ECML-PKDD 2019
140 papers
A Deep Multi-Task Approach for Residual Value Forecasting
Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches A Differentially Private Kernel Two-Sample Test
Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park A Framework for Parallelizing Hierarchical Clustering Methods
Silvio Lattanzi, Thomas Lavastida, Kefu Lu, Benjamin Moseley A Stochastic Quasi-Newton Method with Nesterov's Accelerated Gradient
S. Indrapriyadarsini, Shahrzad Mahboubi, Hiroshi Ninomiya, Hideki Asai A Tool for Researchers: Querying Big Scholarly Data Through Graph Databases
Fabio Mercorio, Mario Mezzanzanica, Vincenzo Moscato, Antonio Picariello, Giancarlo Sperlì A Virtualized Video Surveillance System for Public Transportation
Talmaj Marinc, Serhan Gül, Cornelius Hellge, Peter Schüßler, Thomas Riegel, Peter Amon Agnostic Feature Selection
Guillaume Doquet, Michèle Sebag An Engineered Empirical Bernstein Bound
Mark Alexander Burgess, Archie C. Chapman, Paul Scott Attentive Multi-Task Deep Reinforcement Learning
Timo Bräm, Gino Brunner, Oliver Richter, Roger Wattenhofer Augmenting Physiological Time Series Data: A Case Study for Sleep Apnea Detection
Konstantinos Nikolaidis, Stein Kristiansen, Vera Goebel, Thomas Plagemann, Knut Liestøl, Mohan S. Kankanhalli Automated Data Transformation with Inductive Programming and Dynamic Background Knowledge
Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Fernando Martínez-Plumed, María José Ramírez-Quintana, Susumu Katayama Automatic Recognition of Student Engagement Using Deep Learning and Facial Expression
Omid Mohamad Nezami, Mark Dras, Len Hamey, Deborah Richards, Stephen Wan, Cécile Paris BK-ADAPT: Dynamic Background Knowledge for Automating Data Transformation
Lidia Contreras Ochando, César Ferri, José Hernández-Orallo, Fernando Martínez-Plumed, María José Ramírez-Quintana, Susumu Katayama Characterization and Early Detection of Evergreen News Articles
Yiming Liao, Shuguang Wang, Eui-Hong Sam Han, Jongwuk Lee, Dongwon Lee Cold-Start Recommendation for On-Demand Cinemas
Beibei Li, Beihong Jin, Taofeng Xue, Kunchi Liu, Qi Zhang, Sihua Tian Data Association with Gaussian Processes
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek Data-Driven Policy on Feasibility Determination for the Train Shunting Problem
Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak Deep Convolutional Gaussian Processes
Kenneth Blomqvist, Samuel Kaski, Markus Heinonen Deep Eyedentification: Biometric Identification Using Micro-Movements of the Eye
Lena A. Jäger, Silvia Makowski, Paul Prasse, Sascha Liehr, Maximilian Seidler, Tobias Scheffer Deep Ordinal Reinforcement Learning
Alexander Zap, Tobias Joppen, Johannes Fürnkranz DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups
Adnene Belfodil, Wouter Duivesteijn, Marc Plantevit, Sylvie Cazalens, Philippe Lamarre Distributed Algorithms to Find Similar Time Series
Oleksandra Levchenko, Boyan Kolev, Djamel Edine Yagoubi, Dennis E. Shasha, Themis Palpanas, Patrick Valduriez, Reza Akbarinia, Florent Masseglia FastPoint: Scalable Deep Point Processes
Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola Fine-Grained Explanations Using Markov Logic
Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal Graph Signal Processing for Directed Graphs Based on the Hermitian Laplacian
Satoshi Furutani, Toshiki Shibahara, Mitsuaki Akiyama, Kunio Hato, Masaki Aida Heavy-Tailed Kernels Reveal a Finer Cluster Structure in T-SNE Visualisations
Dmitry Kobak, George C. Linderman, Stefan Steinerberger, Yuval Kluger, Philipp Berens Importance Weighted Generative Networks
Maurice Diesendruck, Ethan R. Elenberg, Rajat Sen, Guy W. Cole, Sanjay Shakkottai, Sinead A. Williamson Integrating Learning and Reasoning with Deep Logic Models
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori Joint Multi-Source Reduction
Lei Zhang, Shupeng Wang, Xin Jin, Siyu Jia Learning to Calibrate and Rerank Multi-Label Predictions
Cheng Li, Virgil Pavlu, Javed A. Aslam, Bingyu Wang, Kechen Qin Learning to Signal in the Goldilocks Zone: Improving Adversary Compliance in Security Games
Sarah Cooney, Kai Wang, Elizabeth Bondi, Thanh Hong Nguyen, Phebe Vayanos, Hailey Winetrobe, Edward A. Cranford, Cleotilde Gonzalez, Christian Lebiere, Milind Tambe Learning with Random Learning Rates
Léonard Blier, Pierre Wolinski, Yann Ollivier Link Prediction via Higher-Order Motif Features
Ghadeer Abuoda, Gianmarco De Francisci Morales, Ashraf Aboulnaga LSTM Encoder-Predictor for Short-Term Train Load Forecasting
Kevin Pasini, Mostepha Khouadjia, Allou Samé, Fabrice Ganansia, Latifa Oukhellou Meta-Learning for Black-Box Optimization
Vishnu Tv, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff Multitask Hopfield Networks
Marco Frasca, Giuliano Grossi, Giorgio Valentini Node Representation Learning for Directed Graphs
Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand On the Stability of Feature Selection in the Presence of Feature Correlations
Konstantinos Sechidis, Konstantinos Papangelou, Sarah Nogueira, James Weatherall, Gavin Brown Online Linear Models for Edge Computing
Hadar Sivan, Moshe Gabel, Assaf Schuster Optimizing Neural Networks for Patent Classification
Louay Abdelgawad, Peter Kluegl, Erdan Genc, Stefan Falkner, Frank Hutter Pattern-Based Anomaly Detection in Mixed-Type Time Series
Len Feremans, Vincent Vercruyssen, Boris Cule, Wannes Meert, Bart Goethals Practical Open-Loop Optimistic Planning
Edouard Leurent, Odalric-Ambrym Maillard Pushing the Limits of Exoplanet Discovery via Direct Imaging with Deep Learning
Kai Hou Yip, Nikolaos Nikolaou, Piero Coronica, Angelos Tsiaras, Billy Edwards, Quentin Changeat, Mario Morvan, Beth Biller, Sasha Hinkley, Jeffrey Salmond, Matthew Archer, Paul Sumption, Elodie Choquet, Remi Soummer, Laurent Pueyo, Ingo P. Waldmann Scalable Bid Landscape Forecasting in Real-Time Bidding
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan Shallow Self-Learning for Reject Inference in Credit Scoring
Nikita Kozodoi, Panagiotis Katsas, Stefan Lessmann, Luís Moreira-Matias, Konstantinos Papakonstantinou Shift Happens: Adjusting Classifiers
Theodore James Thibault Heiser, Mari-Liis Allikivi, Meelis Kull Single-Path NAS: Designing Hardware-Efficient ConvNets in Less than 4 Hours
Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu Stochastic Activation Actor Critic Methods
Wenling Shang, Douwe van der Wal, Herke van Hoof, Max Welling String Sanitization: A Combinatorial Approach
Giulia Bernardini, Huiping Chen, Alessio Conte, Roberto Grossi, Grigorios Loukides, Nadia Pisanti, Solon P. Pissis, Giovanna Rosone Towards a Predictive Patent Analytics and Evaluation Platform
Nebula Alam, Khoi-Nguyen Tran, Sue Ann Chen, John Wagner, Josh Andres, Mukesh K. Mohania Trade-Offs in Large-Scale Distributed Tuplewise Estimation and Learning
Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa Transfer Learning in Credit Risk
Hendra Suryanto, Charles Guan, Andrew Voumard, Ghassan Beydoun Uncovering Hidden Block Structure for Clustering
Luce le Gorrec, Sandrine Mouysset, Iain S. Duff, Philip A. Knight, Daniel Ruiz UnFOOT: Unsupervised Football Analytics Tool
José Carlos Coutinho, João Mendes-Moreira, Cláudio Rebelo de Sá Unjustified Classification Regions and Counterfactual Explanations in Machine Learning
Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, Marcin Detyniecki Unsupervised and Active Learning Using Maximin-Based Anomaly Detection
Zahra Ghafoori, James C. Bezdek, Christopher Leckie, Shanika Karunasekera Wearable-Based Parkinson's Disease Severity Monitoring Using Deep Learning
Jann Goschenhofer, Franz Michael Josef Pfister, Kamer Ali Yuksel, Bernd Bischl, Urban Fietzek, Janek Thomas