INNS BDDL 2019 - Program
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Time16-Apr17-Apr18-AprO.R.: Opening Remarks
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08:30-9:00
O.R.INV: Invited
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09:00-10:00
INV-1TUT-3INV-3
C.B.: Coffee Break (Provided by the Conference)
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10:00-10:30
C.B.C.B.C.B.TUT: Tutorial
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10:30-11:30
INV-2INV-4TUT-4P: Paper Oral Presentations
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11:30-11:50
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L.B.: Lunch Break (Not provided by the conference)
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11:50-12:10
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S.A.: Social Activity ( Boat trip to Cinque Terre conditional to the sea conditions http://traghettiportofino.it/en/ )
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12:10-12:30
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G.D.: Gala Dinner ( Castelli Restaurant http://www.ristoranteaicastelli.it/index.html )
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12:30-13:30
L.B.L.B.L.B.C.R.: Closing Remarks + Student Awards
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13:30-14:30
TUT-2S.A.TUT-5
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14:30-14:50
P02
P03P23P26Big Data and Deep Learning Theory
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14:50-15:10
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Optimization Issues in Big Data and Deep Learning
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15:10-15:30
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P09P37P34Convolutional NN
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15:30-16:00
C.B.C.B.Transfer Learning
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16:00-17:00
TUT-1TUT-6Recurrent NN
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17:00-17:20
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P04P05P39Applications in Tansportation
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17:20-17:40
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P08C.R.General Applications
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17:40-18:00
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P11Applications in Business
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Strucured Data
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20:30GDGeneral topics in Deep NN
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INV1 - Guang-Bin Huang - Extreme Learning Machines (ELM) – When ELM and Deep Learning Synergize
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INV2 - Hava Siegelmann - TBD
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INV3 - Paolo Ferragina - Hybrid Data Structures and beyond
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INV4 - Massimiliano Pontil - Online Meta-Learning
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TUT1 - Deep Learning for Graphs - Davide Bacciu, Alessio Micheli
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TUT2 - Continual Lifelong Learning with Neural Networks - German I. Parisi, Vincenzo Lomonaco
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TUT3 - Fairness in Machine Learning - Silvia Chiappa, Luca Oneto
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TUT4 - Deep Randomized Neural Networks - Claudio Gallicchio, Simone Scardapane
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TUT5 - Complexity of Shallow and Deep Networks - Věra Kůrková
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TUT6 - Tensor Decompositions and Applications. Blessing of Dimensionality - Danilo P. Mandic, Ilia Kisil, Giuseppe G. Calvi
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P01 - On the trade-off between number of examples and precision of supervision in regression - Giorgio Gnecco, Federico Nutarelli
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P02 - Distributed SmSVM Ensemble Learning - Jeffrey Hajewski, Suely Oliveira
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P03 - Size/Accuracy Trade-off in Convolutional Neural Networks: An Evolutionary Approach - Tomaso Cetto, Jonathan Byrne, David Moloney
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P04 - Fast transfer learning for image polarity detection - Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino
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P05 - Dropout for Recurrent Neural Networks - Nathan Watt, Mathys du Plessis
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P06 - Psychiatric disorders classification with 3D Convolutional Neural Networks - Stefano Campese, Ivano Lauriola, Cristina Scarpazza, Giuseppe Sartori, Fabio Aiolli
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P07 - Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions - Zhishen Huang, Stephen Becker
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P08 - Deep-learning domain adaptation techniques for credit cards fraud detection - Bertrand Lebichot, Yann-Aël Le Borgne, Liyun He-Guelton, Frederic Oblé, Gianluca Bontempi
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P09 - Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks - Hong-Jun Yoon, John X. Qiu, J. Blair Christian, Jacob Hinkle, Folami Alamudun, Georgia Tourassi
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P10 - An information theoretic approach to the autoencoder - Vincenzo Crescimanna, Bruce Graham
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P11 - Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning - Iam Palatnik de Sousa, Marley Maria Bernardes Rebuzzi Vellasco, Eduardo Costa da Silva
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P12 - Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies - Roberto Spigolon, Luca Oneto, Dimitar Anastasovksi, Nadia Fabrizio, Marie SWIATEK, Renzo Canepa, Davide Anguita
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P13 - Presumable Applications of Deep Learning for Cellular Automata Identification - Anton Popov, Alexander Makarenko
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P14 - Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability - Luca Oneto, Irene Buselli, Paolo Sanetti, Renzo Canepa, Simone Petralli, Davide Anguita
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P15 - Train Overtaking Prediction in Railway Networks: a Big Data Perspective - Luca Oneto, Irene Buselli, Alessandro Lulli, Renzo Canepa, Simone Petralli, Davide Anguita
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P16 - Cavitation Noise Spectra Prediction with Hybrid Models - Francesca Cipollini, Fabiana Miglianti, Luca Oneto, Giorgio Tani, Michele Viviani, Davide Anguita
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P17 - Pseudoinverse Learners: New Trend and Applications to Big Data - Ping Guo, Dongbin Zhao, Min Han, Shoubo Feng
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P18 - Innovation Capability of Firms: A Big Data Approach with patents - Linda Ponta, Gloria Puliga, Luca Oneto, Raffaella Manzini
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P19 - Predicting future market trends: which is the optimal window? - Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria
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P20 - F0 modeling using DNN for Arabic parametric speech synthesis - Imene Zangar, Zied Mnasri, Vincent Colotte, Denis Jouvet
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P21 - Regularizing Neural Networks with Gradient Monitoring - Gavneet Singh Chadha, Elnaz Meydani, Andreas Schwung
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P22 - Visual Analytics for Supporting Conflict Resolution in Large Railway Networks - Udo Schlegel, Wolfgang Jentner, Juri Buchmüller, Eren Cakmak, Giuliano Castiglia, Renzo Canepa, Simone Petralli, Luca Oneto, Daniel Keim, Davide Anguita
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P23 - Modeling Urban Traffic Data through Graph-Based Neural Networks - Viviana Pinto, Alan Perotti, Tania Cerquitelli
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P24 - Traffic Sign Detection using R-CNN - Philipp Rehlaender, Maik Schroeer, Gavneet Chadha, Andreas Schwung
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P25 - Deep Tree Transductions - A Short Survey - Davide Bacciu, Antonio Bruno
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P26 - Approximating the Solution of Surface Wave Propagation Using Deep Neural Networks - Wilhelm Sorteberg, Stef Garasto, Chris Cantwell, Anil Anthony Bharath
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P27 - A Semi-Supervised Deep Rule-Based Approach for Remote Sensing Scene Classification - Xiaowei Gu, Plamen Angelov
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P28 - Comparing the Estimations of Value-at-Risk using Artificial Network and Other Methods for Business Sectors - Siu Cheung, Ziqi Chen, Yanli Li
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P29 - Using Convolutional Neural Networks to Distinguish Different Sign Language Alphanumerics - Stephen Green, Ivan Tyukin, Alexander Gorban
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P30 - Mise en abyme with artificial intelligence: how to predict the accuracy of ANN, applied to hyper-parameter tuning - Giorgia Franchini, Mathilde Galinier, Micaela Verucchi
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P31 - Asynchronous Stochastic Variational Inference - Saad Mohamad, Abdelhamid Bouchachia, Moamar Mouchaweh
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P32 - Probabilistic Bounds for Binary Classication of Large Data Sets - Vera Kurkova, Marcello Sanguineti
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P33 - Multikernel activation functions: formulation and a case study - Simone Scardapane, Elena Nieddu, Donatella Firmani, Paolo Merialdo
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P34 - Understanding Ancient Coin Images - Jessica Cooper, Ognjen Arandjelovic
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P35 - Effects of Skip-connection in ResNet and Batch-normalization on Fisher Information Matrix - Yasutaka Furusho, Kazushi Ikeda
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P36 - Skipping two layers in ResNet makes the generalization gap smaller than skipping one or no layer - Yasutaka Furusho, Tongliang Liu, Kazushi Ikeda
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P37 - A preference-learning framework for modeling Relational data - Ivano Lauriola, Mirko Polato, Guglielmo Faggioli, Fabio Aiolli
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P38 - Convolutional Neural Networks for Twitter Text Toxicity Analysis - Spiros Georgakopoulos, Sotiris Tasoulis, Aristidis Vrahatis, Vassilis Plagianakos
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P39 - Fast Spectral Radius Initialization for Recurrent Neural Networks - Claudio Gallicchio, Alessio Micheli, Luca Pedrelli
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