Eamonn Keogh

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Mining Time Series Data

Eamonn Keogh, 2005 .

SAXually Explicit Images: Finding Unusual Shapes

Li Wei, Eamonn J. Keogh, Eamonn Keogh, 2006, Sixth International Conference on Data Mining (ICDM'06).

Improving efficiency and effectiveness of dynamic time warping in large time series databases

Chotirat Ann Ratanamahatana, Eamonn Keogh, 2005 .

Learning from time series in the presence of noise: unsupervised and semi-supervised approaches

Eamonn J. Keogh, Eamonn Keogh, Dragomir Yankov, 2008 .

Semi-supervised time series classification

Li Wei, Eamonn J. Keogh, Eamonn Keogh, 2006, KDD '06.

Intelligent Icons: Integrating Lite-Weight Data Mining and Visualization into GUI Operating Systems

Li Wei, Eamonn J. Keogh, Stefano Lonardi, 2006, Sixth International Conference on Data Mining (ICDM'06).

Fast Best-Match Shape Searching in Rotation-Invariant Metric Spaces

Li Wei, Eamonn Keogh, Dragomir Yankov, 2008, IEEE Transactions on Multimedia.

Assumption-Free Anomaly Detection in Time Series

Li Wei, Stefano Lonardi, Chotirat Ann Ratanamahatana, 2005, SSDBM.

Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification

Geoffrey I. Webb, Germain Forestier, Ann E. Nicholson, 2014, 2014 IEEE International Conference on Data Mining.

Efficient pattern discovery in massive time series databases

Li Wei, Eamonn Keogh, 2006 .

Compression-based data mining of sequential data

Li Wei, John C. Handley, Eamonn J. Keogh, 2007, Data Mining and Knowledge Discovery.

Eamonn J. Keogh, Yan Zhu, Eamonn Keogh, 2019, IEEE Transactions on Multimedia.

Eamonn Keogh, Gustavo E. A. P. A. Batista, Diego Furtado Silva, 2018 .

Matrix Profile XV: Exploiting Time Series Consensus Motifs to Find Structure in Time Series Sets

Eamonn Keogh, Shaghayegh Gharghabi, Kaveh Kamgar, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Exact Indexing of Dynamic Time Warping

Eamonn Keogh, 2002, VLDB.

Complex Adaptive System

John Case, Jean-Michel Renders, Eamonn J. Keogh, 2010, Encyclopedia of Machine Learning.

A Computational System to Support Fully Automated Mark-Recapture Studies of Ants

Eamonn Keogh, Carey Yoon, Frank Madrid, 2019, 2019 International Conference on Computational Science and Computational Intelligence (CSCI).

Fast Best-Match Shape Searching in Rotation-Invariant Metric Spaces

Li Wei, Eamonn J. Keogh, Eamonn Keogh, 2007, IEEE Transactions on Multimedia.

Test Set

Risto Miikkulainen, Marko Grobelnik, Pierre Flener, 2010, Encyclopedia of Machine Learning and Data Mining.

HOT SAX: Finding the Most Unusual Time Series Subsequence: Algorithms and Applications

Jessica Lin, Eamonn Keogh, Ada Wai-Chee Fu, 2004 .

Exact indexing of dynamic time warping

Eamonn J. Keogh, Chotirat Ann Ratanamahatana, Eamonn Keogh, 2002, Knowledge and Information Systems.

R Bindings for the UCR Suite [R package rucrdtw version 0.1.4]

Eamonn J. Keogh, Eamonn Keogh, Gustavo E. A. P. A. Batista, 2020 .

Data mining techniques on historical image databases

Eamonn Keogh, Xiaoyue Wang, 2010 .

Everything you know about Dynamic Time Warping is Wrong

Eamonn J. Keogh, Chotirat Ann Ratanamahatana, Eamonn Keogh, 2004 .

Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms

Eamonn J. Keogh, Eamonn Keogh, Shima Imani, 2020, KDD.

Introducing time series chains: a new primitive for time series data mining

Eamonn J. Keogh, Yan Zhu, Eamonn Keogh, 2019, Knowledge and Information Systems.

Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures

Pavlos Protopapas, Eamonn J. Keogh, Eamonn Keogh, 2008, The VLDB Journal.

A Practical Tool for Visualizing and Data Mining Medical Time Series

Li Wei, Eamonn J. Keogh, Stefano Lonardi, 2005, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05).

A novel technique for indexing video surveillance data

Chotirat Ann Ratanamahatana, Eamonn Keogh, Bhrigu Celly, 2003, IWVS '03.

LB_Keogh supports exact indexing of shapes under rotation invariance with arbitrary representations and distance measures

Eamonn J. Keogh, Eamonn Keogh, Michail Vlachos, 2006, VLDB.

Matrix Profile XVI: Efficient and Effective Labeling of Massive Time Series Archives

Eamonn Keogh, Shailendra Singh, Frank Madrid, 2019, 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series

Eamonn Keogh, Shima Imani, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Features or Shape? Tackling the False Dichotomy of Time Series Classification pdf

Eamonn Keogh, Sara Alaee, Alireza Abdoli, 2020, SDM.

Segmenting Time Series: A Survey and Novel Approach

Eamonn J. Keogh, Eamonn Keogh, Michael J. Pazzani, 2002 .

Efficiently finding unusual shapes in large image databases

Li Wei, Eamonn J. Keogh, Eamonn Keogh, 2008, Data Mining and Knowledge Discovery.

Discovering unusual and non-trivial patterns in massive time series databases

Eamonn Keogh, Jessica Lin, 2005 .

Indexing and Mining Time Series Data

Eamonn Keogh, 2008 .

Multi-Resolution K-Means Clustering of Time Series and Application to Images

Dimitrios Gunopulos, Eamonn J. Keogh, Jessica Lin, 2003 .

Making Image Retrieval and Classification More Accurate Using Time Series and Learned Constraints

Vit Niennattrakul, Chotirat Ann Ratanamahatana, Eamonn Keogh, 2009 .

An ultra-fast time series distance measure to allow data mining in more complex real-world deployments

Eamonn J. Keogh, Eamonn Keogh, Anthony Bagnall, 2020, Data Mining and Knowledge Discovery.

Certainty Equivalence Principle

Jean-Michel Renders, João Gama, Lise Getoor, 2010, Encyclopedia of Machine Learning and Data Mining.

Click-Through Rate (CTR)

Jean-Michel Renders, João Gama, Eamonn J. Keogh, 2010, Encyclopedia of Machine Learning and Data Mining.

Integrating Lite-Weight but Ubiquitous Data Mining into GUI Operating Systems

Li Wei, Eamonn J. Keogh, Stefano Lonardi, 2005, J. Univers. Comput. Sci..

A Wavelet-Based Anytime Algorithm for K-Means Clustering of Time Series

Dimitrios Gunopulos, Eamonn J. Keogh, Jessica Lin, 2003 .

Flying Insect Classification with Inexpensive Sensors

Eamonn J. Keogh, Eamonn Keogh, Gustavo E. A. P. A. Batista, 2014, Journal of Insect Behavior.

Preface to the International Workshop on Spatial and Spatio-Temporal Data Mining

Dimitrios Gunopulos, Eamonn J. Keogh, Alfredo Cuzzocrea, 2011, IEEE ICDM 2011.

Matrix Profile XVII: Indexing the Matrix Profile to Allow Arbitrary Range Queries

Eamonn J. Keogh, Eamonn Keogh, Yan Zhu, 2020, 2020 IEEE 36th International Conference on Data Engineering (ICDE).

Online Amnestic DTW to allow Real-Time Golden Batch Monitoring

Eamonn J. Keogh, Eamonn Keogh, Hoang Anh Dau, 2019, KDD.

Introducing time series snippets: a new primitive for summarizing long time series

Eamonn Keogh, Wei Ding, Scott E. Crouter, 2020, Data Mining and Knowledge Discovery.

Matrix profile goes MAD: variable-length motif and discord discovery in data series

Eamonn J. Keogh, Yan Zhu, Themis Palpanas, 2020, Data Mining and Knowledge Discovery.

Fast time series classification using numerosity reduction

Li Wei, Eamonn J. Keogh, Chotirat Ann Ratanamahatana, 2006, ICML.

Why the lack of reproducibility is crippling research in data mining and what you can do about it

Eamonn Keogh, 2007, MDM '07.

Algorithms for mining large collections of time series and multimedia

Eamonn Keogh, Xiaopeng Xi, 2007 .

Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy

Eamonn J. Keogh, Eamonn Keogh, Nurjahan Begum, 2015, KDD.

Experiencing SAX: a novel symbolic representation of time series

Li Wei, Jessica Lin, Eamonn J. Keogh, 2007, Data Mining and Knowledge Discovery.

Clustering in the Face of Fast Changing Streams

Eamonn J. Keogh, Eamonn Keogh, Nurjahan Begum, 2016, SDM.

Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW pdf

Eamonn J. Keogh, Eamonn Keogh, Kaveh Kamgar, 2020, 2020 IEEE International Conference on Data Mining (ICDM).

Eamonn Keogh, Michael J. Pazzani, 2001 .

Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness

Eamonn J. Keogh, Eamonn Keogh, Takaaki Nakamura, 2020, KDD.

Multiresolution Clustering of Time Series and Application to Images

Dimitrios Gunopulos, Eamonn Keogh, Michail Vlachos, 2007 .

Test Data

Risto Miikkulainen, Marko Grobelnik, Pierre Flener, 2019, Encyclopedia of Machine Learning and Data Mining.

Mining shape and time series databases with symbolic representations

Eamonn Keogh, 2007, KDD '07.

Discovering and Labeling Power System Events in Synchrophasor Data with Matrix Profile

Koji Yamashita, Eamonn Keogh, Jie Shi, 2019, 2019 IEEE Sustainable Power and Energy Conference (iSPEC).

Time series classification for varying length series pdf

Geoffrey I. Webb, Eamonn J. Keogh, Eamonn Keogh, 2019, ArXiv.

2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings: Welcome Message

Eamonn Keogh, Kate Smith-Miles, Vincent C. S. Lee, 2009, CIDM 2009.

Inverse Resolution

Pierre Flener, Eamonn J. Keogh, Ricardo Vilalta, 2010, Encyclopedia of Machine Learning and Data Mining.

On the effect of endpoints on dynamic time warping

Eamonn Keogh, Gustavo E. A. P. A. Batista, Diego Furtado Silva, 2016 .

Super‐Efficient Cross‐Correlation (SEC‐C): A Fast Matched Filtering Code Suitable for Desktop Computers

Eamonn J. Keogh, Yan Zhu, Eamonn Keogh, 2018, Seismological Research Letters.

A Fast and Robust Method for Pattern Matching in Time Series Databases

Eamonn Keogh, 2012 .

Fast Motion Capture Matching with Replicated Motion Editing

Dimitrios Gunopulos, Eamonn Keogh, Michail Vlachos, 2003 .

Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series pdf

Eamonn J. Keogh, Eamonn Keogh, Zhongfang Zhuang, 2021, SDM.

Finding the Unusual Medical Time Series: Algorithms and Applications

Jessica Lin, Eamonn Keogh, Helga Van Herle, 2005 .

Monitoring and Mining Animal Sounds in Visual Space

Eamonn Keogh, Bilson Campana, Yuan Hao, 2012, Journal of Insect Behavior.

FINDING OR NOT FINDING RULES IN TIME SERIES

Eamonn J. Keogh, Jessica Lin, Eamonn Keogh, 2004 .