Eamonn J. Keogh

ORCID

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 122

Top Venues

Data Min. Knowl. Discov.

CoRR

ICDM

KDD

Publications

Ryan Mercer, Eamonn J. Keogh
Novelets: a new primitive that allows online detection of emerging behaviors in time series. Knowl. Inf. Syst. 66 (1) (2024)
Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies. CoRR (2024)
Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang, Jeff M. Phillips, Eamonn J. Keogh
Sketching Multidimensional Time Series for Fast Discord Mining. CoRR (2023)
Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
Time Series Synthesis Using the Matrix Profile for Anonymization. CoRR (2023)
Eamonn J. Keogh
Getting an h-Index of 100 in 20 Years or Less! KDD (2023)
Renjie Wu, Eamonn J. Keogh
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress. IEEE Trans. Knowl. Data Eng. 35 (3) (2023)
Prithviraj Yuvaraj, Amin Akalantar, Eamonn J. Keogh, Philip Brisk
Feature Extraction Accelerator for Streaming Time Series. FCCM (2023)
Chin-Chia Michael Yeh, Huiyuan Chen, Yujie Fan, Xin Dai, Yan Zheng, Vivian Lai, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
Ego-Network Transformer for Subsequence Classification in Time Series Data. BigData (2023)
Chin-Chia Michael Yeh, Huiyuan Chen, Yujie Fan, Xin Dai, Yan Zheng, Vivian Lai, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
Ego-Network Transformer for Subsequence Classification in Time Series Data. CoRR (2023)
Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang, Jeff M. Phillips, Eamonn J. Keogh
Sketching Multidimensional Time Series for Fast Discord Mining. BigData (2023)
Yue Lu, Thirumalai Vinjamoor Akhil Srinivas, Takaaki Nakamura, Makoto Imamura, Eamonn J. Keogh
Matrix Profile XXX: MADRID: A Hyper-Anytime and Parameter-Free Algorithm to Find Time Series Anomalies of all Lengths. ICDM (2023)
Eamonn J. Keogh
Time Series Data Mining: A Unifying View. Proc. VLDB Endow. 16 (12) (2023)
Sadaf Tafazoli, Yue Lu, Renjie Wu, Thirumalai Vinjamoor Akhil Srinivas, Hannah Dela Cruz, Ryan Mercer, Eamonn J. Keogh
MP, Fusing catch 22 and the Matrix Profile to Produce an Efficient and Interpretable Anomaly Detector. ICDM (2023)
Renjie Wu, Audrey Der, Eamonn J. Keogh
When is Early Classification of Time Series Meaningful? IEEE Trans. Knowl. Data Eng. 35 (3) (2023)
Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
Time Series Synthesis Using the Matrix Profile for Anonymization. BigData (2023)
Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn J. Keogh
DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams. Data Min. Knowl. Discov. 37 (2) (2023)
Sadaf Tafazoli, Eamonn J. Keogh
. SDM (2023)
Takaaki Nakamura, Ryan Mercer, Makoto Imamura, Eamonn J. Keogh
MERLIN++: parameter-free discovery of time series anomalies. Data Min. Knowl. Discov. 37 (2) (2023)
Renjie Wu, Audrey Der, Eamonn J. Keogh
When is Early Classification of Time Series Meaningful? (Extended Abstract). ICDE (2022)
Audrey Der, Chin-Chia Michael Yeh, Renjie Wu, Junpeng Wang, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series. CoRR (2022)
Ryan Mercer, Eamonn J. Keogh
Matrix Profile XXV: Introducing Novelets: A Primitive that Allows Online Detection of Emerging Behaviors in Time Series. ICDM (2022)
Renjie Wu, Eamonn J. Keogh
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress (Extended Abstract). ICDE (2022)
Ryan Mercer, Sara Alaee, Alireza Abdoli, Nader Shakibay Senobari, Shailendra Singh, Amy C. Murillo, Eamonn J. Keogh
Introducing the contrast profile: a novel time series primitive that allows real world classification. Data Min. Knowl. Discov. 36 (2) (2022)
Maryam Shahcheraghi, Ryan Mercer, João Manuel De Almeida Rodrigues, Audrey Der, Hugo Filipe Silveira Gamboa, Zachary Zimmerman, Eamonn J. Keogh
Matrix Profile XXVI: Mplots: Scaling Time Series Similarity Matrices to Massive Data. ICDM (2022)
Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn J. Keogh
Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams. KDD (2022)
Audrey Der, Chin-Chia Michael Yeh, Renjie Wu, Junpeng Wang, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series. ICKG (2022)
Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Wei Zhang, Eamonn J. Keogh
Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series. SDM (2022)
Renjie Wu, Eamonn J. Keogh
FastDTW is Approximate and Generally Slower Than the Algorithm it Approximates. IEEE Trans. Knowl. Data Eng. 34 (8) (2022)
Maryam Shahcheraghi, Trevor Cappon, Samet Oymak, Evangelos E. Papalexakis, Eamonn J. Keogh, Zachary Zimmerman, Philip Brisk
Matrix Profile Index Approximation for Streaming Time Series. IEEE BigData (2021)
Renjie Wu, Eamonn J. Keogh
FastDTW is approximate and Generally Slower than the Algorithm it Approximates (Extended Abstract). ICDE (2021)
Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Wei Zhang, Eamonn J. Keogh
Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series. CoRR (2021)
Sara Alaee, Ryan Mercer, Kaveh Kamgar, Eamonn J. Keogh
Time series motifs discovery under DTW allows more robust discovery of conserved structure. Data Min. Knowl. Discov. 35 (3) (2021)
Renjie Wu, Audrey Der, Eamonn J. Keogh
When is Early Classification of Time Series Meaningful? CoRR (2021)
Yan Zhu, Abdullah Mueen, Eamonn J. Keogh
Matrix Profile IX: Admissible Time Series Motif Discovery With Missing Data. IEEE Trans. Knowl. Data Eng. 33 (6) (2021)
Ryan Mercer, Sara Alaee, Alireza Abdoli, Shailendra Singh, Amy C. Murillo, Eamonn J. Keogh
Matrix Profile XXIII: Contrast Profile: A Novel Time Series Primitive that Allows Real World Classification. ICDM (2021)
Ryan Mercer, Seyhan Ucar, Eamonn J. Keogh
Shape-Based Telemetry Approach for Distracted Driving Behavior Detection. CSCN (2021)
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
Matrix Profile Goes MAD: Variable-Length Motif And Discord Discovery in Data Series. CoRR (2020)
Shima Imani, Eamonn J. Keogh
Natura: Towards Conversational Analytics for Comparing and Contrasting Time Series. WWW (Companion Volume) (2020)
Makoto Imamura, Takaaki Nakamura, Eamonn J. Keogh
Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness. KDD (2020)
Takaaki Nakamura, Makoto Imamura, Ryan Mercer, Eamonn J. Keogh
MERLIN: Parameter-Free Discovery of Arbitrary Length Anomalies in Massive Time Series Archives. ICDM (2020)
Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
An ultra-fast time series distance measure to allow data mining in more complex real-world deployments. Data Min. Knowl. Discov. 34 (4) (2020)
Sara Alaee, Kaveh Kamgar, Eamonn J. Keogh
Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW. CoRR (2020)
Alireza Abdoli, Sara Alaee, Shima Imani, Amy C. Murillo, Alec C. Gerry, Leslie Hickle, Eamonn J. Keogh
Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms. KDD (2020)
Yan Zhu, Chin-Chia Michael Yeh, Zachary Zimmerman, Eamonn J. Keogh
Matrix Profile XVII: Indexing the Matrix Profile to Allow Arbitrary Range Queries. ICDE (2020)
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. CoRR (2020)
Renjie Wu, Eamonn J. Keogh
FastDTW is approximate and Generally Slower than the Algorithm it Approximates. CoRR (2020)
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
Matrix profile goes MAD: variable-length motif and discord discovery in data series. Data Min. Knowl. Discov. 34 (4) (2020)
Renjie Wu, Eamonn J. Keogh
Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress. CoRR (2020)
Sara Alaee, Alireza Abdoli, Christian R. Shelton, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
Features or Shape? Tackling the False Dichotomy of Time Series Classification. SDM (2020)
Sara Alaee, Kaveh Kamgar, Eamonn J. Keogh
Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW. ICDM (2020)
Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn J. Keogh
Introducing time series snippets: a new primitive for summarizing long time series. Data Min. Knowl. Discov. 34 (6) (2020)
Yan Zhu, Shaghayegh Gharghabi, Diego Furtado Silva, Hoang Anh Dau, Chin-Chia Michael Yeh, Nader Shakibay Senobari, Abdulaziz Almaslukh, Kaveh Kamgar, Zachary Zimmerman, Gareth J. Funning, Abdullah Mueen, Eamonn J. Keogh
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code. Data Min. Knowl. Discov. 34 (4) (2020)
Kaveh Kamgar, Eamonn J. Keogh, Zachary Zimmerman, Nader Shakibay Senobari, Gareth J. Funning, Brian Crites, Philip Brisk
Matrix Profile XIV: Scaling Time Series Motif Discovery with GPUs to Break a Quintillion Pairwise Comparisons a Day and Beyond. SoCC (2019)
Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
The UCR time series archive. IEEE CAA J. Autom. Sinica 6 (6) (2019)
Kaveh Kamgar, Shaghayegh Gharghabi, Eamonn J. Keogh
Matrix Profile XV: Exploiting Time Series Consensus Motifs to Find Structure in Time Series Sets. ICDM (2019)
Shima Imani, Sara Alaee, Eamonn J. Keogh
Putting the Human in the Time Series Analytics Loop. WWW (Companion Volume) (2019)
Frank Madrid, Shailendra Singh, Quentin Chesnais, Kerry Mauck, Eamonn J. Keogh
Matrix Profile XVI: Efficient and Effective Labeling of Massive Time Series Archives. DSAA (2019)
Zachary Zimmerman, Nader Shakibay Senobari, Gareth J. Funning, Evangelos E. Papalexakis, Samet Oymak, Philip Brisk, Eamonn J. Keogh
Matrix Profile XVIII: Time Series Mining in the Face of Fast Moving Streams using a Learned Approximate Matrix Profile. ICDM (2019)
Alireza Abdoli, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
Time Series Classification: Lessons Learned in the (Literal) Field while Studying Chicken Behavior. IEEE BigData (2019)
Chin-Chia Michael Yeh, Yan Zhu, Hoang Anh Dau, Amirali Darvishzadeh, Mikhail Noskov, Eamonn J. Keogh
Online Amnestic DTW to allow Real-Time Golden Batch Monitoring. KDD (2019)
Frank Madrid, Shima Imani, Ryan Mercer, Zachary Zimmerman, Nader Shakibay Senobari, Eamonn J. Keogh
Matrix Profile XX: Finding and Visualizing Time Series Motifs of All Lengths using the Matrix Profile. ICBK (2019)
Zachary Zimmerman, Kaveh Kamgar, Nader Shakibay Senobari, Brian Crites, Gareth J. Funning, Philip Brisk, Eamonn J. Keogh
Matrix Profile XIV: Scaling Time Series Motif Discovery with GPUs to Break a Quintillion Pairwise Comparisons a Day and Beyond. SoCC (2019)
Shaghayegh Gharghabi, Chin-Chia Michael Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn J. Keogh
Correction to: Domain agnostic online semantic segmentation for multi-dimensional time series. Data Min. Knowl. Discov. 33 (6) (2019)
Shaghayegh Gharghabi, Chin-Chia Michael Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn J. Keogh
Domain agnostic online semantic segmentation for multi-dimensional time series. Data Min. Knowl. Discov. 33 (1) (2019)
Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh
Introducing time series chains: a new primitive for time series data mining. Knowl. Inf. Syst. 60 (2) (2019)
Chang Wei Tan, François Petitjean, Eamonn J. Keogh, Geoffrey I. Webb
Time series classification for varying length series. CoRR (2019)
Diego Furtado Silva, Chin-Chia Michael Yeh, Yan Zhu, Gustavo E. A. P. A. Batista, Eamonn J. Keogh
Fast Similarity Matrix Profile for Music Analysis and Exploration. IEEE Trans. Multim. 21 (1) (2019)
Sara Alaee, Alireza Abdoli, Christian R. Shelton, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
Features or Shape? Tackling the False Dichotomy of Time Series Classification. CoRR (2019)
Alireza Abdoli, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
Time Series Classification: Lessons Learned in the (Literal) Field while Studying Chicken Behavior. CoRR (2019)
Shima Imani, Eamonn J. Keogh
Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series. ICDM (2019)
Yilin Shen, Yanping Chen, Eamonn J. Keogh, Hongxia Jin
Accelerating Time Series Searching with Large Uniform Scaling. SDM (2018)
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. SIGMOD Conference (2018)
Yan Zhu, Zachary Zimmerman, Nader Shakibay Senobari, Chin-Chia Michael Yeh, Gareth J. Funning, Abdullah Mueen, Philip Brisk, Eamonn J. Keogh
Exploiting a novel algorithm and GPUs to break the ten quadrillion pairwise comparisons barrier for time series motifs and joins. Knowl. Inf. Syst. 54 (1) (2018)
Diego Furtado Silva, Rafael Giusti, Eamonn J. Keogh, Gustavo E. A. P. A. Batista
Speeding up similarity search under dynamic time warping by pruning unpromising alignments. Data Min. Knowl. Discov. 32 (4) (2018)
Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn J. Keogh
Matrix Profile XIII: Time Series Snippets: A New Primitive for Time Series Data Mining. ICBK (2018)
Alireza Abdoli, Amy C. Murillo, Chin-Chia Michael Yeh, Alec C. Gerry, Eamonn J. Keogh
Time Series Classification to Improve Poultry Welfare. CoRR (2018)
Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh
Time Series Chains: A Novel Tool for Time Series Data Mining. IJCAI (2018)
Yan Zhu, Abdullah Mueen, Eamonn J. Keogh
Admissible Time Series Motif Discovery with Missing Data. CoRR (2018)
Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series. SIGMOD Conference (2018)
Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Abdullah Mueen, Eamonn J. Keogh
Optimizing dynamic time warping's window width for time series data mining applications. Data Min. Knowl. Discov. 32 (4) (2018)
Yan Zhu, Chin-Chia Michael Yeh, Zachary Zimmerman, Kaveh Kamgar, Eamonn J. Keogh
Matrix Profile XI: SCRIMP++: Time Series Motif Discovery at Interactive Speeds. ICDM (2018)
Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios. ICDM (2018)
Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
The UCR Time Series Archive. CoRR (2018)
Anthony J. Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, Eamonn J. Keogh
The UEA multivariate time series classification archive, 2018. CoRR (2018)
Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Zachary Zimmerman, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh
Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile. Data Min. Knowl. Discov. 32 (1) (2018)
Chin-Chia Michael Yeh, Yan Zhu, Evangelos E. Papalexakis, Abdullah Mueen, Eamonn J. Keogh
Representation Learning by Reconstructing Neighborhoods. CoRR (2018)
Alireza Abdoli, Amy C. Murillo, Chin-Chia Michael Yeh, Alec C. Gerry, Eamonn J. Keogh
Time Series Classification to Improve Poultry Welfare. ICMLA (2018)
Rodica Neamtu, Ramoza Ahsan, Elke A. Rundensteiner, Gábor N. Sárközy, Eamonn J. Keogh, Hoang Anh Dau, Cuong Nguyen, Charles Lovering
Generalized Dynamic Time Warping: Unleashing the Warping Power Hidden in Point-Wise Distances. ICDE (2018)
Yifei Ding, Eamonn J. Keogh
Query Suggestion to allow Intuitive Interactive Search in Multidimensional Time Series. SSDBM (2017)
Hoang Anh Dau, Eamonn J. Keogh
Matrix Profile V: A Generic Technique to Incorporate Domain Knowledge into Motif Discovery. KDD (2017)
Anthony J. Bagnall, Jason Lines, Aaron Bostrom, James Large, Eamonn J. Keogh
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Discov. 31 (3) (2017)
Chin-Chia Michael Yeh, Nickolas Kavantzas, Eamonn J. Keogh
Matrix Profile VI: Meaningful Multidimensional Motif Discovery. ICDM (2017)
Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh
Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award). ICDM (2017)
Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Eamonn J. Keogh
Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series. IEEE BigData (2017)
Shaghayegh Gharghabi, Yifei Ding, Chin-Chia Michael Yeh, Kaveh Kamgar, Liudmila Ulanova, Eamonn J. Keogh
Matrix Profile VIII: Domain Agnostic Online Semantic Segmentation at Superhuman Performance Levels. ICDM (2017)
Chin-Chia Michael Yeh, Nickolas Kavantzas, Eamonn J. Keogh
Matrix Profile IV: Using Weakly Labeled Time Series to Predict Outcomes. Proc. VLDB Endow. 10 (12) (2017)
Yilin Shen, Yanping Chen, Eamonn J. Keogh, Hongxia Jin
Searching Time Series with Invariance to Large Amounts of Uniform Scaling. ICDE (2017)
Germain Forestier, François Petitjean, Hoang Anh Dau, Geoffrey I. Webb, Eamonn J. Keogh
Generating Synthetic Time Series to Augment Sparse Datasets. ICDM (2017)
Usue Mori, Alexander Mendiburu, Eamonn J. Keogh, José Antonio Lozano
Reliable early classification of time series based on discriminating the classes over time. Data Min. Knowl. Discov. 31 (1) (2017)
Mohammad Shokoohi-Yekta, Bing Hu, Hongxia Jin, Jun Wang, Eamonn J. Keogh
Generalizing DTW to the multi-dimensional case requires an adaptive approach. Data Min. Knowl. Discov. 31 (1) (2017)

Eamonn J. Keogh.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Eamonn J. Keogh