Eamonn J. Keogh

322 papers A* 97A 33B 19C 6Misc 5Journal 103Unranked 43

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Finding Repeated Structures in Time Series: Algorithms and Applications: A Unifying View of Time Series Motifs/Shapelets/Chains and Similar Primitives. KDD (2) Eamonn J. Keogh
2024	A	`conf`	A Systematic Evaluation of Generated Time Series and Their Effects in Self-Supervised Pretraining. CIKM Audrey Der, Chin-Chia Michael Yeh, Xin Dai, Huiyuan Chen, Yan Zheng, Yujie Fan, Zhongfang Zhuang, Vivian Lai, Junpeng Wang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	J	`jnl`	A Systematic Evaluation of Generated Time Series and Their Effects in Self-Supervised Pretraining. CoRR Audrey Der, Chin-Chia Michael Yeh, Xin Dai, Huiyuan Chen, Yan Zheng, Yujie Fan, Zhongfang Zhuang, Vivian Lai, Junpeng Wang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	J	`jnl`	C Knowl. Inf. Syst. Sadaf Tafazoli, Yue Lu, Renjie Wu, Thirumalai Vinjamoor Akhil Srinivas, Hannah Dela Cruz, Ryan Mercer, Eamonn J. Keogh
2024	J	`jnl`	Introducing Mplots: scaling time series recurrence plots to massive datasets. J. Big Data Maryam Shahcheraghi, Ryan Mercer, João Manuel De Almeida Rodrigues, Audrey Der, Hugo Filipe Silveira Gamboa, Zachary Zimmerman, Kerry Mauck, Eamonn J. Keogh
2024	—	`conf`	Matrix Profile XXXI: Motif Discovery Made Faster. ICKG Maryam Shahcheraghi, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Mahashweta Das, Eamonn J. Keogh
2024	A*	`conf`	Matrix Profile for Anomaly Detection on Multidimensional Time Series. ICDM Chin-Chia Michael Yeh, Audrey Der, Uday Singh Saini, Vivian Lai, Yan Zheng, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Yujie Fan, Huiyuan Chen, Prince Osei Aboagye, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	J	`jnl`	Matrix Profile for Anomaly Detection on Multidimensional Time Series. CoRR Chin-Chia Michael Yeh, Audrey Der, Uday Singh Saini, Vivian Lai, Yan Zheng, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Yujie Fan, Huiyuan Chen, Prince Osei Aboagye, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	J	`jnl`	Novelets: a new primitive that allows online detection of emerging behaviors in time series. Knowl. Inf. Syst. Ryan Mercer, Eamonn J. Keogh
2024	A	`conf`	PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies. SDM Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	J	`jnl`	PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies. CoRR Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	B	`conf`	Time Series Data Mining: A Unifying View. DSAA Eamonn J. Keogh
2023	J	`jnl`	Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress. IEEE Trans. Knowl. Data Eng. Renjie Wu, Eamonn J. Keogh
2023	J	`jnl`	DAMP: accurate time series anomaly detection on trillions of datapoints and ultra-fast arriving data streams. Data Min. Knowl. Discov. Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn J. Keogh
2023	B	`conf`	Ego-Network Transformer for Subsequence Classification in Time Series Data. IEEE Big Data 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
2023	J	`jnl`	Ego-Network Transformer for Subsequence Classification in Time Series Data. CoRR 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
2023	Misc	`conf`	Feature Extraction Accelerator for Streaming Time Series. FCCM Prithviraj Yuvaraj, Amin Akalantar, Eamonn J. Keogh, Philip Brisk
2023	A*	`conf`	Getting an h-Index of 100 in 20 Years or Less! KDD Eamonn J. Keogh
2023	J	`jnl`	MERLIN++: parameter-free discovery of time series anomalies. Data Min. Knowl. Discov. Takaaki Nakamura, Ryan Mercer, Makoto Imamura, Eamonn J. Keogh
2023	A*	`conf`	Matrix Profile XXIX: C ICDM Sadaf Tafazoli, Yue Lu, Renjie Wu, Thirumalai Vinjamoor Akhil Srinivas, Hannah Dela Cruz, Ryan Mercer, Eamonn J. Keogh
2023	A	`conf`	Matrix Profile XXVIII: Discovering Multi-Dimensional Time Series Anomalies with SDM Sadaf Tafazoli, Eamonn J. Keogh
2023	A*	`conf`	Matrix Profile XXX: MADRID: A Hyper-Anytime and Parameter-Free Algorithm to Find Time Series Anomalies of all Lengths. ICDM Yue Lu, Thirumalai Vinjamoor Akhil Srinivas, Takaaki Nakamura, Makoto Imamura, Eamonn J. Keogh
2023	B	`conf`	Sketching Multidimensional Time Series for Fast Discord Mining. IEEE Big Data Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang, Jeff M. Phillips, Eamonn J. Keogh
2023	J	`jnl`	Sketching Multidimensional Time Series for Fast Discord Mining. CoRR Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang, Jeff M. Phillips, Eamonn J. Keogh
2023	—	`conf`	Tailgating Behavior Detection On Rear Vehicles. ITSC Seyhan Ucar, Ryan Mercer, Eamonn J. Keogh
2023	J	`jnl`	Time Series Data Mining: A Unifying View. Proc. VLDB Endow. Eamonn J. Keogh
2023	B	`conf`	Time Series Synthesis Using the Matrix Profile for Anonymization. IEEE Big Data Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2023	J	`jnl`	Time Series Synthesis Using the Matrix Profile for Anonymization. CoRR Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2023	J	`jnl`	When is Early Classification of Time Series Meaningful? IEEE Trans. Knowl. Data Eng. Renjie Wu, Audrey Der, Eamonn J. Keogh
2022	A*	`conf`	Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress (Extended Abstract). ICDE Renjie Wu, Eamonn J. Keogh
2022	A	`conf`	Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series. SDM Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Wei Zhang, Eamonn J. Keogh
2022	J	`jnl`	FastDTW is Approximate and Generally Slower Than the Algorithm it Approximates. IEEE Trans. Knowl. Data Eng. Renjie Wu, Eamonn J. Keogh
2022	J	`jnl`	Introducing the contrast profile: a novel time series primitive that allows real world classification. Data Min. Knowl. Discov. Ryan Mercer, Sara Alaee, Alireza Abdoli, Nader Shakibay Senobari, Shailendra Singh, Amy C. Murillo, Eamonn J. Keogh
2022	A*	`conf`	Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams. KDD Yue Lu, Renjie Wu, Abdullah Mueen, Maria A. Zuluaga, Eamonn J. Keogh
2022	A*	`conf`	Matrix Profile XXV: Introducing Novelets: A Primitive that Allows Online Detection of Emerging Behaviors in Time Series. ICDM Ryan Mercer, Eamonn J. Keogh
2022	A*	`conf`	Matrix Profile XXVI: Mplots: Scaling Time Series Similarity Matrices to Massive Data. ICDM Maryam Shahcheraghi, Ryan Mercer, João Manuel De Almeida Rodrigues, Audrey Der, Hugo Filipe Silveira Gamboa, Zachary Zimmerman, Eamonn J. Keogh
2022	—	`conf`	Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series. ICKG Audrey Der, Chin-Chia Michael Yeh, Renjie Wu, Junpeng Wang, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2022	J	`jnl`	Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series. CoRR Audrey Der, Chin-Chia Michael Yeh, Renjie Wu, Junpeng Wang, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh
2022	A*	`conf`	When is Early Classification of Time Series Meaningful? (Extended Abstract). ICDE Renjie Wu, Audrey Der, Eamonn J. Keogh
2021	J	`jnl`	Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series. CoRR Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Wei Zhang, Eamonn J. Keogh
2021	A*	`conf`	FastDTW is approximate and Generally Slower than the Algorithm it Approximates (Extended Abstract). ICDE Renjie Wu, Eamonn J. Keogh
2021	J	`jnl`	Matrix Profile IX: Admissible Time Series Motif Discovery With Missing Data. IEEE Trans. Knowl. Data Eng. Yan Zhu, Abdullah Mueen, Eamonn J. Keogh
2021	—	`conf`	Matrix Profile Index Approximation for Streaming Time Series. IEEE BigData Maryam Shahcheraghi, Trevor Cappon, Samet Oymak, Evangelos E. Papalexakis, Eamonn J. Keogh, Zachary Zimmerman, Philip Brisk
2021	A*	`conf`	Matrix Profile XXIII: Contrast Profile: A Novel Time Series Primitive that Allows Real World Classification. ICDM Ryan Mercer, Sara Alaee, Alireza Abdoli, Shailendra Singh, Amy C. Murillo, Eamonn J. Keogh
2021	—	`conf`	Shape-Based Telemetry Approach for Distracted Driving Behavior Detection. CSCN Ryan Mercer, Seyhan Ucar, Eamonn J. Keogh
2021	J	`jnl`	Time series motifs discovery under DTW allows more robust discovery of conserved structure. Data Min. Knowl. Discov. Sara Alaee, Ryan Mercer, Kaveh Kamgar, Eamonn J. Keogh
2021	J	`jnl`	When is Early Classification of Time Series Meaningful? CoRR Renjie Wu, Audrey Der, Eamonn J. Keogh
2020	J	`jnl`	An ultra-fast time series distance measure to allow data mining in more complex real-world deployments. Data Min. Knowl. Discov. Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
2020	J	`jnl`	Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress. CoRR Renjie Wu, Eamonn J. Keogh
2020	J	`jnl`	FastDTW is approximate and Generally Slower than the Algorithm it Approximates. CoRR Renjie Wu, Eamonn J. Keogh
2020	A	`conf`	Features or Shape? Tackling the False Dichotomy of Time Series Classification. SDM Sara Alaee, Alireza Abdoli, Christian R. Shelton, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
2020	A*	`conf`	Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms. KDD Alireza Abdoli, Sara Alaee, Shima Imani, Amy C. Murillo, Alec C. Gerry, Leslie Hickle, Eamonn J. Keogh
2020	J	`jnl`	Introducing time series snippets: a new primitive for summarizing long time series. Data Min. Knowl. Discov. Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn J. Keogh
2020	A*	`conf`	MERLIN: Parameter-Free Discovery of Arbitrary Length Anomalies in Massive Time Series Archives. ICDM Takaaki Nakamura, Makoto Imamura, Ryan Mercer, Eamonn J. Keogh
2020	J	`jnl`	Matrix Profile Goes MAD: Variable-Length Motif And Discord Discovery in Data Series. CoRR Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2020	A*	`conf`	Matrix Profile XVII: Indexing the Matrix Profile to Allow Arbitrary Range Queries. ICDE Yan Zhu, Chin-Chia Michael Yeh, Zachary Zimmerman, Eamonn J. Keogh
2020	A*	`conf`	Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness. KDD Makoto Imamura, Takaaki Nakamura, Eamonn J. Keogh
2020	A*	`conf`	Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW. ICDM Sara Alaee, Kaveh Kamgar, Eamonn J. Keogh
2020	J	`jnl`	Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW. CoRR Sara Alaee, Kaveh Kamgar, Eamonn J. Keogh
2020	J	`jnl`	Matrix profile goes MAD: variable-length motif and discord discovery in data series. Data Min. Knowl. Discov. Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2020	—	`conf`	Natura: Towards Conversational Analytics for Comparing and Contrasting Time Series. WWW (Companion Volume) Shima Imani, Eamonn J. Keogh
2020	J	`jnl`	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. 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
2020	J	`jnl`	VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. CoRR Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2019	J	`jnl`	Correction to: Domain agnostic online semantic segmentation for multi-dimensional time series. Data Min. Knowl. Discov. Shaghayegh Gharghabi, Chin-Chia Michael Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn J. Keogh
2019	J	`jnl`	Domain agnostic online semantic segmentation for multi-dimensional time series. Data Min. Knowl. Discov. Shaghayegh Gharghabi, Chin-Chia Michael Yeh, Yifei Ding, Wei Ding, Paul Hibbing, Samuel LaMunion, Andrew Kaplan, Scott E. Crouter, Eamonn J. Keogh
2019	J	`jnl`	Fast Similarity Matrix Profile for Music Analysis and Exploration. IEEE Trans. Multim. Diego Furtado Silva, Chin-Chia Michael Yeh, Yan Zhu, Gustavo E. A. P. A. Batista, Eamonn J. Keogh
2019	J	`jnl`	Features or Shape? Tackling the False Dichotomy of Time Series Classification. CoRR Sara Alaee, Alireza Abdoli, Christian R. Shelton, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
2019	J	`jnl`	Introducing time series chains: a new primitive for time series data mining. Knowl. Inf. Syst. Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh
2019	—	`conf`	Matrix Profile XIV: Scaling Time Series Motif Discovery with GPUs to Break a Quintillion Pairwise Comparisons a Day and Beyond. SoCC Zachary Zimmerman, Kaveh Kamgar, Nader Shakibay Senobari, Brian Crites, Gareth J. Funning, Philip Brisk, Eamonn J. Keogh
2019	A*	`conf`	Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series. ICDM Shima Imani, Eamonn J. Keogh
2019	A*	`conf`	Matrix Profile XV: Exploiting Time Series Consensus Motifs to Find Structure in Time Series Sets. ICDM Kaveh Kamgar, Shaghayegh Gharghabi, Eamonn J. Keogh
2019	B	`conf`	Matrix Profile XVI: Efficient and Effective Labeling of Massive Time Series Archives. DSAA Frank Madrid, Shailendra Singh, Quentin Chesnais, Kerry Mauck, Eamonn J. Keogh
2019	A*	`conf`	Matrix Profile XVIII: Time Series Mining in the Face of Fast Moving Streams using a Learned Approximate Matrix Profile. ICDM Zachary Zimmerman, Nader Shakibay Senobari, Gareth J. Funning, Evangelos E. Papalexakis, Samet Oymak, Philip Brisk, Eamonn J. Keogh
2019	—	`conf`	Matrix Profile XX: Finding and Visualizing Time Series Motifs of All Lengths using the Matrix Profile. ICBK Frank Madrid, Shima Imani, Ryan Mercer, Zachary Zimmerman, Nader Shakibay Senobari, Eamonn J. Keogh
2019	A*	`conf`	Online Amnestic DTW to allow Real-Time Golden Batch Monitoring. KDD Chin-Chia Michael Yeh, Yan Zhu, Hoang Anh Dau, Amirali Darvishzadeh, Mikhail Noskov, Eamonn J. Keogh
2019	—	`conf`	Putting the Human in the Time Series Analytics Loop. WWW (Companion Volume) Shima Imani, Sara Alaee, Eamonn J. Keogh
2019	J	`jnl`	The UCR time series archive. IEEE CAA J. Autom. Sinica Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
2019	—	`conf`	Time Series Classification: Lessons Learned in the (Literal) Field while Studying Chicken Behavior. IEEE BigData Alireza Abdoli, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
2019	J	`jnl`	Time Series Classification: Lessons Learned in the (Literal) Field while Studying Chicken Behavior. CoRR Alireza Abdoli, Amy C. Murillo, Alec C. Gerry, Eamonn J. Keogh
2019	J	`jnl`	Time series classification for varying length series. CoRR Chang Wei Tan, François Petitjean, Eamonn J. Keogh, Geoffrey I. Webb
2018	A	`conf`	Accelerating Time Series Searching with Large Uniform Scaling. SDM Yilin Shen, Yanping Chen, Eamonn J. Keogh, Hongxia Jin
2018	J	`jnl`	Admissible Time Series Motif Discovery with Missing Data. CoRR Yan Zhu, Abdullah Mueen, Eamonn J. Keogh
2018	J	`jnl`	Exploiting a novel algorithm and GPUs to break the ten quadrillion pairwise comparisons barrier for time series motifs and joins. Knowl. Inf. Syst. Yan Zhu, Zachary Zimmerman, Nader Shakibay Senobari, Chin-Chia Michael Yeh, Gareth J. Funning, Abdullah Mueen, Philip Brisk, Eamonn J. Keogh
2018	A*	`conf`	Generalized Dynamic Time Warping: Unleashing the Warping Power Hidden in Point-Wise Distances. ICDE Rodica Neamtu, Ramoza Ahsan, Elke A. Rundensteiner, Gábor N. Sárközy, Eamonn J. Keogh, Hoang Anh Dau, Cuong Nguyen, Charles Lovering
2018	—	`conf`	Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series. SIGMOD Conference Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2018	A*	`conf`	Matrix Profile XI: SCRIMP++: Time Series Motif Discovery at Interactive Speeds. ICDM Yan Zhu, Chin-Chia Michael Yeh, Zachary Zimmerman, Kaveh Kamgar, Eamonn J. Keogh
2018	A*	`conf`	Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios. ICDM Shaghayegh Gharghabi, Shima Imani, Anthony J. Bagnall, Amirali Darvishzadeh, Eamonn J. Keogh
2018	—	`conf`	Matrix Profile XIII: Time Series Snippets: A New Primitive for Time Series Data Mining. ICBK Shima Imani, Frank Madrid, Wei Ding, Scott E. Crouter, Eamonn J. Keogh
2018	J	`jnl`	Optimizing dynamic time warping's window width for time series data mining applications. Data Min. Knowl. Discov. Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Abdullah Mueen, Eamonn J. Keogh
2018	J	`jnl`	Representation Learning by Reconstructing Neighborhoods. CoRR Chin-Chia Michael Yeh, Yan Zhu, Evangelos E. Papalexakis, Abdullah Mueen, Eamonn J. Keogh
2018	J	`jnl`	Speeding up similarity search under dynamic time warping by pruning unpromising alignments. Data Min. Knowl. Discov. Diego Furtado Silva, Rafael Giusti, Eamonn J. Keogh, Gustavo E. A. P. A. Batista
2018	J	`jnl`	The UCR Time Series Archive. CoRR Hoang Anh Dau, Anthony J. Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana, Eamonn J. Keogh
2018	J	`jnl`	The UEA multivariate time series classification archive, 2018. CoRR Anthony J. Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn, James Large, Aaron Bostrom, Paul Southam, Eamonn J. Keogh
2018	A*	`conf`	Time Series Chains: A Novel Tool for Time Series Data Mining. IJCAI Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh
2018	C	`conf`	Time Series Classification to Improve Poultry Welfare. ICMLA Alireza Abdoli, Amy C. Murillo, Chin-Chia Michael Yeh, Alec C. Gerry, Eamonn J. Keogh
2018	J	`jnl`	Time Series Classification to Improve Poultry Welfare. CoRR Alireza Abdoli, Amy C. Murillo, Chin-Chia Michael Yeh, Alec C. Gerry, Eamonn J. Keogh
2018	J	`jnl`	Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile. Data Min. Knowl. Discov. 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
2018	—	`conf`	VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. SIGMOD Conference Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh
2017	—	`ch.`	Curse of Dimensionality. Encyclopedia of Machine Learning and Data Mining Eamonn J. Keogh, Abdullah Mueen
2017	J	`jnl`	Generalizing DTW to the multi-dimensional case requires an adaptive approach. Data Min. Knowl. Discov. Mohammad Shokoohi-Yekta, Bing Hu, Hongxia Jin, Jun Wang, Eamonn J. Keogh
2017	A*	`conf`	Generating Synthetic Time Series to Augment Sparse Datasets. ICDM Germain Forestier, François Petitjean, Hoang Anh Dau, Geoffrey I. Webb, Eamonn J. Keogh
2017	—	`ch.`	Indexing and Mining Time Series Data. Encyclopedia of GIS Eamonn J. Keogh
2017	—	`ch.`	Instance-Based Learning. Encyclopedia of Machine Learning and Data Mining Eamonn J. Keogh
2017	—	`conf`	Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series. IEEE BigData Hoang Anh Dau, Diego Furtado Silva, François Petitjean, Germain Forestier, Anthony J. Bagnall, Eamonn J. Keogh
2017	J	`jnl`	Matrix Profile IV: Using Weakly Labeled Time Series to Predict Outcomes. Proc. VLDB Endow. Chin-Chia Michael Yeh, Nickolas Kavantzas, Eamonn J. Keogh
2017	A*	`conf`	Matrix Profile V: A Generic Technique to Incorporate Domain Knowledge into Motif Discovery. KDD Hoang Anh Dau, Eamonn J. Keogh
2017	A*	`conf`	Matrix Profile VI: Meaningful Multidimensional Motif Discovery. ICDM Chin-Chia Michael Yeh, Nickolas Kavantzas, Eamonn J. Keogh
2017	A*	`conf`	Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award). ICDM Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh
2017	A*	`conf`	Matrix Profile VIII: Domain Agnostic Online Semantic Segmentation at Superhuman Performance Levels. ICDM Shaghayegh Gharghabi, Yifei Ding, Chin-Chia Michael Yeh, Kaveh Kamgar, Liudmila Ulanova, Eamonn J. Keogh
2017	—	`ch.`	Nearest Neighbor. Encyclopedia of Machine Learning and Data Mining Eamonn J. Keogh
2017	B	`conf`	Query Suggestion to allow Intuitive Interactive Search in Multidimensional Time Series. SSDBM Yifei Ding, Eamonn J. Keogh
2017	J	`jnl`	Reliable early classification of time series based on discriminating the classes over time. Data Min. Knowl. Discov. Usue Mori, Alexander Mendiburu, Eamonn J. Keogh, José Antonio Lozano
2017	A*	`conf`	Searching Time Series with Invariance to Large Amounts of Uniform Scaling. ICDE Yilin Shen, Yanping Chen, Eamonn J. Keogh, Hongxia Jin
2017	J	`jnl`	The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Min. Knowl. Discov. Anthony J. Bagnall, Jason Lines, Aaron Bostrom, James Large, Eamonn J. Keogh
2017	—	`ch.`	Time Series. Encyclopedia of Machine Learning and Data Mining Eamonn J. Keogh
2016	J	`jnl`	A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy. CoRR Nurjahan Begum, Liudmila Ulanova, Hoang Anh Dau, Jun Wang, Eamonn J. Keogh
2016	J	`jnl`	Accelerating the discovery of unsupervised-shapelets. Data Min. Knowl. Discov. Jesin Zakaria, Abdullah Mueen, Eamonn J. Keogh, Neal E. Young
2016	J	`jnl`	Classification of streaming time series under more realistic assumptions. Data Min. Knowl. Discov. Bing Hu, Yanping Chen, Eamonn J. Keogh
2016	A	`conf`	Clustering in the Face of Fast Changing Streams. SDM Liudmila Ulanova, Nurjahan Begum, Mohammad Shokoohi-Yekta, Eamonn J. Keogh
2016	A*	`conf`	Extracting Optimal Performance from Dynamic Time Warping. KDD Abdullah Mueen, Eamonn J. Keogh
2016	J	`jnl`	Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm. Knowl. Inf. Syst. François Petitjean, Germain Forestier, Geoffrey I. Webb, Ann E. Nicholson, Yanping Chen, Eamonn J. Keogh
2016	J	`jnl`	Irrevocable-choice algorithms for sampling from a stream. Data Min. Knowl. Discov. Yan Zhu, Eamonn J. Keogh
2016	A*	`conf`	Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets. ICDM Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh
2016	A*	`conf`	Matrix Profile II: Exploiting a Novel Algorithm and GPUs to Break the One Hundred Million Barrier for Time Series Motifs and Joins. ICDM Yan Zhu, Zachary Zimmerman, Nader Shakibay Senobari, Chin-Chia Michael Yeh, Gareth J. Funning, Abdullah Mueen, Philip Brisk, Eamonn J. Keogh
2016	A*	`conf`	Matrix Profile III: The Matrix Profile Allows Visualization of Salient Subsequences in Massive Time Series. ICDM Chin-Chia Michael Yeh, Helga Van Herle, Eamonn J. Keogh
2016	A*	`conf`	Prefix and Suffix Invariant Dynamic Time Warping. ICDM Diego Furtado Silva, Gustavo E. A. P. A. Batista, Eamonn J. Keogh
2016	A	`conf`	Semi-Supervision Dramatically Improves Time Series Clustering under Dynamic Time Warping. CIKM Hoang Anh Dau, Nurjahan Begum, Eamonn J. Keogh
2016	—	`conf`	SiMPle: Assessing Music Similarity Using Subsequences Joins. ISMIR Diego Furtado Silva, Chin-Chia Michael Yeh, Gustavo E. A. P. A. Batista, Eamonn J. Keogh
2015	J	`jnl`	A general framework for never-ending learning from time series streams. Data Min. Knowl. Discov. Yanping Chen, Yuan Hao, Thanawin Rakthanmanon, Jesin Zakaria, Bing Hu, Eamonn J. Keogh
2015	A*	`conf`	Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy. KDD Nurjahan Begum, Liudmila Ulanova, Jun Wang, Eamonn J. Keogh
2015	A*	`conf`	Discovery of Meaningful Rules in Time Series. KDD Mohammad Shokoohi-Yekta, Yanping Chen, Bilson J. L. Campana, Bing Hu, Jesin Zakaria, Eamonn J. Keogh
2015	A*	`conf`	Efficient Long-Term Degradation Profiling in Time Series for Complex Physical Systems. KDD Liudmila Ulanova, Tan Yan, Haifeng Chen, Guofei Jiang, Eamonn J. Keogh, Kai Zhang
2015	J	`jnl`	Establishing the provenance of historical manuscripts with a novel distance measure. Pattern Anal. Appl. Bing Hu, Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Eamonn J. Keogh
2015	J	`jnl`	Exploring Low Cost Laser Sensors to Identify Flying Insect Species - Evaluation of Machine Learning and Signal Processing Methods. J. Intell. Robotic Syst. Diego Furtado Silva, Vinícius M. A. de Souza, Daniel P. W. Ellis, Eamonn J. Keogh, Gustavo E. A. P. A. Batista
2015	A	`conf`	On the Non-Trivial Generalization of Dynamic Time Warping to the Multi-Dimensional Case. SDM Mohammad Shokoohi-Yekta, Jun Wang, Eamonn J. Keogh
2015	A	`conf`	Scalable Clustering of Time Series with U-Shapelets. SDM Liudmila Ulanova, Nurjahan Begum, Eamonn J. Keogh
2015	J	`jnl`	Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series. Data Min. Knowl. Discov. Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh
2014	Misc	`conf`	Accelerating the dynamic time warping distance measure using logarithmetic arithmetic. ACSSC Joseph Tarango, Eamonn J. Keogh, Philip Brisk
2014	J	`jnl`	Beyond one billion time series: indexing and mining very large time series collections with i SAX2+. Knowl. Inf. Syst. Alessandro Camerra, Jin Shieh, Themis Palpanas, Thanawin Rakthanmanon, Eamonn J. Keogh
2014	J	`jnl`	CID: an efficient complexity-invariant distance for time series. Data Min. Knowl. Discov. Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Oben Moses Tataw, Vinícius M. A. de Souza
2014	A*	`conf`	Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification. ICDM François Petitjean, Germain Forestier, Geoffrey I. Webb, Ann E. Nicholson, Yanping Chen, Eamonn J. Keogh
2014	J	`jnl`	Flying Insect Classification with Inexpensive Sensors. CoRR Yanping Chen, Adena Why, Gustavo E. A. P. A. Batista, Agenor Mafra-Neto, Eamonn J. Keogh
2014	B	`conf`	Generating Synthetic Data to Allow Learning from a Single Exemplar per Class. SISAP Liudmila Ulanova, Yuan Hao, Eamonn J. Keogh
2014	J	`jnl`	Rare Time Series Motif Discovery from Unbounded Streams. Proc. VLDB Endow. Nurjahan Begum, Eamonn J. Keogh
2013	—	`conf`	A Minimum Description Length Technique for Semi-Supervised Time Series Classification. IRI (best papers) Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh
2013	J	`jnl`	Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping. ACM Trans. Knowl. Discov. Data Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh
2013	—	`conf`	Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps. ICMLA (1) Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Daniel P. W. Ellis
2013	A*	`conf`	Classification of Multi-dimensional Streaming Time Series by Weighting Each Classifier's Track Record. ICDM Bing Hu, Yanping Chen, Jesin Zakaria, Liudmila Ulanova, Eamonn J. Keogh
2013	A	`conf`	Clustering of Symbols Using Minimal Description Length. ICDAR Oben M. Tataw, Thanawin Rakthanmanon, Eamonn J. Keogh
2013	A*	`conf`	DTW-D: time series semi-supervised learning from a single example. KDD Yanping Chen, Bing Hu, Eamonn J. Keogh, Gustavo E. A. P. A. Batista
2013	A*	`conf`	Data Mining a Trillion Time Series Subsequences Under Dynamic Time Warping. IJCAI Thanawin Rakthanmanon, Eamonn J. Keogh
2013	J	`jnl`	Experimental comparison of representation methods and distance measures for time series data. Data Min. Knowl. Discov. Xiaoyue Wang, Abdullah Mueen, Hui Ding, Goce Trajcevski, Peter Scheuermann, Eamonn J. Keogh
2013	A	`conf`	Fast Shapelets: A Scalable Algorithm for Discovering Time Series Shapelets. SDM Eamonn J. Keogh, Thanawin Rakthanmanon
2013	Misc	`conf`	Instruction set extensions for Dynamic Time Warping. CODES+ISSS Joseph Tarango, Eamonn J. Keogh, Philip Brisk
2013	A*	`conf`	Parameter-Free Audio Motif Discovery in Large Data Archives. ICDM Yuan Hao, Mohammad Shokoohi-Yekta, George Papageorgiou, Eamonn J. Keogh
2013	J	`jnl`	Quantitative Analysis of Live-Cell Growth at the Shoot Apex of Arabidopsis thaliana: Algorithms for Feature Measurement and Temporal Alignment. IEEE ACM Trans. Comput. Biol. Bioinform. Oben M. Tataw, G. Venugopala Reddy, Eamonn J. Keogh, Amit K. Roy-Chowdhury
2013	A	`conf`	Time Series Classification under More Realistic Assumptions. SDM Bing Hu, Yanping Chen, Eamonn J. Keogh
2013	Misc	`conf`	Towards a minimum description length based stopping criterion for semi-supervised time series classification. IRI Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh
2013	A*	`conf`	Towards never-ending learning from time series streams. KDD Yuan Hao, Yanping Chen, Jesin Zakaria, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh
2012	A	`conf`	A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets. SDM Qiang Zhu, Gustavo E. A. P. A. Batista, Thanawin Rakthanmanon, Eamonn J. Keogh
2012	A*	`conf`	Clustering Time Series Using Unsupervised-Shapelets. ICDM Jesin Zakaria, Abdullah Mueen, Eamonn J. Keogh
2012	A	`conf`	Diversifying query results on semi-structured data. CIKM Mahbub Hasan, Abdullah Mueen, Vassilis J. Tsotras, Eamonn J. Keogh
2012	J	`jnl`	Efficiently Finding Near Duplicate Figures in Archives of Historical Documents. J. Multim. Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh
2012	—	`conf`	Getting your acceptance rate to 80%: a checklist for publishing. SIGMOD/PODS PhD Symposium Eamonn J. Keogh
2012	A	`conf`	Image Mining of Historical Manuscripts to Establish Provenance. SDM Bing Hu, Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Eamonn J. Keogh
2012	J	`jnl`	MDL-based time series clustering. Knowl. Inf. Syst. Thanawin Rakthanmanon, Eamonn J. Keogh, Stefano Lonardi, Scott Evans
2012	A	`conf`	Mining Massive Archives of Mice Sounds with Symbolized Representations. SDM Jesin Zakaria, Sarah Rotschafer, Abdullah Mueen, Khaleel Razak, Eamonn J. Keogh
2012	J	`jnl`	Mining historical manuscripts with local color patches. Knowl. Inf. Syst. Qiang Zhu, Eamonn J. Keogh
2012	A	`conf`	Monitoring and Mining Insect Sounds in Visual Space. SDM Yuan Hao, Bilson J. L. Campana, Eamonn J. Keogh
2012	A*	`conf`	Searching and mining trillions of time series subsequences under dynamic time warping. KDD Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh
2011	A	`conf`	A Complexity-Invariant Distance Measure for Time Series. SDM Gustavo E. A. P. A. Batista, Xiaoyue Wang, Eamonn J. Keogh
2011	J	`jnl`	A disk-aware algorithm for time series motif discovery. Data Min. Knowl. Discov. Abdullah Mueen, Eamonn J. Keogh, Qiang Zhu, Sydney Cash, M. Brandon Westover, Nima Bigdely Shamlo
2011	J	`jnl`	An efficient and effective similarity measure to enable data mining of petroglyphs. Data Min. Knowl. Discov. Qiang Zhu, Xiaoyue Wang, Eamonn J. Keogh, Sang-Hee Lee
2011	—	`ch.`	Data, Mining Time Series Data. International Encyclopedia of Statistical Science Eamonn J. Keogh
2011	A*	`conf`	Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL. ICDM Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh
2011	A*	`conf`	Logical-shapelets: an expressive primitive for time series classification. KDD Abdullah Mueen, Eamonn J. Keogh, Neal E. Young
2011	A*	`conf`	Mining Historical Documents for Near-Duplicate Figures. ICDM Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh
2011	A*	`conf`	SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining. KDD Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Agenor Mafra-Neto, Edgar Rowton
2011	—	`conf`	Searching historical manuscripts for near-duplicate figures. HIP@ICDAR Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh
2011	A*	`conf`	Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data. ICDM Thanawin Rakthanmanon, Eamonn J. Keogh, Stefano Lonardi, Scott Evans
2011	J	`jnl`	Time series shapelets: a novel technique that allows accurate, interpretable and fast classification. Data Min. Knowl. Discov. Lexiang Ye, Eamonn J. Keogh
2011	—	`conf`	Towards Automatic Classification on Flying Insects Using Inexpensive Sensors. ICMLA (1) Gustavo E. A. P. A. Batista, Yuan Hao, Eamonn J. Keogh, Agenor Mafra-Neto
2011	—	`conf`	Towards Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL. Algorithmic Probability and Friends Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh
2010	A	`conf`	A Compression Based Distance Measure for Texture. SDM Bilson J. L. Campana, Eamonn J. Keogh
2010	J	`jnl`	A brief survey on sequence classification. SIGKDD Explor. Zhengzheng Xing, Jian Pei, Eamonn J. Keogh
2010	J	`jnl`	A compression-based distance measure for texture. Stat. Anal. Data Min. Bilson J. L. Campana, Eamonn J. Keogh
2010	A*	`conf`	Accelerating Dynamic Time Warping Subsequence Search with GPUs and FPGAs. ICDM Doruk Sart, Abdullah Mueen, Walid A. Najjar, Eamonn J. Keogh, Vit Niennattrakul
2010	J	`jnl`	Annotating Historical Archives of Images. Int. J. Digit. Libr. Syst. Xiaoyue Wang, Lexiang Ye, Eamonn J. Keogh, Christian R. Shelton
2010	C	`conf`	Classification of Live Moths Combining Texture, Color and Shape Primitives. ICMLA Gustavo E. A. P. A. Batista, Bilson J. L. Campana, Eamonn J. Keogh
2010	—	`ch.`	Curse of Dimensionality. Encyclopedia of Machine Learning Eamonn J. Keogh, Abdullah Mueen
2010	A*	`conf`	Data Editing Techniques to Allow the Application of Distance-Based Outlier Detection to Streams. ICDM Vit Niennattrakul, Eamonn J. Keogh, Chotirat Ann Ratanamahatana
2010	J	`jnl`	Experimental Comparison of Representation Methods and Distance Measures for Time Series Data CoRR Xiaoyue Wang, Hui Ding, Goce Trajcevski, Peter Scheuermann, Eamonn J. Keogh
2010	A*	`conf`	How to Do Good Data Mining Research and Get it Published in Top Venues. ICDM Eamonn J. Keogh
2010	—	`ch.`	Instance-Based Learning. Encyclopedia of Machine Learning Eamonn J. Keogh
2010	—	`ch.`	Mining Time Series Data. Data Mining and Knowledge Discovery Handbook Chotirat Ann Ratanamahatana, Jessica Lin, Dimitrios Gunopulos, Eamonn J. Keogh, Michail Vlachos, Gautam Das
2010	A*	`conf`	Mother Fugger: Mining Historical Manuscripts with Local Color Patches. ICDM Qiang Zhu, Eamonn J. Keogh
2010	—	`ch.`	Nearest Neighbor. Encyclopedia of Machine Learning Eamonn J. Keogh
2010	A*	`conf`	Online discovery and maintenance of time series motifs. KDD Abdullah Mueen, Eamonn J. Keogh
2010	A*	`conf`	Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times. ICDM Jin Shieh, Eamonn J. Keogh
2010	—	`ch.`	Time Series. Encyclopedia of Machine Learning Eamonn J. Keogh
2010	B	`conf`	Using CAPTCHAs to Index Cultural Artifacts. IDA Qiang Zhu, Eamonn J. Keogh
2010	A*	`conf`	iSAX 2.0: Indexing and Mining One Billion Time Series. ICDM Alessandro Camerra, Themis Palpanas, Jin Shieh, Eamonn J. Keogh
2009	C	`conf`	Augmenting Historical Manuscripts with Automatic Hyperlinks. ISM Xiaoyue Wang, Eamonn J. Keogh
2009	A*	`conf`	Augmenting the generalized hough transform to enable the mining of petroglyphs. KDD Qiang Zhu, Xiaoyue Wang, Eamonn J. Keogh, Sang-Hee Lee
2009	A	`conf`	Autocannibalistic and Anyspace Indexing Algorithms with Application to Sensor Data Mining. SDM Lexiang Ye, Xiaoyue Wang, Eamonn J. Keogh, Agenor Mafra-Neto
2009	—	`ch.`	Compression-Based Data Mining. Encyclopedia of Data Warehousing and Mining Eamonn J. Keogh, Li Keogh, John C. Handley
2009	A	`conf`	Exact Discovery of Time Series Motifs. SDM Abdullah Mueen, Eamonn J. Keogh, Qiang Zhu, Sydney Cash, M. Brandon Westover
2009	A*	`conf`	Finding Time Series Motifs in Disk-Resident Data. ICDM Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Shamlo
2009	—	`conf`	Finding centuries-old hyperlinks with a novel semi-supervised learning technique. JCDL Xiaoyue Wang, Eamonn J. Keogh
2009	J	`jnl`	Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures. VLDB J. Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Michail Vlachos, Sang-Hee Lee, Pavlos Protopapas
2009	A*	`conf`	Time series shapelets: a new primitive for data mining. KDD Lexiang Ye, Eamonn J. Keogh
2008	—	`ch.`	A Clustering Analysis for Target Group Identification by Locality in Motor Insurance Industry. Soft Computing Applications in Business Xiaozhe Wang, Eamonn J. Keogh
2008	—	`conf`	Annotating historical archives of images. JCDL Xiaoyue Wang, Lexiang Ye, Eamonn J. Keogh, Christian R. Shelton
2008	J	`jnl`	Converting non-parametric distance-based classification to anytime algorithms. Pattern Anal. Appl. Xiaopeng Xi, Ken Ueno, Eamonn J. Keogh, Dah-Jye Lee
2008	J	`jnl`	Disk aware discord discovery: finding unusual time series in terabyte sized datasets. Knowl. Inf. Syst. Dragomir Yankov, Eamonn J. Keogh, Umaa Rebbapragada
2008	J	`jnl`	Efficiently finding unusual shapes in large image databases. Data Min. Knowl. Discov. Li Wei, Eamonn J. Keogh, Xiaopeng Xi, Melissa Yoder
2008	J	`jnl`	Fast Best-Match Shape Searching in Rotation-Invariant Metric Spaces. IEEE Trans. Multim. Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Wendy L. Hodges
2008	—	`ch.`	Indexing and Mining Time Series Data. Encyclopedia of GIS Eamonn J. Keogh
2008	J	`jnl`	Querying and mining of time series data: experimental comparison of representations and distance measures. Proc. VLDB Endow. Hui Ding, Goce Trajcevski, Peter Scheuermann, Xiaoyue Wang, Eamonn J. Keogh
2008	—	`conf`	Real-Time Classification of Streaming Sensor Data. ICTAI (1) Shashwati Kasetty, Candice Stafford, Gregory P. Walker, Xiaoyue Wang, Eamonn J. Keogh
2008	J	`jnl`	Scaling and time warping in time series querying. VLDB J. Ada Wai-Chee Fu, Eamonn J. Keogh, Leo Yung Hang Lau, Chotirat (Ann) Ratanamahatana, Raymond Chi-Wing Wong
2008	J	`jnl`	Streaming Time Series Summarization Using User-Defined Amnesic Functions. IEEE Trans. Knowl. Data Eng. Themis Palpanas, Michail Vlachos, Eamonn J. Keogh, Dimitrios Gunopulos
2008	A	`conf`	The Asymmetric Approximate Anytime Join: A New Primitive with Applications to Data Mining. SDM Lexiang Ye, Xiaoyue Wang, Dragomir Yankov, Eamonn J. Keogh
2007	J	`jnl`	Compression-based data mining of sequential data. Data Min. Knowl. Discov. Eamonn J. Keogh, Stefano Lonardi, Chotirat Ann Ratanamahatana, Li Wei, Sang-Hee Lee, John C. Handley
2007	A*	`conf`	Detecting time series motifs under uniform scaling. KDD Dragomir Yankov, Eamonn J. Keogh, Jose Medina, Bill Yuan-chi Chiu, Victor B. Zordan
2007	A*	`conf`	Disk Aware Discord Discovery: Finding Unusual Time Series in Terabyte Sized Datasets. ICDM Dragomir Yankov, Eamonn J. Keogh, Umaa Rebbapragada
2007	J	`jnl`	Domain-Driven, Actionable Knowledge Discovery. IEEE Intell. Syst. Longbing Cao, Chengqi Zhang, Qiang Yang, David A. Bell, Michail Vlachos, Bahar Taneri, Eamonn J. Keogh, Philip S. Yu, Ning Zhong, Mafruz Zaman Ashrafi, David Taniar, Eugene Dubossarsky, Warwick Graco
2007	J	`jnl`	Efficient query filtering for streaming time series with applications to semisupervised learning of time series classifiers. Knowl. Inf. Syst. Li Wei, Eamonn J. Keogh, Helga Van Herle, Agenor Mafra-Neto, Russell J. Abbott
2007	J	`jnl`	Experiencing SAX: a novel symbolic representation of time series. Data Min. Knowl. Discov. Jessica Lin, Eamonn J. Keogh, Li Wei, Stefano Lonardi
2007	A	`conf`	Fast Best-Match Shape Searching in Rotation Invariant Metric Spaces. SDM Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Wendy L. Hodges
2007	A	`conf`	Finding Motifs in a Database of Shapes. SDM Xiaopeng Xi, Eamonn J. Keogh, Li Wei, Agenor Mafra-Neto
2007	J	`jnl`	Finding the most unusual time series subsequence: algorithms and applications. Knowl. Inf. Syst. Eamonn J. Keogh, Jessica Lin, Sang-Hee Lee, Helga Van Herle
2007	A*	`conf`	Locally Constrained Support Vector Clustering. ICDM Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan
2007	—	`conf`	TS2-tree - an efficient similarity based organization for trajectory data. GIS Petko Bakalov, Eamonn J. Keogh, Vassilis J. Tsotras
2007	—	`conf`	Visual Exploration of Genomic Data. PKDD Michail Vlachos, Bahar Taneri, Eamonn J. Keogh, Philip S. Yu
2007	A	`conf`	WAT: Finding Top-K Discords in Time Series Database. SDM Yingyi Bu, Oscar Tat-Wing Leung, Ada Wai-Chee Fu, Eamonn J. Keogh, Jian Pei, Sam Meshkin
2006	J	`jnl`	A Bit Level Representation for Time Series Data Mining with Shape Based Similarity. Data Min. Knowl. Discov. Anthony J. Bagnall, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh, Stefano Lonardi, Gareth J. Janacek
2006	A*	`conf`	A Decade of Progress in Indexing and Mining Large Time Series Databases. VLDB Eamonn J. Keogh
2006	A*	`conf`	Anytime Classification Using the Nearest Neighbor Algorithm with Applications to Stream Mining. ICDM Ken Ueno, Xiaopeng Xi, Eamonn J. Keogh, Dah-Jye Lee
2006	—	`conf`	Clustering Workflow Requirements Using Compression Dissimilarity Measure. ICDM Workshops Li Wei, John C. Handley, Nathaniel Martin, Tong Sun, Eamonn J. Keogh
2006	A*	`conf`	Configurable cache subsetting for fast cache tuning. DAC Pablo Viana, Ann Gordon-Ross, Eamonn J. Keogh, Edna Barros, Frank Vahid
2006	A*	`conf`	Data mining and information retrieval in time series/multimedia databases. ACM Multimedia Eamonn J. Keogh
2006	J	`jnl`	Efficient Discovery of Unusual Patterns in Time Series. New Gener. Comput. Stefano Lonardi, Jessica Lin, Eamonn J. Keogh, Bill Yuan-chi Chiu
2006	—	`conf`	Ensembles of Nearest Neighbor Forecasts. ECML Dragomir Yankov, Dennis DeCoste, Eamonn J. Keogh
2006	A*	`conf`	Fast time series classification using numerosity reduction. ICML Xiaopeng Xi, Eamonn J. Keogh, Christian R. Shelton, Li Wei, Chotirat Ann Ratanamahatana
2006	C	`conf`	Finding Time Series Discords Based on Haar Transform. ADMA Ada Wai-Chee Fu, Oscar Tat-Wing Leung, Eamonn J. Keogh, Jessica Lin
2006	J	`jnl`	Finding Unusual Medical Time-Series Subsequences: Algorithms and Applications. IEEE Trans. Inf. Technol. Biomed. Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu, Helga Van Herle
2006	A*	`conf`	Global distance-based segmentation of trajectories. KDD Aris Anagnostopoulos, Michail Vlachos, Marios Hadjieleftheriou, Eamonn J. Keogh, Philip S. Yu
2006	—	`conf`	Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data. PKDD Jessica Lin, Eamonn J. Keogh
2006	J	`jnl`	Indexing Multidimensional Time-Series. VLDB J. Michail Vlachos, Marios Hadjieleftheriou, Dimitrios Gunopulos, Eamonn J. Keogh
2006	A*	`conf`	Intelligent Icons: Integrating Lite-Weight Data Mining and Visualization into GUI Operating Systems. ICDM Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Stefano Lonardi, Jin Shieh, Scott Sirowy
2006	A*	`conf`	LB_Keogh Supports Exact Indexing of Shapes under Rotation Invariance with Arbitrary Representations and Distance Measures. VLDB Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Sang-Hee Lee, Michail Vlachos
2006	A*	`conf`	Manifold Clustering of Shapes. ICDM Dragomir Yankov, Eamonn J. Keogh
2006	A*	`conf`	SAXually Explicit Images: Finding Unusual Shapes. ICDM Li Wei, Eamonn J. Keogh, Xiaopeng Xi
2006	A*	`conf`	Semi-supervised time series classification. KDD Li Wei, Eamonn J. Keogh
2005	B	`conf`	A MPAA-Based Iterative Clustering Algorithm Augmented by Nearest Neighbors Search for Time-Series Data Streams. PAKDD Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dimitrios Gunopulos, Jian-wei Liu, Shou-Jian Yu, Jia-Jin Le
2005	B	`conf`	A Novel Bit Level Time Series Representation with Implication of Similarity Search and Clustering. PAKDD Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh, Anthony J. Bagnall, Stefano Lonardi
2005	B	`conf`	A Practical Tool for Visualizing and Data Mining Medical Time Series. CBMS Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) Ratanamahatana, Helga Van Herle
2005	B	`conf`	Approximations to Magic: Finding Unusual Medical Time Series. CBMS Jessica Lin, Eamonn J. Keogh, Ada Wai-Chee Fu, Helga Van Herle
2005	B	`conf`	Assumption-Free Anomaly Detection in Time Series. SSDBM Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) Ratanamahatana
2005	A*	`conf`	Atomic Wedgie: Efficient Query Filtering for Streaming Times Series. ICDM Li Wei, Eamonn J. Keogh, Helga Van Herle, Agenor Mafra-Neto
2005	J	`jnl`	Clustering of time-series subsequences is meaningless: implications for previous and future research. Knowl. Inf. Syst. Eamonn J. Keogh, Jessica Lin
2005	B	`conf`	Dot Plots for Time Series Analysis. ICTAI Dragomir Yankov, Eamonn J. Keogh, Stefano Lonardi, Ada Wai-Chee Fu
2005	B	`conf`	Efficient trajectory joins using symbolic representations. Mobile Data Management Petko Bakalov, Marios Hadjieleftheriou, Eamonn J. Keogh, Vassilis J. Tsotras
2005	—	`conf`	Elastic Partial Matching of Time Series. PKDD Longin Jan Latecki, Vasilis Megalooikonomou, Qiang Wang, Rolf Lakämper, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
2005	J	`jnl`	Exact indexing of dynamic time warping. Knowl. Inf. Syst. Eamonn J. Keogh, Chotirat (Ann) Ratanamahatana
2005	J	`jnl`	Guest Editorial. Mach. Learn. Eamonn J. Keogh
2005	A*	`conf`	HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence. ICDM Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu
2005	—	`ch.`	Indexing Multi-Dimensional Trajectories for Similarity Queries. Spatial Databases Michail Vlachos, Marios Hadjieleftheriou, Eamonn J. Keogh, Dimitrios Gunopulos
2005	J	`jnl`	Integrating Lite-Weight but Ubiquitous Data Mining into GUI Operating Systems. J. Univers. Comput. Sci. Li Wei, Eamonn J. Keogh, Xiaopeng Xi, Stefano Lonardi
2005	—	`ch.`	Mining Time Series Data. The Data Mining and Knowledge Discovery Handbook Chotirat (Ann) Ratanamahatana, Jessica Lin, Dimitrios Gunopulos, Eamonn J. Keogh, Michail Vlachos, Gautam Das
2005	—	`conf`	Multimedia Retrieval Using Time Series Representation and Relevance Feedback. ICADL Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
2005	A*	`conf`	Partial Elastic Matching of Time Series. ICDM Longin Jan Latecki, Vasileios Megalooikonomou, Qiang Wang, Rolf Lakämper, Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
2005	—	`conf`	Recent Advances in Mining Time Series Data. PKDD Eamonn J. Keogh
2005	A*	`conf`	Scaling and Time Warping in Time Series Querying. VLDB Ada Wai-Chee Fu, Eamonn J. Keogh, Leo Yung Hang Lau, Chotirat (Ann) Ratanamahatana
2005	A	`conf`	Three Myths about Dynamic Time Warping Data Mining. SDM Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
2005	A	`conf`	Time-series Bitmaps: a Practical Visualization Tool for Working with Large Time Series Databases. SDM Nitin Kumar, Venkata Nishanth Lolla, Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) Ratanamahatana
2005	—	`conf`	Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases. KES (2) Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
2005	A	`conf`	Visualization and Mining of Temporal Data. IEEE Visualization Eamonn J. Keogh
2005	J	`jnl`	Visualizing and discovering non-trivial patterns in large time series databases. Inf. Vis. Jessica Lin, Eamonn J. Keogh, Stefano Lonardi
2004	—	`conf`	A Grid-Based Index Method for Time Warping Distance. WAIM Jiyuan An, Yi-Ping Phoebe Chen, Eamonn J. Keogh
2004	A*	`conf`	Indexing Large Human-Motion Databases. VLDB Eamonn J. Keogh, Themis Palpanas, Victor B. Zordan, Dimitrios Gunopulos, Marc Cardle
2004	B	`conf`	Iterative Incremental Clustering of Time Series. EDBT Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dimitrios Gunopulos
2004	A	`conf`	Making Time-Series Classification More Accurate Using Learned Constraints. SDM Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
2004	A*	`conf`	Online Amnesic Approximation of Streaming Time Series. ICDE Themistoklis Palpanas, Michail Vlachos, Eamonn J. Keogh, Dimitrios Gunopulos, Wagner Truppel
2004	A*	`conf`	Towards parameter-free data mining. KDD Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) Ratanamahatana
2004	A*	`conf`	Visually mining and monitoring massive time series. KDD Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jeffrey P. Lankford, Donna M. Nystrom
2004	A*	`conf`	VizTree: a Tool for Visually Mining and Monitoring Massive Time Series Databases. VLDB Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jeffrey P. Lankford, Donna M. Nystrom
2004	—	`conf`	We Have Seen the Future, and It Is Symbolic. ACSW Eamonn J. Keogh, Jessica Lin, Stefano Lonardi, Bill Yuan-chi Chiu
2003	Misc	`conf`	(Not) Finding Rules in Time Series: A Surprising Result with Implications for Previous and Future Research. IC-AI Jessica Lin, Eamonn J. Keogh, Wagner Truppel
2003	—	`conf`	A Gentle Introduction to Machine Learning and Data Mining for the Database Community. SBBD Eamonn J. Keogh
2003	—	`conf`	A symbolic representation of time series, with implications for streaming algorithms. DMKD Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Bill Yuan-chi Chiu
2003	A*	`conf`	Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research. ICDM Eamonn J. Keogh, Jessica Lin, Wagner Truppel
2003	—	`conf`	Clustering of streaming time series is meaningless. DMKD Jessica Lin, Eamonn J. Keogh, Wagner Truppel
2003	—	`conf`	Efficiently Finding Arbitrarily Scaled Patterns in Massive Time Series Databases. PKDD Eamonn J. Keogh
2003	C	`conf`	Grid-Based Indexing for Large Time Series Databases. IDEAL Jiyuan An, Hanxiong Chen, Kazutaka Furuse, Nobuo Ohbo, Eamonn J. Keogh
2003	A*	`conf`	Indexing multi-dimensional time-series with support for multiple distance measures. KDD Michail Vlachos, Marios Hadjieleftheriou, Dimitrios Gunopulos, Eamonn J. Keogh
2003	J	`jnl`	On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration. Data Min. Knowl. Discov. Eamonn J. Keogh, Shruti Kasetty
2003	A*	`conf`	Probabilistic discovery of time series motifs. KDD Bill Yuan-chi Chiu, Eamonn J. Keogh, Stefano Lonardi
2002	C	`conf`	An Augmented Visual Query Mechanism for Finding Patterns in Time Series Data. FQAS Eamonn J. Keogh, Harry Hochheiser, Ben Shneiderman
2002	A*	`conf`	Exact Indexing of Dynamic Time Warping. VLDB Eamonn J. Keogh
2002	A*	`conf`	Finding surprising patterns in a time series database in linear time and space. KDD Eamonn J. Keogh, Stefano Lonardi, Bill Yuan-chi Chiu
2002	—	`conf`	Indexing and Mining Time Series. SBBD Eamonn J. Keogh
2002	A	`conf`	Iterative Deepening Dynamic Time Warping for Time Series. SDM Selina Chu, Eamonn J. Keogh, David M. Hart, Michael J. Pazzani
2002	J	`jnl`	Learning the Structure of Augmented Bayesian Classifiers. Int. J. Artif. Intell. Tools Eamonn J. Keogh, Michael J. Pazzani
2002	J	`jnl`	Locally adaptive dimensionality reduction for indexing large time series databases. ACM Trans. Database Syst. Kaushik Chakrabarti, Eamonn J. Keogh, Sharad Mehrotra, Michael J. Pazzani
2002	A*	`conf`	Mining Motifs in Massive Time Series Databases. ICDM Pranav Patel, Eamonn J. Keogh, Jessica Lin, Stefano Lonardi
2002	A*	`conf`	On the need for time series data mining benchmarks: a survey and empirical demonstration. KDD Eamonn J. Keogh, Shruti Kasetty
2001	A*	`conf`	An Online Algorithm for Segmenting Time Series. ICDM Eamonn J. Keogh, Selina Chu, David M. Hart, Michael J. Pazzani
2001	A	`conf`	Derivative Dynamic Time Warping. SDM Eamonn J. Keogh, Michael J. Pazzani
2001	J	`jnl`	Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases. Knowl. Inf. Syst. Eamonn J. Keogh, Kaushik Chakrabarti, Michael J. Pazzani, Sharad Mehrotra
2001	A*	`conf`	Ensemble-index: a new approach to indexing large databases. KDD Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
2001	—	`conf`	Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases. SIGMOD Conference Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehrotra, Michael J. Pazzani
2000	B	`conf`	A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases. PAKDD Eamonn J. Keogh, Michael J. Pazzani
2000	A*	`conf`	Scaling up dynamic time warping for datamining applications. KDD Eamonn J. Keogh, Michael J. Pazzani
1999	B	`conf`	An Indexing Scheme for Fast Similarity Search in Large Time Series Databases. SSDBM Eamonn J. Keogh, Michael J. Pazzani
1999	A	`conf`	Learning augmented Bayesian classifiers: A comparison of distribution-based and classification-based approaches. AISTATS Eamonn J. Keogh, Michael J. Pazzani
1999	A*	`conf`	Relevance Feedback Retrieval of Time Series Data. SIGIR Eamonn J. Keogh, Michael J. Pazzani
1999	—	`conf`	Scaling up Dynamic Time Warping to Massive Dataset. PKDD Eamonn J. Keogh, Michael J. Pazzani
1998	A*	`conf`	An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback. KDD Eamonn J. Keogh, Michael J. Pazzani
1997	A*	`conf`	A Probabilistic Approach to Fast Pattern Matching in Time Series Databases. KDD Eamonn J. Keogh, Padhraic Smyth
1997	B	`conf`	Fast Similarity Search in the Presence of Longitudinal Scaling in Time Series Databases. ICTAI Eamonn J. Keogh