WORKSHOP

Workshop on Learning and Mining with Industrial Data (LMID 2019) will be held in conjunction with the 2019 IEEE International Conference on Data Mining (ICDM 2019) on November 8. The conference/workshop venue is in Beijing, China.

INTRODUCTION

Digital technologies, the Internet of Things (IoT), cloud computing, and edge computing are transforming manufacturing and industry. Machine learning and data mining on industrial data have crucial impact on optimizing all aspects in the manufacturing process, including design, engineering, manufacturing, supply chain, and services. This research field also brings some challenges for learning methods, such as interconnected sensor data, real-time learning, multimodal data analysis, and resource-constrained devices. This workshop aims to bring together researchers and practitioners from academia and industry to discuss challenges, emerging topics, and recent advances in learning and mining with industrial data.

TOPICS

We encourage submissions on theory, methods, and applications on various aspects in industrial data analysis. Topics of interest include, but are not limited to:

• Mining graph and networked data
• Time Series and streaming data analysis
• Learning with heterogeneous and multimodal data
• Scalability, online learning
• Low-resource machine learning
• Preference learning, opinion mining
• Anomaly detection, predictive maintenance
• Knowledge graph and knowledge integration
• Reinforcement learning, optimization
• Optimization and learning with simulation-based data
• Applications, case studies, software tools

SUBMISSION & PUBLICATION

All submissions should be between four (4) and eight (8) pages, and follow the IEEE ICDM format (see the IEEE ICDM 2019 Submission Guidelines for more details). All submissions will be triple-blind reviewed on the basis of the ICDM review policy. Please submit your manuscript through the ICDM 2019 submission site.

All accepted submissions will be included in the IEEE ICDM 2019 Workshops Proceedings published by IEEE Computer Society Press, and will be also included in the IEEE Computer Society Digital Library (CSDL) and IEEE Xplore (indexed by EI).

IMPORTANT DATES

Paper submission: August 18, 2019
Paper notification: September 4, 2019
Camera-ready deadline and copyright forms: September 8, 2019
Workshop date: November 8 2019, 13:00-18:00

INVITED SPEAKERS

• Prof. Bogdan Gabrys
  University of Technology Sydney, Australia
  


• Prof. Xin Yao
  University of Birmingham, UK
  Sourthern University of Science and Technology, China
  

PROGRAM

13:00-13:10	Opening
13:10-14:10	Keynote: Automated composition, optimisation and adaptation of complex predictive systems 　Bogdan Gabrys
14:10-15:30	Scoring Message Stream Anomalies in Railway Communication Systems 　Lucas Foulon, Serge Fenet, Christophe Rigotti, and Denis Jouvin Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection 　Naoya Takeishi Automated Machine Learning Techniques in Prognostics of Railway Track Defects 　Simon Kocbek and Bogdan Gabrys Data Mining in Railway Defect Image Based on Object Detection Technology 　Bing Zhao, Mingrui Dai, Ping Li, Xiaoning Ma
15:30-16:00	Coffee Break
16:00-16:30	Keynote: TBA 　Xin Yao
16:30-17:50	Identifying Topological Prototypes using Deep Point Cloud Autoencoder Networks 　Nidhi Nivesh Dommaraju, Mariusz Bujny, Stefan Menzel, Markus Olhofer, and Fabian Duddeck Data-driven insights from predictive analytics on heterogeneous experimental data of industrial magnetic materials 　Zijiang Yang, Tetsushi Watari, Daisuke Ichigozaki, Kei Morohoshi, Yoshinori Suga, Wei-keng Liao, Alok Choudhary, and Ankit Agrawal Learning Time-series Data of Industrial Design Optimization using Recurrent Neural Networks 　Sneha Saha, Thiago Rios, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck, Xin Yao, Zhao Xu, and Patricia Wollstadt A Dynamically Adaptive Movie Occupancy Forecasting System with Feature Optimization 　Sundararaman Venkataramani, Ateendra Ramesh, Sharan Sundar S, Aashish Kumar Jain, Gautham Krishna Gudur, and Vineeth Vijayaraghavan
17:50-18:00	Closing

WORKSHOP ORGANIZATION

Organization Committee

• Zhao Xu, NEC Laboratories Europe, Germany
  Thomas Bäck, Leiden University, Netherlands
  Leandro Minku, University of Birmingham, UK
  Stefan Menzel, Honda Research Institute Europe, Germany
  

Program Committee

• Volker Tresp, Siemens, Germany
  Alberto GarciaDuran, EPFL, Switzerland
  Mathias Niepert, NEC Laboratories Europe, Germany
  Tim Wirtz, Fraunhofer IAIS, Germany
  Felix Wittleben, Leiden University, Netherlands
  Sebastian Schmitt, Honda Research Institute Europe, Germany
  Rémi Philippe Lebret, EPFL, Switzerland
  Chun Wai Chiu, University of Birmingham, UK
  Carolin Lawrence, NEC Laboratories Europe, Germany
  Peter Tino, University of Birmingham, UK
  Xiahan Shi, Bosch, Germany
  Wojtek Kowalczyk, Leiden University, Netherlands
  Steffen Frik, DYNAmore, Germany
  Yaochu Jin, University of Surrey, UK
  Markus Olhofer, Honda Research Institute Europe, Germany
  Liyan Song, University of Birmingham, UK
  Gustavo Oliveira, Federal University of Pernambuco, Brazil
  Hao Wang, Leiden University, Netherlands
  Tobias Rodemann, Honda Research Institute Europe, Germany
  Krzysztof Krawiec, Poznan University of Technology, Poland
  Daniel OnoroRubio, NEC Laboratories Europe, Germany
  Giacomo Boracchi, Politecnico di Milano, Italy
  Shujian Yu, NEC Laboratories Europe, Germany
  Steffen Limmer, Honda Research Institute Europe, Germany
  Jun Cheng, Technical University of Munich, Germany
  Mohammad Nabi Omidvar, University of Birmingham, UK
  Heike Trautmann, University of Münster, Germany
  Jerzy Stefanowski, Poznan University of Technology, Poland
  Martin Schiegg, Bosch, Germany
  Bogdan Gabrys, University of Technology Sydney, Australia
  Patricia Wollstadt, Honda Research Institute Europe, Germany
  

ACKNOWLEDGEMENT

The organizers would like to acknowledge the support provided by the EU Marie Skłodowska-Curie Actions (MSCA) project ECOLE.

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