ECML-PKDD 2020
205 papers
A Context-Aware Approach to Detect Abnormal Human Behaviors
Roghayeh Mojarad, Ferhat Attal, Abdelghani Chibani, Yacine Amirat A Deep Dive into Multilingual Hate Speech Classification
Sai Saketh Aluru, Binny Mathew, Punyajoy Saha, Animesh Mukherjee A Framework for Deep Quantification Learning
Lei Qi, Mohammed Khaleel, Wallapak Tavanapong, Adisak Sukul, David A. M. Peterson A General Machine Learning Framework for Survival Analysis
Andreas Bender, David Rügamer, Fabian Scheipl, Bernd Bischl A Principle of Least Action for the Training of Neural Networks
Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari A Relaxation-Based Approach for Mining Diverse Closed Patterns
Arnold Hien, Samir Loudni, Noureddine Aribi, Yahia Lebbah, Mohammed El Amine Laghzaoui, Abdelkader Ouali, Albrecht Zimmermann Activation Anomaly Analysis
Philip Sperl, Jan-Philipp Schulze, Konstantin Böttinger ADMMiRNN: Training RNN with Stable Convergence via an Efficient ADMM Approach
Yu Tang, Zhigang Kan, Dequan Sun, Linbo Qiao, Jingjing Xiao, Zhiquan Lai, Dongsheng Li AMQAN: Adaptive Multi-Attention Question-Answer Networks for Answer Selection
Haitian Yang, Weiqing Huang, Xuan Zhao, Yan Wang, Yuyan Chen, Bin Lv, Rui Mao, Ning Li An Advert Creation System for 3D Product Placements
Ivan Bacher, Hossein Javidnia, Soumyabrata Dev, Rahul Agrahari, Murhaf Hossari, Matthew Nicholson, Clare Conran, Jian Tang, Peng Song, David Corrigan, François Pitié An Algorithmic Framework for Decentralised Matrix Factorisation
Erika Duriakova, Weipéng Huáng, Elias Z. Tragos, Aonghus Lawlor, Barry Smyth, James Geraci, Neil Hurley Automated Integration of Genomic Metadata with Sequence-to-Sequence Models
Giuseppe Cannizzaro, Michele Leone, Anna Bernasconi, Arif Canakoglu, Mark J. Carman Automated Quality Assurance for Hand-Held Tools via Embedded Classification and AutoML
Christoffer Löffler, Christian Nickel, Christopher Sobel, Daniel Dzibela, Jonathan Braat, Benjamin Gruhler, Philipp Woller, Nicolas Witt, Christopher Mutschler Automation of Leasing Vehicle Return Assessment Using Deep Learning Models
Mohsan Jameel, Mofassir ul Islam Arif, Andre Hintsches, Lars Schmidt-Thieme AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models
Qing Cui, Qitao Shi, Hao Qian, Caizhi Tang, Xixi Li, Yiming Zhao, Tao Jiang, Longfei Li, Jun Zhou Bayesian Optimization with Missing Inputs
Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh Companion Guided Soft Margin for Face Recognition
Yingcheng Su, Yichao Wu, Zhenmao Li, Qiushan Guo, Ken Chen, Junjie Yan, Ding Liang, Xiaolin Hu Confusable Learning for Large-Class Few-Shot Classification
Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long Deep Reinforcement Learning (DRL) for Portfolio Allocation
Eric Benhamou, David Saltiel, Jean-Jacques Ohana, Jamal Atif, Rida Laraki Deep Reinforcement Learning for Large-Scale Epidemic Control
Pieter J. K. Libin, Arno Moonens, Timothy Verstraeten, Fabian Perez-Sanjines, Niel Hens, Philippe Lemey, Ann Nowé Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL
Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen Early Detection of Fake News with Multi-Source Weak Social Supervision
Kai Shu, Guoqing Zheng, Yichuan Li, Subhabrata Mukherjee, Ahmed Hassan Awadallah, Scott W. Ruston, Huan Liu Energy Consumption Forecasting Using a Stacked Nonparametric Bayesian Approach
Dilusha Weeraddana, Nguyen Lu Dang Khoa, Lachlan O'Neil, Weihong Wang, Chen Cai Explaining End-to-End ECG Automated Diagnosis Using Contextual Features
Derick M. de Oliveira, Antônio H. Ribeiro, João A. O. Pedrosa, Gabriela M. M. Paixão, Antônio Luiz P. Ribeiro, Wagner Meira Jr. Fairness by Explicability and Adversarial SHAP Learning
James M. Hickey, Pietro G. Di Stefano, Vlasios Vasileiou Fashion Outfit Generation for E-Commerce
Elaine M. Bettaney, Stephen R. Hardwick, Odysseas Zisimopoulos, Benjamin Paul Chamberlain Federated Multi-View Matrix Factorization for Personalized Recommendations
Adrian Flanagan, Were Oyomno, Alexander Grigorievskiy, Kuan Eeik Tan, Suleiman A. Khan, Muhammad Ammad-ud-din Feedback-Guided Attributed Graph Embedding for Relevant Video Recommendation
Taofeng Xue, Xinzhou Dong, Wei Zhuo, Beihong Jin, He Chen, Wenhai Pan, Beibei Li, Xuejian Zhang Few-Shot Microscopy Image Cell Segmentation
Youssef Dawoud, Julia Hornauer, Gustavo Carneiro, Vasileios Belagiannis Filling Gaps in Micro-Meteorological Data
Antoine Richard, Lior Fine, Offer Rozenstein, Josef Tanny, Matthieu Geist, Cédric Pradalier Finding the Optimal Network Depth in Classification Tasks
Bartosz Wójcik, Maciej Wolczyk, Klaudia Balazy, Jacek Tabor FireAnt: Claim-Based Medical Misinformation Detection and Monitoring
Branislav Pecher, Ivan Srba, Róbert Móro, Matús Tomlein, Mária Bieliková Flexible Recurrent Neural Networks
Anne Lambert, Françoise Le Bolzer, François Schnitzler FlowFrontNet: Improving Carbon Composite Manufacturing with CNNs
Simon Stieber, Niklas Schröter, Alexander Schiendorfer, Alwin Hoffmann, Wolfgang Reif FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-Grams
Wanzheng Zhu, Hongyu Gong, Jiaming Shen, Chao Zhang, Jingbo Shang, Suma Bhat, Jiawei Han GIKT: A Graph-Based Interaction Model for Knowledge Tracing
Yang Yang, Jian Shen, Yanru Qu, Yunfei Liu, Kerong Wang, Yaoming Zhu, Weinan Zhang, Yong Yu Graph Diffusion Wasserstein Distances
Amélie Barbe, Marc Sebban, Paulo Gonçalves, Pierre Borgnat, Rémi Gribonval Graph-Revised Convolutional Network
Donghan Yu, Ruohong Zhang, Zhengbao Jiang, Yuexin Wu, Yiming Yang Inductive Document Representation Learning for Short Text Clustering
Junyang Chen, Zhiguo Gong, Wei Wang, Xiao Dong, Wei Wang, Weiwen Liu, Cong Wang, Xian Chen Inductive Generalized Zero-Shot Learning with Adversarial Relation Network
Guanyu Yang, Kaizhu Huang, Rui Zhang, John Yannis Goulermas, Amir Hussain Lagrangian Duality for Constrained Deep Learning
Ferdinando Fioretto, Pascal Van Hentenryck, Terrence W. K. Mak, Cuong Tran, Federico Baldo, Michele Lombardi Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting
Léo Gautheron, Pascal Germain, Amaury Habrard, Guillaume Metzler, Emilie Morvant, Marc Sebban, Valentina Zantedeschi Learning Gradient Boosted Multi-Label Classification Rules
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier Learning to Simulate on Sparse Trajectory Data
Hua Wei, Chacha Chen, Chang Liu, Guanjie Zheng, Zhenhui Li Long-Term Pipeline Failure Prediction Using Nonparametric Survival Analysis
Dilusha Weeraddana, Sudaraka Mallawaarachchi, Tharindu Warnakula, Zhidong Li, Yang Wang Massively Distributed Clustering via Dirichlet Process Mixture
Khadidja Meguelati, Benedicte Fontez, Nadine Hilgert, Florent Masseglia, Isabelle Sanchez Measuring Immigrants Adoption of Natives Shopping Consumption with Machine Learning
Riccardo Guidotti, Mirco Nanni, Fosca Giannotti, Dino Pedreschi, Simone Bertoli, Biagio Speciale, Hillel Rapoport Mining Dense Subgraphs with Similar Edges
Polina Rozenshtein, Giulia Preti, Aristides Gionis, Yannis Velegrakis Model-Based Clustering with HDBSCAN
Michael Strobl, Jörg Sander, Ricardo J. G. B. Campello, Osmar R. Zaïane Multi-Future Merchant Transaction Prediction
Chin-Chia Michael Yeh, Zhongfang Zhuang, Wei Zhang, Liang Wang Multi-Imbalance: Open Source Python Toolbox for Multi-Class Imbalanced Classification
Jacek Grycza, Damian Horna, Hanna Klimczak, Mateusz Lango, Kamil Plucinski, Jerzy Stefanowski Networked Point Process Models Under the Lens of Scrutiny
Guilherme R. Borges, Flavio Figueiredo, Renato M. Assunção, Pedro O. S. Vaz de Melo On Saliency Maps and Adversarial Robustness
Puneet Mangla, Vedant Singh, Vineeth N. Balasubramanian On-Site Gamma-Hadron Separation with Deep Learning on FPGAs
Sebastian Buschjäger, Lukas Pfahler, Jens Buß, Katharina Morik, Wolfgang Rhode Online Partial Label Learning
Haobo Wang, Yuzhou Qiang, Chen Chen, Weiwei Liu, Tianlei Hu, Zhao Li, Gang Chen Open Set Domain Adaptation Using Optimal Transport
Marwa Kechaou, Romain Hérault, Mokhtar Z. Alaya, Gilles Gasso Orthant Based Proximal Stochastic Gradient Method for ℓ 1-Regularized Optimization
Tianyi Chen, Tianyu Ding, Bo Ji, Guanyi Wang, Yixin Shi, Jing Tian, Sheng Yi, Xiao Tu, Zhihui Zhu Orthogonal Mixture of Hidden Markov Models
Negar Safinianaini, Camila P. E. de Souza, Henrik Boström, Jens Lagergren Poisoning Attacks on Algorithmic Fairness
David Solans, Battista Biggio, Carlos Castillo Privacy-Preserving Decision Trees Training and Prediction
Adi Akavia, Max Leibovich, Yehezkel S. Resheff, Roey Ron, Moni Shahar, Margarita Vald Probabilistic Reconciliation of Hierarchical Forecast via Bayes' Rule
Giorgio Corani, Dario Azzimonti, João P. S. C. Augusto, Marco Zaffalon Progressive Supervision for Node Classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi Real-Time Lane Configuration with Coordinated Reinforcement Learning
Udesh Gunarathna, Hairuo Xie, Egemen Tanin, Shanika Karunasekera, Renata Borovica-Gajic Reprogramming GANs via Input Noise Design
Kangwook Lee, Changho Suh, Kannan Ramchandran Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S. Rosenblum Robust Domain Adaptation: Representations, Weights and Inductive Bias
Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot Scalable Backdoor Detection in Neural Networks
Haripriya Harikumar, Vuong Le, Santu Rana, Sourangshu Bhattacharya, Sunil Gupta, Svetha Venkatesh Self-Supervised Log Parsing
Sasho Nedelkoski, Jasmin Bogatinovski, Alexander Acker, Jorge Cardoso, Odej Kao Simple, Scalable, and Stable Variational Deep Clustering
Lele Cao, Sahar Asadi, Wenfei Zhu, Christian Schmidli, Michael Sjöberg Sparse Separable Nonnegative Matrix Factorization
Nicolas Nadisic, Arnaud Vandaele, Jeremy E. Cohen, Nicolas Gillis SpecGreedy: Unified Dense Subgraph Detection
Wenjie Feng, Shenghua Liu, Danai Koutra, Huawei Shen, Xueqi Cheng Stop the Clock: Are Timeout Effects Real?
Niander Assis, Renato M. Assunção, Pedro O. S. Vaz de Melo Tackling Noise in Active Semi-Supervised Clustering
Jonas Soenen, Sebastijan Dumancic, Toon van Craenendonck, Hendrik Blockeel Target to Source Coordinate-Wise Adaptation of Pre-Trained Models
Luxin Zhang, Pascal Germain, Yacine Kessaci, Christophe Biernacki Temporal Heterogeneous Interaction Graph Embedding for Next-Item Recommendation
Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi To Ensemble or Not Ensemble: When Does End-to-End Training Fail?
Andrew M. Webb, Charles Reynolds, Wenlin Chen, Henry W. J. Reeve, Dan-Andrei Iliescu, Mikel Luján, Gavin Brown Topological Insights into Sparse Neural Networks
Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu Unsupervised Human Pose Estimation on Depth Images
Thibault Blanc-Beyne, Axel Carlier, Sandrine Mouysset, Vincent Charvillat Unsupervised Multi-Source Domain Adaptation for Regression
Guillaume Richard, Antoine de Mathelin, Georges Hébrail, Mathilde Mougeot, Nicolas Vayatis Utilizing Structure-Rich Features to Improve Clustering
Benjamin Schelling, Lena Greta Marie Bauer, Sahar Behzadi, Claudia Plant VisualSynth: Democratizing Data Science in Spreadsheets
Clément Gautrais, Yann Dauxais, Samuel Kolb, Arcchit Jain, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt