olivier Ramalho, Yves Candau:
Indoor air pollutant sources using Blind Source Separation Methods. - Andreu González-Calabuig, Georgina Faura, Manel del Valle:
High dimensionality voltammetric biosensor data processed with artificial neural networks.
Kernels, graphs and clustering
- Shuyu Dong, Dorina Thanou, Pierre-Antoine Absil, Pascal Frossard:
Learning sparse models of diffusive graph signals. - Dinh Tran-Van, Alessandro Sperduti, Fabrizio Costa:
The Conjunctive Disjunctive Node Kernel. - Maryam Abdollahyan, Fabrizio Smeraldi:
POKer: a Partial Order Kernel for Comparing Strings with Alternative Substrings. - Jérôme Mariette, Fabrice Rossi, Madalina Olteanu, Nathalie Villa-Vialaneix:
Accelerating stochastic kernel SOM. - Vahan Petrosyan, Alexandre Proutière:
Viral initialization for spectral clustering. - Nicolò Navarin, Alessandro Sperduti:
Approximated Neighbours MinHash Graph Node Kernel. - Michele Donini, Nicolò Navarin, Ivano Lauriola, Fabio Aiolli, Fabrizio Costa:
Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning. - Susanne Jauhiainen, Tommi Kärkkäinen:
A Simple Cluster Validation Index with Maximal Coverage. - Patrick O. Glauner, Manxing Du, Victor Paraschiv, Andrey Boytsov, Isabel Lopez Andrade, Jorge Augusto Meira, Petko Valtchev, Radu State:
The Top 10 Topics in Machine Learning Revisited: A Quantitative Meta-Study.
Regression, robots and biological systems
- Pierre-Yves Gousenbourger, Estelle M. Massart, Antoni Musolas, Pierre-Antoine Absil, Julien M. Hendrickx, Laurent Jacques, Youssef M. Marzouk:
Piecewise-Bézier C1 smoothing on manifolds with application to wind field estimation. - Van-Tinh Tran, Alex Aussem:
Reducing variance due to importance weighting in covariate shift bias correction. - Bulcsú Sándor, Claudius Gros:
Complex activity patterns generated by short-term synaptic plasticity. - Tjeerd Olde Scheper:
Criticality in Biocomputation. - Bernardo Stearns, Fábio Medeiros Rangel, Flavio Rangel, Fabrício Firmino de Faria, Jonice Oliveira:
Scholar Performance Prediction using Boosted Regression Trees Techniques. - Milad Malekzadeh Shafaroudi, Jeffrey F. Queißer, Jochen J. Steil:
Imitation learning for a continuum trunk robot. - Luiz F. R. Oliveira, Felipe M. G. França:
ELM vs. WiSARD: a performance comparison. - Patrick Blöbaum, Shohei Shimizu, Takashi Washio:
A novel principle for causal inference in data with small error variance. - Jeevan Manavalan, Matthew Howard:
Learning null space projections fast. - Edna Milgo, Nixon K. Ronoh, Peter Waiganjo Wagacha, Bernard Manderick:
Comparison of adaptive MCMC methods. - Sam Palmer, Denise Gorse:
Pseudo-analytical solutions for stochastic options pricing using Monte Carlo simulation and Breeding PSO-trained neural networks. - Anders Søgaard:
Spikes as regularizers. - Zahra Karevan, Yunlong Feng, Johan A. K. Suykens:
Moving Least Squares Support Vector Machines for weather temperature prediction. - João P. P. Gomes, Diego P. P. Mesquita, Ananda Freire, Amauri H. Souza Júnior, Tommi Kärkkäinen:
A Robust Minimal Learning Machine based on the M-Estimator.
Processing, Mining and Visualizing Massive Urban Data
- Pierre Borgnat, Etienne Côme, Latifa Oukhellou:
Processing, mining and visualizing massive urban data. - Emeric Tonnelier, Nicolas Baskiotis, Vincent Guigue, Patrick Gallinari:
Anomaly detection and characterization in smart card logs using NMF and Tweets. - Rémy Cazabet, Pierre Borgnat, Pablo Jensen:
Using degree constrained gravity null-models to understand the structure of journeys' networks in bicycle sharing systems. - Diego Carvalho, Felipe M. G. França, Raul Barbosa, Douglas de O. Cardoso:
A neuro-symbolic approach to GPS trajectory classification. - Léna Carel, Pierre Alquier:
Non-negative matrix factorization as a pre-processing tool for travelers temporal profiles clustering. - Nicolas Cheifetz, Allou Samé, Zineb Sabir, Anne-Claire Sandraz, Cédric Féliers:
Extracting urban water usage habits from smart meter data: a functional clustering approach. - Anaïs Rémy, Etienne Côme:
Multiscale Spatio-Temporal Data Aggregation and Mapping for Urban Data Exploration. - Pierre-Antoine Laharotte, Romain Billot, Nour-Eddin El Faouzi:
Detection of non-recurrent road traffic events based on clustering indicators.
Signal and image processing, collaborative filtering
- Josef Feigl, Martin Bogdan:
Collaborative filtering with neural networks. - Weam M. Binjumah, Alexey Redyuk, Rod Adams, Neil Davey, Yi Sun:
Investigating optical transmission error correction using wavelet transforms. - Massimo De Gregorio, Maurizio Giordano:
WiSARDrp for Change Detection in Video Sequences. - Eyal Ben Zion, Boaz Lerner:
Learning human behaviors and lifestyle by capturing temporal relations in mobility patterns. - Patrick Thiam, Viktor Kessler, Friedhelm Schwenker:
Hierarchical Combination of Video Features for Personalised Pain Level Recognition. - Jing Ke, Yi Guo, Arcot Sowmya, Tomasz Bednarz:
A performance acceleration algorithm of spectral unmixing via subset selection. - Hong-Bo Xie, Hui Liu:
Myoelectrical signal classification based on S transform and two-directional 2DPCA. - Klaas Dijkstra, Jaap van de Loosdrecht, Lambert Schomaker, Marco A. Wiering:
Hyper-spectral frequency selection for the classification of vegetation diseases. - Isaac Fernández-Varela, Diego Álvarez-Estévez, Elena Hernández-Pereira, Vicente Moret-Bonillo:
Outlining a simple and robust method for the automatic detection of EEG arousals. - Gizelle Kupac Vianna, Gustavo Sucupira Oliveira, Gabriel Vargas Cunha:
A decision support system based on cellular automata to help the control of late blight in tomato cultures. - Adrian Ion-Margineanu, Sofie Van Cauter, Diana Maria Sima, Frederik Maes, Stefan Sunaert, Uwe Himmelreich, Sabine Van Huffel:
Comparison of manual and semi-manual delineations for classifying glioblastoma multiforme patients based on histogram and texture MRI features. - Diego García-Pérez, Ignacio Díaz Blanco, Daniel Pérez, Abel Alberto Cuadrado Vega, Manuel Domínguez-González:
Latent variable analysis in hospital electric power demand using non-negative matrix factorization. - Ronny Hug, Wolfgang Hübner, Michael Arens:
Supporting generative models of spatial behavior by user interaction.
Algorithmic Challenges in Big Data Analytics
- Verónica Bolón-Canedo, Beatriz Remeseiro, Konstantinos Sechidis, David Martínez-Rego, Amparo Alonso-Betanzos:
Algorithmic challenges in big data analytics. - Xiang Jiang, Erico N. de Souza, Xuan Liu, Behrouz Haji Soleimani, Xiaoguang Wang, Daniel L. Silver, Stan Matwin:
Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification. - Carlos Eiras-Franco, Leslie Kanthan, Amparo Alonso-Betanzos, David Martínez-Rego:
Scalable approximate k-NN Graph construction based on Locality Sensitive Hashing. - Henry W. J. Reeve, Gavin Brown:
Degrees of Freedom in Regression Ensembles. - Diego Fernández-Francos, Oscar Fontenla-Romero, Amparo Alonso-Betanzos, Gavin Brown:
Mutual information for improving the efficiency of the SCH algorithm. - Laura Morán-Fernández, Verónica Bolón-Canedo, Amparo Alonso-Betanzos:
A distributed approach for classification using distance metrics.
Deep learning
- Claudio Gallicchio, Alessio Micheli, Luca Silvestri:
Local Lyapunov Exponents of Deep RNN. - Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke:
Learning Semantic Prediction using Pretrained Deep Feedforward Networks. - Bruno Ordozgoiti, Alberto Mozo, Sandra Gómez Canaval, Udi Margolin, Elisha J. Rosensweig, Itai Segall:
Deep convolutional neural networks for detecting noisy neighbours in cloud infrastructure. - Matias Valdenegro-Toro:
Real-time convolutional networks for sonar image classification in low-power embedded systems. - Valentina Arrigoni, Beatrice Rossi, Pasqualina Fragneto, Giuseppe Desoli:
Approximate operations in Convolutional Neural Networks with RNS data representation. - Yanyan Geng, Ru-Ze Liang, Weizhi Li, Jingbin Wang, Gaoyuan Liang, Chenhao Xu, Jingyan Wang:
Learning convolutional neural network to maximize Pos@Top performance measure. - Melanie Ducoffe, Frédéric Precioso:
Active learning strategy for CNN combining batchwise Dropout and Query-By-Committee. - Petros Giannakopoulos, Yannis Cotronis:
A Deep Q-Learning Agent for L-Game with Variable Batch Training. - Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. - Antonio D'Isanto, Kai Lars Polsterer:
Uncertain photometric redshifts via combining deep convolutional and mixture density networks. - Stavros Timotheatos, Grigorios Tsagkatakis, Panagiotis Tsakalides, Panos E. Trahanias:
Feature Extraction and Learning for RSSI based Indoor Device Localization.
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last updated on 2025-02-02 15:21 CET by the dblp team
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