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ORCID6th LOD 2020: Siena, Italy - Part II
- Giuseppe Nicosia
, Varun Ojha, Emanuele La Malfa, Giorgio Jansen, Vincenzo Sciacca, Panos M. Pardalos, Giovanni Giuffrida, Renato Umeton:
Machine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020, Siena, Italy, July 19-23, 2020, Revised Selected Papers, Part II. Lecture Notes in Computer Science 12566, Springer 2020, ISBN 978-3-030-64579-3 - Elisa Marcelli, Renato De Leone:
Multi-kernel Covariance Terms in Multi-output Support Vector Machines. 1-11 - Alessandro Zonta, Ali el Hassouni, David W. Romero, Jakub M. Tomczak:
Generative Fourier-Based Auto-encoders: Preliminary Results. 12-15 - Günther Schindler, Wolfgang Roth, Franz Pernkopf, Holger Fröning:
Parameterized Structured Pruning for Deep Neural Networks. 16-27 - Riste Stojanov, Gorjan Popovski, Nasi Jofce, Dimitar Trajanov, Barbara Korousic-Seljak, Tome Eftimov:
FoodViz: Visualization of Food Entities Linked Across Different Standards. 28-38 - Mayumi Ohta, Nathaniel Berger, Artem Sokolov, Stefan Riezler:
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization. 39-64 - Julia Krützmann, Alexander Schiendorfer, Sergej Beratz, Judith Moosburger-Will, Wolfgang Reif, Siegfried Horn:
Learning Controllers for Adaptive Spreading of Carbon Fiber Tows. 65-77 - Alper Yegenoglu, Kai Krajsek, Sandra Díaz-Pier, Michael Herty:
Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent. 78-92 - Christofer Fellicious, Thomas Weißgerber, Michael Granitzer:
Effects of Random Seeds on the Accuracy of Convolutional Neural Networks. 93-102 - Jimiama Mafeni Mase, Peter Chapman, Grazziela P. Figueredo, Mercedes Torres Torres:
Benchmarking Deep Learning Models for Driver Distraction Detection. 103-117 - Abhay Harpale:
Chronologically Guided Deep Network for Remaining Useful Life Estimation. 118-130 - Leandro Leonardo Lorente-Leyva, M. M. E. Alemany, Diego Hernán Peluffo-Ordóñez, Israel David Herrera-Granda:
A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry. 131-142 - Abhay Harpale:
Automatic Curriculum Recommendation for Employees. 143-155 - Nima Nabizadeh, Martin Heckmann, Dorothea Kolossa:
Target-Aware Prediction of Tool Usage in Sequential Repair Tasks. 156-168 - Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo:
Safer Reinforcement Learning for Agents in Industrial Grid-Warehousing. 169-180 - Vladimir Soloviev, Nikita Titov, Elena Smirnova:
Coking Coal Railway Transportation Forecasting Using Ensembles of ElasticNet, LightGBM, and Facebook Prophet. 181-190 - Jose Cruz, Wilson Mamani, Christian Romero, Ferdinand Pineda:
Multi-parameter Regression of Photovoltaic Systems using Selection of Variables with the Method: Recursive Feature Elimination for Ridge, Lasso and Bayes. 191-202 - Rommel G. Regis:
High-Dimensional Constrained Discrete Multi-objective Optimization Using Surrogates. 203-214 - Jon Vadillo, Roberto Santana, José Antonio Lozano:
Exploring Gaps in DeepFool in Search of More Effective Adversarial Perturbations. 215-227 - Abhinav Raj, Subhankar Mishra:
Lottery Ticket Hypothesis: Placing the k-orrect Bets. 228-239 - S. Hamid Mousavi, Jakob Drefs, Jörg Lücke:
A Double-Dictionary Approach Learns Component Means and Variances for V1 Encoding. 240-244 - Israel David Herrera-Granda, Leandro Leonardo Lorente-Leyva, Diego Hernán Peluffo-Ordóñez, M. M. E. Alemany:
A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios. 245-258 - Giorgia Franchini, Valeria Ruggiero, Luca Zanni:
Steplength and Mini-batch Size Selection in Stochastic Gradient Methods. 259-263 - Yaodong He, Shiu Yin Yuen:
Black Box Algorithm Selection by Convolutional Neural Network. 264-280 - Richard Ball, Hennie A. Kruger, Lynette Drevin:
A Unified Approach to Anomaly Detection. 281-291 - Sara Atito Ali Ahmed, Berrin A. Yanikoglu, Cemre Zor, Muhammad Awais, Josef Kittler:
Skin Lesion Diagnosis with Imbalanced ECOC Ensembles. 292-303 - Astrid Merckling, Alexandre Coninx, Loic Cressot, Stéphane Doncieux, Nicolas Perrin:
State Representation Learning from Demonstration. 304-315 - Huanghua Li, Zhidong Deng, Jianxin Zhang, Zhen Zhang, Xiaozhao Wang, Yongbao Li, Feng Li, Lizhong Xie:
A Deep Learning Based Fault Detection Method for Rocket Launcher Electrical System. 316-325 - Mayowa Ayodele, Richard Allmendinger, K. Nadia Papamichail:
Heuristic Search in LegalTech: Dynamic Allocation of Legal Cases to Legal Staff. 326-338 - Daniel N. Nissani:
Unsupervisedly Learned Representations - Should the Quest Be Over? 339-349 - Yuzhou Gao, Tengchao Yu, Jinglai Li:
Bayesian Optimization with Local Search. 350-361 - Thu Dinh, Bao Wang, Andrea L. Bertozzi, Stanley J. Osher, Jack Xin:
Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets. 362-381 - Jake Williams, Abel Tadesse, Tyler Sam, Huey Sun, George D. Montañez:
Limits of Transfer Learning. 382-393 - Helge Spieker, Arnaud Gotlieb:
Learning Objective Boundaries for Constraint Optimization Problems. 394-408 - Michela Quadrini, Sebastian Daberdaku, Carlo Ferrari:
Hierarchical Representation and Graph Convolutional Networks for the Prediction of Protein-Protein Interaction Sites. 409-420 - Petia D. Koprinkova-Hristova, Nadejda Bocheva:
Brain-Inspired Spike Timing Model of Dynamic Visual Information Perception and Decision Making with STDP and Reinforcement Learning. 421-435 - Sani Aji, Poom Kumam, Punnarai Siricharoen, Ali Maina Bukar:
Automatic Classification of Low-Angle Fuze-Quick Craters Using Deep Learning. 436-447 - Alexey Marchenko, Alexey Utki-Otki, Dmitry Golubev:
Efficient Text Processing via Context Triggered Piecewise Hashing Algorithm for Spam Detection. 448-456 - Galina A. Samigulina, Zarina I. Samigulina:
Machine Learning for Big Data Analysis in Drug Design. 457-469 - Harry Wang, Brian T. Denton:
Pareto-Weighted-Sum-Tuning: Learning-to-Rank for Pareto Optimization Problems. 470-480 - Marcin Orchel, Johan A. K. Suykens:
Fast Hyperparameter Tuning for Support Vector Machines with Stochastic Gradient Descent. 481-493 - Aynalem Tesfaye Misganaw, Sabine Roller:
PlattForm: Parallel Spoken Corpus of Middle West German Dialects with Web-Based Interface. 494-503 - Cole Smith, Andrii Dobroshynskyi, Suzanne McIntosh:
Quantifying Local Energy Demand Through Pollution Analysis. 504-515 - Zahra Jandaghi, Liming Cai:
On Graph Learning with Neural Networks. 516-528 - Alma A. M. Rahat, Michael Wood:
On Bayesian Search for the Feasible Space Under Computationally Expensive Constraints. 529-540 - Florin Tim Peters, Robin Hirt:
A Transfer Machine Learning Matching Algorithm for Source and Target (TL-MAST). 541-558 - Nicholas Mandarano, Rommel G. Regis, Elizabeth Bloom:
Machine Learning and Statistical Models for the Prevalence of Multiple Sclerosis. 559-571 - Mahdi Jammal, Stéphane Canu, Maher Abdallah:
Robust and Sparse Support Vector Machines via Mixed Integer Programming. 572-585 - Gideon Mbiydzenyuy:
Univariate Time Series Anomaly Labelling Algorithm. 586-599 - Natalya Selitskaya, Stanislaw Sielicki, Nikolaos Christou:
Challenges in Real-Life Face Recognition with Heavy Makeup and Occlusions Using Deep Learning Algorithms. 600-611 - Gail Gilboa-Freedman, Yair Amichai-Hamburger, Dotan Castro:
Who Accepts Information Measures? 612-616 - Nicolas Bach, Andrew Melnik, Federico Rosetto, Helge J. Ritter:
An Error-Based Addressing Architecture for Dynamic Model Learning. 617-630 - Nicolas Bach, Andrew Melnik, Malte Schilling, Timo Korthals, Helge J. Ritter:
Learn to Move Through a Combination of Policy Gradient Algorithms: DDPG, D4PG, and TD3. 631-644 - Mahdi Jammal, Stéphane Canu, Maher Abdallah:
ℓ 1 Regularized Robust and Sparse Linear Modeling Using Discrete Optimization. 645-661
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