John Paparrizos

Orcid: 0000-0002-7592-748X

Affiliations:

Ohio State University, OH, USA

According to our database¹, John Paparrizos authored at least 34 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

Article

PhD thesis

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Bibliography

2024

Time-Series Anomaly Detection: Overview and New Trends.

[BibT_eX]

[DOI]

Proc. VLDB Endow., August, 2024

Bridging the Gap: A Decade Review of Time-Series Clustering Methods.

[BibT_eX]

[DOI]

John Paparrizos

Fan Yang

Haojun Li

CoRR, 2024

A Survey on Time-Series Distance Measures.

[BibT_eX]

[DOI]

CoRR, 2024

Dive into Time-Series Anomaly Detection: A Decade Review.

[BibT_eX]

[DOI]

CoRR, 2024

The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark.

[BibT_eX]

[DOI]

Qinghua Liu

John Paparrizos

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Beyond the Dimensions: A Structured Evaluation of Multivariate Time Series Distance Measures.

[BibT_eX]

[DOI]

Jens E. d'Hondt

Odysseas Papapetrou

John Paparrizos

Proceedings of the 40th International Conference on Data Engineering, ICDE 2024, 2024

AdaEdge: A Dynamic Compression Selection Framework for Resource Constrained Devices.

[BibT_eX]

[DOI]

Chunwei Liu

John Paparrizos

Aaron J. Elmore

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

ADecimo: Model Selection for Time Series Anomaly Detection.

[BibT_eX]

[DOI]

Paul Boniol

Emmanouil Sylligardos

John Paparrizos

Panos E. Trahanias

Themis Palpanas

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

An Interactive Dive into Time-Series Anomaly Detection.

[BibT_eX]

[DOI]

Paul Boniol

John Paparrizos

Themis Palpanas

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments.

[BibT_eX]

[DOI]

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2023

Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series.

[BibT_eX]

[DOI]

Emmanouil Sylligardos

Proc. VLDB Endow., 2023

Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

Odyssey: An Engine Enabling The Time-Series Clustering Journey.

[BibT_eX]

[DOI]

John Paparrizos

Sai Prasanna Teja Reddy

Proc. VLDB Endow., 2023

Querying Time-Series Data: A Comprehensive Comparison of Distance Measures.

[BibT_eX]

[DOI]

IEEE Data Eng. Bull., 2023

New Trends in Time Series Anomaly Detection.

[BibT_eX]

[DOI]

Paul Boniol

John Paparrizos

Themis Palpanas

Proceedings of the Proceedings 26th International Conference on Extending Database Technology, 2023

2022

TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2022

Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2022

Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2022

Fast Adaptive Similarity Search through Variance-Aware Quantization.

[BibT_eX]

[DOI]

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Decomposed Bounded Floats for Fast Compression and Queries.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

SAND in Action: Subsequence Anomaly Detection for Streams.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

SAND: Streaming Subsequence Anomaly Detection.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

Good to the Last Bit: Data-Driven Encoding with CodecDB.

[BibT_eX]

[DOI]

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

VergeDB: A Database for IoT Analytics on Edge Devices.

[BibT_eX]

[DOI]

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

2020

PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2020

Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Conference on Management of Data, 2020

2019

Artificial Intelligence in Resource-Constrained and Shared Environments.

[BibT_eX]

[DOI]

ACM SIGOPS Oper. Syst. Rev., 2019

GRAIL: Efficient Time-Series Representation Learning.

[BibT_eX]

[DOI]

John Paparrizos

Michael J. Franklin

Proc. VLDB Endow., 2019

Band-limited Training and Inference for Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

Fast and Accurate Time-Series Clustering.

[BibT_eX]

[DOI]

John Paparrizos

Luis Gravano

ACM Trans. Database Syst., 2017

2016

k-Shape: Efficient and Accurate Clustering of Time Series.

[BibT_eX]

[DOI]

John Paparrizos

Luis Gravano

SIGMOD Rec., 2016

Predicting the impact of scientific concepts using full-text features.

[BibT_eX]

[DOI]

J. Assoc. Inf. Sci. Technol., 2016

The Social Dynamics of Language Change in Online Networks.

[BibT_eX]

[DOI]

Proceedings of the Social Informatics - 8th International Conference, 2016

Detecting Devastating Diseases in Search Logs.

[BibT_eX]

[DOI]

John Paparrizos

Ryen W. White

Eric Horvitz

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

John Paparrizos

Timeline

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