Table of Contents

• Anomaly Detection: How to Artificially Increase Your F1-Score with a Biased Evaluation ProtocolDamien Fourure, Muhammad Usama Javaid, Nicolas Posocco, Simon Tihon. 3-18 [doi]
• Mining Anomalies in Subspaces of High-Dimensional Time Series for Financial Transactional DataJingzhu He, Chin-Chia Michael Yeh, Yanhong Wu, Liang Wang, Wei Zhang. 19-36 [doi]
• AIMED-RL: Exploring Adversarial Malware Examples with Reinforcement LearningRaphael Labaca Castro, Sebastian Franz, Gabi Dreo Rodosek. 37-52 [doi]
• Learning Explainable Representations of Malware BehaviorPaul Prasse, Jan Brabec, Jan Kohout, Martin Kopp, Lukás Bajer, Tobias Scheffer. 53-68 [doi]
• Strategic Mitigation Against Wireless Attacks on Autonomous PlatoonsGuoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe. 69-84 [doi]
• DeFraudNet: An End-to-End Weak Supervision Framework to Detect Fraud in Online Food DeliveryJose Mathew, Meghana Negi, Rutvik Vijjali, Jairaj Sathyanarayana. 85-99 [doi]
• Time Series Forecasting with Gaussian Processes Needs PriorsGiorgio Corani, Alessio Benavoli, Marco Zaffalon. 103-117 [doi]
• Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series ForecastJens Schreiber, Stephan Vogt, Bernhard Sick. 118-134 [doi]
• Generating Multi-type Temporal Sequences to Mitigate Class-Imbalanced ProblemLun Jiang, Nima Salehi Sadghiani, Zhuo Tao, Andrew Cohen. 135-150 [doi]
• Recognizing Skeleton-Based Hand Gestures by a Spatio-Temporal NetworkXin Li, Jun Liao, Li Liu 0001. 151-167 [doi]
• Smurf-Based Anti-money Laundering in Time-Evolving Transaction NetworksMichele 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. 171-186 [doi]
• Spatio-Temporal Multi-graph Networks for Demand Forecasting in Online MarketplacesAnkit Gandhi, Aakanksha, Sivaramakrishnan Kaveri, Vineet Chaoji. 187-203 [doi]
• The Limit Order Book Recreation Model (LOBRM): An Extended AnalysisZijian Shi, John Cartlidge. 204-220 [doi]
• Taking over the Stock Market: Adversarial Perturbations Against Algorithmic TradersElior Nehemya, Yael Mathov, Asaf Shabtai, Yuval Elovici. 221-236 [doi]
• Continuous-Action Reinforcement Learning for Portfolio Allocation of a Life Insurance CompanyCarlo Abrate, Alessio Angius, Gianmarco De Francisci Morales, Stefano Cozzini, Francesca Iadanza, Laura Li Puma, Simone Pavanelli, Alan Perotti, Stefano Pignataro, Silvia Ronchiadin. 237-252 [doi]
• XRR: Explainable Risk Ranking for Financial ReportsTing-Wei Lin, Ruei-Yao Sun, Hsuan-Ling Chang, Chuan-Ju Wang, Ming-Feng Tsai. 253-268 [doi]
• Self-disclosure on Twitter During the COVID-19 Pandemic: A Network PerspectivePrasanna Umar, Chandan Akiti, Anna Cinzia Squicciarini, Sarah Michele Rajtmajer. 271-286 [doi]
• COVID Edge-Net: Automated COVID-19 Lung Lesion Edge Detection in Chest CT ImagesKang Wang, Yang Zhao 0003, Yong Dou, Dong Wen, Zikai Gao. 287-301 [doi]
• Improving Ambulance Dispatching with Machine Learning and SimulationNikki Theeuwes, Geert-Jan van Houtum, Yingqian Zhang. 302-318 [doi]
• Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19Renhe Jiang, Zhaonan Wang, Zekun Cai, Chuang Yang, Zipei Fan, Tianqi Xia, Go Matsubara, Hiroto Mizuseki, Xuan Song, Ryosuke Shibasaki. 319-334 [doi]
• Single Model for Influenza Forecasting of Multiple Countries by Multi-task LearningTaichi Murayama, Shoko Wakamiya, Eiji Aramaki. 335-350 [doi]
• Automatic Acoustic Mosquito Tagging with Bayesian Neural NetworksIvan Kiskin, Adam D. Cobb, Marianne Sinka, Kathy Willis, Stephen J. Roberts. 351-366 [doi]
• Multitask Recalibrated Aggregation Network for Medical Code PredictionWei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen. 367-383 [doi]
• Open Data Science to Fight COVID-19: Winning the 500k XPRIZE Pandemic Response ChallengeMiguel Angel Lozano, Òscar Garibo i Orts, Eloy Piñol, Miguel Rebollo, Kristina Polotskaya, Miguel Ángel García-March, J. Alberto Conejero, Francisco Escolano, Nuria Oliver. 384-399 [doi]
• Getting Your Package to the Right Place: Supervised Machine Learning for GeolocationGeorge Forman. 403-419 [doi]
• Machine Learning Guided Optimization for Demand Responsive Transport SystemsLouis Zigrand, Pegah Alizadeh, Emiliano Traversi, Roberto Wolfler Calvo. 420-436 [doi]
• OBELISC: Oscillator-Based Modelling and Control Using Efficient Neural Learning for Intelligent Road Traffic Signal CalculationCristian Axenie, Rongye Shi, Daniele Foroni, Alexander Wieder, Mohamad Al Hajj Hassan, Paolo Sottovia, Margherita Grossi, Stefano Bortoli, Götz Brasche. 437-452 [doi]
• VAMBC: A Variational Approach for Mobility Behavior ClusteringMingxuan Yue, Yao-Yi Chiang, Cyrus Shahabi. 453-469 [doi]
• Multi-agent Deep Reinforcement Learning with Spatio-Temporal Feature Fusion for Traffic Signal ControlXin Du, Jiahai Wang, Siyuan Chen, Zhiyue Liu. 470-485 [doi]
• Monte Carlo Search Algorithms for Network Traffic EngineeringChen Dang, Cristina Bazgan, Tristan Cazenave, Morgan Chopin, Pierre-Henri Wuillemin. 486-501 [doi]
• Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-task and Inductive Transfer LearningMichael Wilbur, Ayan Mukhopadhyay, Sayyed Vazirizade, Philip Pugliese, Aron Laszka, Abhishek Dubey. 502-517 [doi]
• CQNet: A Clustering-Based Quadruplet Network for Decentralized Application Classification via Encrypted TrafficYu Wang, Gang Xiong 0001, Chang Liu, Zhen Li, Mingxin Cui, Gaopeng Gou. 518-534 [doi]
• SPOT: A Framework for Selection of Prototypes Using Optimal TransportKarthik S. Gurumoorthy, Pratik Jawanpuria, Bamdev Mishra. 535-551 [doi]