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ORCIDPKDD / ECML 2021: Bilbao, Spain - Part IV
- Yuxiao Dong, Nicolas Kourtellis, Barbara Hammer, José Antonio Lozano
:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part IV. Lecture Notes in Computer Science 12978, Springer 2021, ISBN 978-3-030-86513-9
Anomaly Detection and Malware
- Damien Fourure, Muhammad Usama Javaid, Nicolas Posocco, Simon Tihon:
Anomaly Detection: How to Artificially Increase Your F1-Score with a Biased Evaluation Protocol. 3-18 - Jingzhu He, Chin-Chia Michael Yeh, Yanhong Wu, Liang Wang, Wei Zhang:
Mining Anomalies in Subspaces of High-Dimensional Time Series for Financial Transactional Data. 19-36 - Raphael Labaca Castro, Sebastian Franz, Gabi Dreo Rodosek:
AIMED-RL: Exploring Adversarial Malware Examples with Reinforcement Learning. 37-52 - Paul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukás Bajer, Tobias Scheffer:
Learning Explainable Representations of Malware Behavior. 53-68 - Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe:
Strategic Mitigation Against Wireless Attacks on Autonomous Platoons. 69-84 - Jose Mathew, Meghana Negi, Rutvik Vijjali, Jairaj Sathyanarayana:
DeFraudNet: An End-to-End Weak Supervision Framework to Detect Fraud in Online Food Delivery. 85-99
Spatio-Temporal Data
- Giorgio Corani, Alessio Benavoli, Marco Zaffalon:
Time Series Forecasting with Gaussian Processes Needs Priors. 103-117 - Jens Schreiber, Stephan Vogt, Bernhard Sick:
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series Forecast. 118-134 - Lun Jiang, Nima Salehi Sadghiani, Zhuo Tao, Andrew Cohen:
Generating Multi-type Temporal Sequences to Mitigate Class-Imbalanced Problem. 135-150 - Xin Li, Jun Liao, Li Liu:
Recognizing Skeleton-Based Hand Gestures by a Spatio-Temporal Network. 151-167
E-commerce and Finance
- Michele Starnini, Charalampos E. Tsourakakis, Maryam Zamanipour, André Panisson, Walter Allasia, Marco Fornasiero, Laura Li Puma, Valeria Ricci, Silvia Ronchiadin, Angela Ugrinoska, Marco Varetto, Dario Moncalvo:
Smurf-Based Anti-money Laundering in Time-Evolving Transaction Networks. 171-186 - Ankit Gandhi, Aakanksha, Sivaramakrishnan Kaveri, Vineet Chaoji:
Spatio-Temporal Multi-graph Networks for Demand Forecasting in Online Marketplaces. 187-203 - Zijian Shi, John Cartlidge:
The Limit Order Book Recreation Model (LOBRM): An Extended Analysis. 204-220 - Elior Nehemya, Yael Mathov, Asaf Shabtai, Yuval Elovici:
Taking over the Stock Market: Adversarial Perturbations Against Algorithmic Traders. 221-236 - Carlo Abrate, Alessio Angius, Gianmarco De Francisci Morales, Stefano Cozzini, Francesca Iadanza, Laura Li Puma, Simone Pavanelli, Alan Perotti, Stefano Pignataro, Silvia Ronchiadin:
Continuous-Action Reinforcement Learning for Portfolio Allocation of a Life Insurance Company. 237-252 - Ting-Wei Lin, Ruei-Yao Sun, Hsuan-Ling Chang, Chuan-Ju Wang, Ming-Feng Tsai:
XRR: Explainable Risk Ranking for Financial Reports. 253-268
Healthcare and Medical Applications (including Covid)
- Prasanna Umar, Chandan Akiti, Anna Cinzia Squicciarini, Sarah Michele Rajtmajer:
Self-disclosure on Twitter During the COVID-19 Pandemic: A Network Perspective. 271-286 - Kang Wang, Yang Zhao, Yong Dou, Dong Wen, Zikai Gao:
COVID Edge-Net: Automated COVID-19 Lung Lesion Edge Detection in Chest CT Images. 287-301 - Nikki Theeuwes, Geert-Jan van Houtum, Yingqian Zhang:
Improving Ambulance Dispatching with Machine Learning and Simulation. 302-318 - Renhe Jiang, Zhaonan Wang, Zekun Cai, Chuang Yang, Zipei Fan, Tianqi Xia, Go Matsubara, Hiroto Mizuseki, Xuan Song, Ryosuke Shibasaki:
Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19. 319-334 - Taichi Murayama, Shoko Wakamiya, Eiji Aramaki:
Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning. 335-350 - Ivan Kiskin, Adam D. Cobb, Marianne Sinka, Kathy Willis, Stephen J. Roberts:
Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks. 351-366 - Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Recalibrated Aggregation Network for Medical Code Prediction. 367-383 - Miguel Angel Lozano, Òscar Garibo i Orts, Eloy Piñol, Miguel Rebollo, Kristina Polotskaya, Miguel Ángel García-March, J. Alberto Conejero, Francisco Escolano, Nuria Oliver:
Open Data Science to Fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge. 384-399
Mobility and Transportation
- George Forman:
Getting Your Package to the Right Place: Supervised Machine Learning for Geolocation. 403-419 - Louis Zigrand, Pegah Alizadeh, Emiliano Traversi, Roberto Wolfler Calvo:
Machine Learning Guided Optimization for Demand Responsive Transport Systems. 420-436 - Cristian Axenie, Rongye Shi, Daniele Foroni, Alexander Wieder, Mohamad Al Hajj Hassan, Paolo Sottovia, Margherita Grossi, Stefano Bortoli, Götz Brasche:
OBELISC: Oscillator-Based Modelling and Control Using Efficient Neural Learning for Intelligent Road Traffic Signal Calculation. 437-452 - Mingxuan Yue, Yao-Yi Chiang, Cyrus Shahabi:
VAMBC: A Variational Approach for Mobility Behavior Clustering. 453-469 - Xin Du, Jiahai Wang, Siyuan Chen, Zhiyue Liu:
Multi-agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal Control. 470-485 - Chen Dang, Cristina Bazgan, Tristan Cazenave, Morgan Chopin, Pierre-Henri Wuillemin:
Monte Carlo Search Algorithms for Network Traffic Engineering. 486-501 - Michael Wilbur, Ayan Mukhopadhyay, Sayyed Vazirizade, Philip Pugliese, Aron Laszka, Abhishek Dubey:
Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-task and Inductive Transfer Learning. 502-517 - Yu Wang, Gang Xiong, Chang Liu, Zhen Li, Mingxin Cui, Gaopeng Gou:
CQNet: A Clustering-Based Quadruplet Network for Decentralized Application Classification via Encrypted Traffic. 518-534 - Karthik S. Gurumoorthy, Pratik Jawanpuria, Bamdev Mishra:
SPOT: A Framework for Selection of Prototypes Using Optimal Transport. 535-551
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