Data Analytics
Learning from data for optimal decisions.
Our data analytics work addresses predictive modeling techniques, including system identification, anomaly detection, feature selection, and time series analysis, as well as methods to solve various decision optimization problems including continuous optimization, combinatorial optimization, and sequential decision making.
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Researchers
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Awards
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AWARD Best Student Paper Award at the International Conference on Data Mining Date: November 30, 2017
Awarded to: Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn Keogh
MERL Contact: Daniel Nikovski
Research Areas: Data AnalyticsBrief- Yan Zhu, a former MERL intern from the University of California at Riverside has won the Best Student Paper Award at the International Conference on Data Mining in 2017, for her work on time series chains, a novel primitive for time series analysis. The work was done in collaboration with Makoto Imamura, formerly at Information Technology Center/AI Department, and currently a professor at Tokai University in Tokyo, Japan, Daniel Nikovski from MERL, and Yan's advisor, Prof. Eamonn Keogh from UC Riverside, whose lab has had a long and fruitful collaboration with MERL and Mitsubishi Electric.
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AWARD DEIM 2010 Best Paper Award Date: February 1, 2010
Awarded to: Hideya Shibata, Mamoru Kato, Mitsunori Kori and William Yerazunis
Awarded for: "An Automatic Training Data Collection Method for Confidential E-mail Detection"
Awarded by: The Forum on Data Engineering and Information Management (DEIM)
MERL Contact: William Yerazunis
Research Area: Data Analytics -
AWARD SICE 2008 Best Paper Award Date: July 1, 2008
Awarded to: Nishiuma, N.; Goto, Y.; Kumazawa, H.; Komaya K.; Nikovski, D. and Brand, M.
Awarded for: "Travel Time Prediction using Singular Value Decomposition"
Awarded by: Journal of the Society of Instrument and Control Engineers of Japan
MERL Contact: Daniel Nikovski
Research Area: Data Analytics
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News & Events
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NEWS Mouhacine Benosman to deliver keynote at the mini-symposium 'Data assimilation in Model Order Techniques for Computational Mechanics' Date & Time: July 29, 2019; 10 AM
Where: US National Congress on Computational Mechanics 2019, in Austin Texas
MERL Contact: Mouhacine Benosman
Research Areas: Control, Data Analytics, Dynamical SystemsBrief- MERL researcher Mouhacine Benosman will present his work on 'Learning-based Robust Stabilization for Reduced-Order Models of 3D Boussinesq Equations' as a keynote speaker at the mini-symposium 'Data assimilation in Model Order Techniques for Computational Mechanics', during the next US National Congress on Computational Mechanics 2019, in Austin Texas.
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NEWS Mouhacine Benosman co-edited a special issue on Learning-based Adaptive Control: Theory and Applications Date: February 4, 2019
MERL Contact: Mouhacine Benosman
Research Areas: Control, Data Analytics, Dynamical SystemsBrief- Mouhacine Benosman is a guest editor of a special issue on Learning-based Adaptive Control: Theory and Application, recently published by the International Journal of Adaptive Control and Signal Processing. Other guest editors included Professor F.L. Lewis (University of Texas at Arlington Research Institute), Professor M. Guay (Queen's University), and Professor D. Owens (The University of Sheffield).
The special issue presents results of current research on learning-based adaptive methods, merging together model-based and data-driven machine learning approaches.
More information on the content of this special issue can be found at:
https://onlinelibrary.wiley.com/toc/10991115/2019/33/2
- Mouhacine Benosman is a guest editor of a special issue on Learning-based Adaptive Control: Theory and Application, recently published by the International Journal of Adaptive Control and Signal Processing. Other guest editors included Professor F.L. Lewis (University of Texas at Arlington Research Institute), Professor M. Guay (Queen's University), and Professor D. Owens (The University of Sheffield).
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Recent Publications
- , "Introducing Time Series Chains: A New Primitive for Time Series Data Mining", Knowledge and Information Systems, DOI: 10.1007/s10115-018-1224-8, Vol. 60, No. 2, pp. 1135-1161, August 2019.
- , "Anomaly Detection for Insertion Tasks in Robotic Assembly Using Gaussian Process Models", European Control Conference (ECC), June 2019.
- , "Fault Detection and Classification of Time Series Using Localized Matrix Profiles", IEEE International Conference on Prognostics and Health Management, June 2019.
- , "Space-Time Slicing: Visualizing Object Detector Performance in Driving Video Sequences", IEEE Pacific Visualization Symposium (PacificVis), June 2019.
- , "Heat Exchanger Circuitry Design by Decision Diagrams", International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, DOI: 10.1007/978-3-030-19212-9_30, June 2019, vol. 11494, pp. 467-471.
- , "Last-Mile Scheduling Under Uncertainty", International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, DOI: 10.1007/978-3-030-19212-9_34, June 2019, vol. 11494, pp. 519-528.
- , "Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze", IEEE International Conference on Robotics and Automation (ICRA), May 2019.
- , "On the Minimum Chordal Completion Polytope", Operations Research, DOI: 10.1287/opre.2018.1783, Vol. 67, No. 2, pp. 295-597, March 2019.
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