INNSBDDL

Publications

2020

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. INNSBDDL (2020)

2019

Linda Ponta, Gloria Puliga, Luca Oneto, Raffaella Manzini
Innovation Capability of Firms: A Big Data Approach with Patents. INNSBDDL (2019)
Ivano Lauriola, Mirko Polato, Guglielmo Faggioli, Fabio Aiolli
A Preference-Learning Framework for Modeling Relational Data. INNSBDDL (2019)
Wilhelm E. Sorteberg, Stef Garasto, Chris D. Cantwell, Anil A. Bharath
Approximating the Solution of Surface Wave Propagation Using Deep Neural Networks. INNSBDDL (2019)
Nathan Watt, Mathys C. du Plessis
Dropout for Recurrent Neural Networks. INNSBDDL (2019)
Stefano Campese, Ivano Lauriola, Cristina Scarpazza, Giuseppe Sartori, Fabio Aiolli
Psychiatric Disorders Classification with 3D Convolutional Neural Networks. INNSBDDL (2019)
Tomaso Cetto, Jonathan Byrne, Xiaofan Xu, David Moloney
Size/Accuracy Trade-Off in Convolutional Neural Networks: An Evolutionary Approach. INNSBDDL (2019)
Xiaowei Gu, Plamen P. Angelov
A Semi-supervised Deep Rule-Based Approach for Remote Sensing Scene Classification. INNSBDDL (2019)
Jeffrey Hajewski, Suely Oliveira
Distributed SmSVM Ensemble Learning. INNSBDDL (2019)
Simone Scardapane, Elena Nieddu, Donatella Firmani, Paolo Merialdo
Multikernel Activation Functions: Formulation and a Case Study. INNSBDDL (2019)
Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria
Predicting Future Market Trends: Which Is the Optimal Window? INNSBDDL (2019)
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)
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)
Francesca Cipollini, Fabiana Miglianti, Luca Oneto, Giorgio Tani, Michele Viviani, Davide Anguita
Cavitation Noise Spectra Prediction with Hybrid Models. INNSBDDL (2019)
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)
Vincenzo Crescimanna, Bruce Graham
An Information Theoretic Approach to the Autoencoder. INNSBDDL (2019)
Jessica Cooper, Ognjen Arandjelovic
Understanding Ancient Coin Images. INNSBDDL (2019)
Claudio Gallicchio, Alessio Micheli, Luca Pedrelli
Fast Spectral Radius Initialization for Recurrent Neural Networks. INNSBDDL (2019)
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)
Bertrand Lebichot, Yann-Aël Le Borgne, Liyun He-Guelton, Frédéric Oblé, Gianluca Bontempi
Deep-Learning Domain Adaptation Techniques for Credit Cards Fraud Detection. INNSBDDL (2019)
Gavneet Singh Chadha, Elnaz Meydani, Andreas Schwung
Regularizing Neural Networks with Gradient Monitoring. INNSBDDL (2019)
Luca Oneto, Irene Buselli, Alessandro Lulli, Renzo Canepa, Simone Petralli, Davide Anguita
Train Overtaking Prediction in Railway Networks: A Big Data Perspective. INNSBDDL (2019)
Giorgio Gnecco, Federico Nutarelli
On the Trade-Off Between Number of Examples and Precision of Supervision in Regression. INNSBDDL (2019)
Yasutaka Furusho, Kazushi Ikeda
Effects of Skip-Connection in ResNet and Batch-Normalization on Fisher Information Matrix. INNSBDDL (2019)
Vera Kurková, Marcello Sanguineti
Probabilistic Bounds for Binary Classification of Large Data Sets. INNSBDDL (2019)
Giorgia Franchini, Mathilde Galinier, Micaela Verucchi
Mise en abyme with Artificial Intelligence: How to Predict the Accuracy of NN, Applied to Hyper-parameter Tuning. INNSBDDL (2019)
Viviana Pinto, Alan Perotti, Tania Cerquitelli
Modeling Urban Traffic Data Through Graph-Based Neural Networks. INNSBDDL (2019)
Saad Mohamad, Abdelhamid Bouchachia, Moamar Sayed Mouchaweh
Asynchronous Stochastic Variational Inference. INNSBDDL (2019)
Davide Bacciu, Antonio Bruno
Deep Tree Transductions - A Short Survey. INNSBDDL (2019)
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)
Ping Guo, Dongbin Zhao, Min Han, Shoubo Feng
Pseudoinverse Learners: New Trend and Applications to Big Data. INNSBDDL (2019)
Stephen Green, Ivan Tyukin, Alexander N. Gorban
Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics. INNSBDDL (2019)
Anton Popov, Alexander Makarenko
Presumable Applications of Deep Learning for Cellular Automata Identification. INNSBDDL (2019)
Philipp Rehlaender, Maik Schroeer, Gavneet Singh Chadha, Andreas Schwung
Traffic Sign Detection Using R-CNN. INNSBDDL (2019)
Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Vassilis P. Plagianakos
Convolutional Neural Networks for Twitter Text Toxicity Analysis. INNSBDDL (2019)
Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino
Fast Transfer Learning for Image Polarity Detection. INNSBDDL (2019)
Yasutaka Furusho, Tongliang Liu, Kazushi Ikeda
Skipping Two Layers in ResNet Makes the Generalization Gap Smaller than Skipping One or No Layer. INNSBDDL (2019)
Siu Cheung, Ziqi Chen, Yanli Li
Comparing the Estimations of Value-at-Risk Using Artificial Network and Other Methods for Business Sectors. INNSBDDL (2019)
Zhishen Huang, Stephen Becker
Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions. INNSBDDL (2019)
Imene Zangar, Zied Mnasri, Vincent Colotte, Denis Jouvet
\(F_{0}\) Modeling Using DNN for Arabic Parametric Speech Synthesis. INNSBDDL (2019)