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ORCIDINNSBDDL 2019: Sestri Levante, Genova, Italy
- Luca Oneto
, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Recent Advances in Big Data and Deep Learning, Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL 2019, held at Sestri Levante, Genova, Italy 16-18 April 2019. Springer 2020, ISBN 978-3-030-16840-7 - Giorgio Gnecco, Federico Nutarelli:
On the Trade-Off Between Number of Examples and Precision of Supervision in Regression. 1-6 - Jeffrey Hajewski, Suely Oliveira:
Distributed SmSVM Ensemble Learning. 7-16 - Tomaso Cetto, Jonathan Byrne, Xiaofan Xu, David Moloney:
Size/Accuracy Trade-Off in Convolutional Neural Networks: An Evolutionary Approach. 17-26 - Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino:
Fast Transfer Learning for Image Polarity Detection. 27-37 - Nathan Watt, Mathys C. du Plessis:
Dropout for Recurrent Neural Networks. 38-47 - Stefano Campese, Ivano Lauriola, Cristina Scarpazza, Giuseppe Sartori, Fabio Aiolli:
Psychiatric Disorders Classification with 3D Convolutional Neural Networks. 48-57 - Zhishen Huang, Stephen Becker:
Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions. 58-77 - Bertrand Lebichot, Yann-Aël Le Borgne, Liyun He-Guelton, Frédéric Oblé, Gianluca Bontempi:
Deep-Learning Domain Adaptation Techniques for Credit Cards Fraud Detection. 78-88 - Hong-Jun Yoon, John X. Qiu, James Blair Christian, Jacob D. Hinkle, Folami Alamudun, Georgia D. Tourassi:
Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks. 89-98 - Vincenzo Crescimanna, Bruce Graham:
An Information Theoretic Approach to the Autoencoder. 99-108 - Iam Palatnik de Sousa, Marley Maria Bernardes Rebuzzi Vellasco, Eduardo Costa da Silva:
Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning. 109-119 - Roberto Spigolon, Luca Oneto, Dimitar Anastasovski, Nadia Fabrizio, Marie Swiatek, Renzo Canepa, Davide Anguita:
Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies. 120-125 - Anton Popov, Alexander Makarenko:
Presumable Applications of Deep Learning for Cellular Automata Identification. 126-135 - Luca Oneto, Irene Buselli, Paolo Sanetti, Renzo Canepa, Simone Petralli, Davide Anguita:
Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability. 136-141 - Luca Oneto, Irene Buselli, Alessandro Lulli, Renzo Canepa, Simone Petralli, Davide Anguita:
Train Overtaking Prediction in Railway Networks: A Big Data Perspective. 142-151 - Francesca Cipollini, Fabiana Miglianti, Luca Oneto, Giorgio Tani, Michele Viviani, Davide Anguita:
Cavitation Noise Spectra Prediction with Hybrid Models. 152-157 - Ping Guo, Dongbin Zhao, Min Han, Shoubo Feng:
Pseudoinverse Learners: New Trend and Applications to Big Data. 158-168 - Linda Ponta, Gloria Puliga, Luca Oneto, Raffaella Manzini:
Innovation Capability of Firms: A Big Data Approach with Patents. 169-179 - Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria:
Predicting Future Market Trends: Which Is the Optimal Window? 180-185 - Imene Zangar, Zied Mnasri, Vincent Colotte, Denis Jouvet:
\(F_{0}\) Modeling Using DNN for Arabic Parametric Speech Synthesis. 186-195 - Gavneet Singh Chadha, Elnaz Meydani, Andreas Schwung:
Regularizing Neural Networks with Gradient Monitoring. 196-205 - Udo Schlegel, Wolfgang Jentner, Juri Buchmüller, Eren Cakmak, Giuliano Castiglia, Renzo Canepa, Simone Petralli, Luca Oneto, Daniel A. Keim, Davide Anguita:
Visual Analytics for Supporting Conflict Resolution in Large Railway Networks. 206-215 - Viviana Pinto, Alan Perotti, Tania Cerquitelli:
Modeling Urban Traffic Data Through Graph-Based Neural Networks. 216-225 - Philipp Rehlaender, Maik Schroeer, Gavneet Singh Chadha, Andreas Schwung:
Traffic Sign Detection Using R-CNN. 226-235 - Davide Bacciu, Antonio Bruno:
Deep Tree Transductions - A Short Survey. 236-245 - Wilhelm E. Sorteberg, Stef Garasto, Chris D. Cantwell, Anil A. Bharath:
Approximating the Solution of Surface Wave Propagation Using Deep Neural Networks. 246-256 - Xiaowei Gu, Plamen P. Angelov:
A Semi-supervised Deep Rule-Based Approach for Remote Sensing Scene Classification. 257-266 - Siu Cheung, Ziqi Chen, Yanli Li:
Comparing the Estimations of Value-at-Risk Using Artificial Network and Other Methods for Business Sectors. 267-275 - Stephen Green, Ivan Tyukin, Alexander N. Gorban:
Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics. 276-285 - Giorgia Franchini, Mathilde Galinier, Micaela Verucchi:
Mise en abyme with Artificial Intelligence: How to Predict the Accuracy of NN, Applied to Hyper-parameter Tuning. 286-295 - Saad Mohamad, Abdelhamid Bouchachia, Moamar Sayed Mouchaweh:
Asynchronous Stochastic Variational Inference. 296-308 - Vera Kurková, Marcello Sanguineti:
Probabilistic Bounds for Binary Classification of Large Data Sets. 309-319 - Simone Scardapane, Elena Nieddu, Donatella Firmani, Paolo Merialdo:
Multikernel Activation Functions: Formulation and a Case Study. 320-329 - Jessica Cooper, Ognjen Arandjelovic:
Understanding Ancient Coin Images. 330-340 - Yasutaka Furusho, Kazushi Ikeda:
Effects of Skip-Connection in ResNet and Batch-Normalization on Fisher Information Matrix. 341-348 - Yasutaka Furusho, Tongliang Liu, Kazushi Ikeda:
Skipping Two Layers in ResNet Makes the Generalization Gap Smaller than Skipping One or No Layer. 349-358 - Ivano Lauriola, Mirko Polato, Guglielmo Faggioli, Fabio Aiolli:
A Preference-Learning Framework for Modeling Relational Data. 359-369 - Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Vassilis P. Plagianakos:
Convolutional Neural Networks for Twitter Text Toxicity Analysis. 370-379 - Claudio Gallicchio, Alessio Micheli, Luca Pedrelli:
Fast Spectral Radius Initialization for Recurrent Neural Networks. 380-390
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