- Saad Mohamad, Abdelhamid Bouchachia, Moamar Sayed Mouchaweh:
Asynchronous Stochastic Variational Inference. INNSBDDL 2019: 296-308 - Luca Oneto, Irene Buselli, Alessandro Lulli, Renzo Canepa, Simone Petralli, Davide Anguita:
Train Overtaking Prediction in Railway Networks: A Big Data Perspective. INNSBDDL 2019: 142-151 - Luca Oneto, Irene Buselli, Paolo Sanetti, Renzo Canepa, Simone Petralli, Davide Anguita:
Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability. INNSBDDL 2019: 136-141 - Luca Oneto, Silvia Chiappa:
Fairness in Machine Learning. INNSBDDL (Tutorials) 2019: 155-196 - Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Introduction. INNSBDDL (Tutorials) 2019: 1-4 - German Ignacio Parisi, Vincenzo Lomonaco:
Online Continual Learning on Sequences. INNSBDDL (Tutorials) 2019: 197-221 - Viviana Pinto, Alan Perotti, Tania Cerquitelli:
Modeling Urban Traffic Data Through Graph-Based Neural Networks. INNSBDDL 2019: 216-225 - Linda Ponta, Gloria Puliga, Luca Oneto, Raffaella Manzini:
Innovation Capability of Firms: A Big Data Approach with Patents. INNSBDDL 2019: 169-179 - Anton Popov, Alexander Makarenko:
Presumable Applications of Deep Learning for Cellular Automata Identification. INNSBDDL 2019: 126-135 - Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino:
Fast Transfer Learning for Image Polarity Detection. INNSBDDL 2019: 27-37 - Philipp Rehlaender, Maik Schroeer, Gavneet Singh Chadha, Andreas Schwung:
Traffic Sign Detection Using R-CNN. INNSBDDL 2019: 226-235 - Simone Scardapane, Elena Nieddu, Donatella Firmani, Paolo Merialdo:
Multikernel Activation Functions: Formulation and a Case Study. INNSBDDL 2019: 320-329 - 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. INNSBDDL 2019: 206-215 - Wilhelm E. Sorteberg, Stef Garasto, Chris D. Cantwell, Anil A. Bharath:
Approximating the Solution of Surface Wave Propagation Using Deep Neural Networks. INNSBDDL 2019: 246-256 - Iam Palatnik de Sousa, Marley Maria Bernardes Rebuzzi Vellasco, Eduardo Costa da Silva:
Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning. INNSBDDL 2019: 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. INNSBDDL 2019: 120-125 - Nathan Watt, Mathys C. du Plessis:
Dropout for Recurrent Neural Networks. INNSBDDL 2019: 38-47 - 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. INNSBDDL 2019: 89-98 - Imene Zangar, Zied Mnasri, Vincent Colotte, Denis Jouvet:
\(F_{0}\) Modeling Using DNN for Arabic Parametric Speech Synthesis. INNSBDDL 2019: 186-195 - 2018
- Robert Kozma, Roman Ilin, Hava T. Siegelmann:
Evolution of Abstraction Across Layers in Deep Learning Neural Networks. INNS Conference on Big Data 2018: 203-213 - Dieky Adzkiya:
Preface: 3rd INNS Conference on Big Data and Deep Learning 2018. INNS Conference on Big Data 2018: 1 - Diah Agustin, Erna Apriliani, Hendro Nurhadi:
Preliminary study on estimation of 12.7 x 99 mm caliber projectile motion using Ensemble Kalman Filter method. INNS Conference on Big Data 2018: 163-173 - Nguyen Anh, Mukesh Prasad, Narasimalu Srikanth, Suresh Sundaram:
Wind Speed Intervals Prediction using Meta-cognitive Approach. INNS Conference on Big Data 2018: 23-32 - Nguyen Anh, Mukesh Prasad, Narasimalu Srikanth, Suresh Sundaram:
Wave Forecasting using Meta-cognitive Interval Type-2 Fuzzy Inference System. INNS Conference on Big Data 2018: 33-41 - Riska Aprilia, Erna Apriliani, Hendro Nurhadi:
Preliminary study on estimation of 12.7×99 mm caliber projectile motion using Extended Kalman Filter method. INNS Conference on Big Data 2018: 153-162 - Ahmad Arinaldi, Jaka Arya Pradana, Arlan Arventa Gurusinga:
Detection and classification of vehicles for traffic video analytics. INNS Conference on Big Data 2018: 259-268 - Muhammad Attamimi, Takayuki Nagai, Djoko Purwanto:
Object detection based on particle filter and integration of multiple features. INNS Conference on Big Data 2018: 214-218 - Gaël Beck, Hanane Azzag, Stéphanie Bougeard, Mustapha Lebbah, Ndèye Niang:
A New Micro-Batch Approach for Partial Least Square Clusterwise Regression. INNS Conference on Big Data 2018: 239-250 - Kaoutar Benlamine, Nistor Grozavu, Younès Bennani, Nicoleta Rogovschi, Kamel Haddadou, Ahmed Amamou:
Domain Name Recommendation based on Neural Network. INNS Conference on Big Data 2018: 60-70 - Francesca Cipollini, Luca Oneto, Andrea Coraddu, Stefano Savio, Davide Anguita:
Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents. INNS Conference on Big Data 2018: 42-51