mlsanityData to 14 Oct 2026

Random Dilated Shapelet Transform: A New Approach for Time Series Shapelets

arXiv 2109.13514 ↗First posted 28 Sep 2021cs.CV cs.LGcited by 22

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Abstract (arXiv)

Shapelet-based algorithms are widely used for time series classification because of their ease of interpretation, but they are currently outperformed by recent state-of-the-art approaches. We present a new formulation of time series shapelets including the notion of dilation, and we introduce a new shapelet feature to enhance their discriminative power for classification. Experiments performed on 112 datasets show that our method improves on the state-of-the-art shapelet algorithm, and achieves comparable accuracy to recent state-of-the-art approaches, without sacrificing neither scalability, nor interpretability.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 15 of its 24 references that are in the map. First posted on arXiv 28 Sep 2021.

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15 of 24 references.

References · 15

  1. 2018Deep learning for time series classification: a reviewcited by 576
  2. 2018The UCR Time Series Archivecited by 431
  3. 2019InceptionTime: Finding AlexNet for Time Series Classificationcited by 387
  4. 2019ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernelscited by 339
  5. 2020Benchmarking Multivariate Time Series Classification Algorithmscited by 145
  6. 2021HIVE-COTE 2.0: a new meta ensemble for time series classificationcited by 118
  7. 2019catch22: CAnonical Time-series CHaracteristicscited by 105
  8. 2019TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classificationcited by 67
  9. 2020The Canonical Interval Forest (CIF) Classifier for Time Series Classificationcited by 48
  10. 2017Fast and Accurate Time Series Classification with WEASELcited by 47
  11. 2020Interpretable Time Series Classification using Linear Models and Multi-resolution Multi-domain Symbolic Representationscited by 31
  12. 2021The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classificationcited by 26
3 more
  1. 2015Ultra-Fast Shapelets for Time Series Classificationcited by 7
  2. 2020A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifierscited by 6
  3. 2019GENDIS: GENetic DIscovery of Shapeletscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 7; 2024: 5; 2025: 4; 2026: 6.

22 papers.

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  1. 2023Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlookcited by 110
  2. 2023Bake off redux: a review and experimental evaluation of recent time series classification algorithmscited by 101
  3. 2024aeon: a Python toolkit for learning from time seriescited by 47
  4. 2023WEASEL 2.0 -- A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series Classificationcited by 15
  5. 2023QUANT: A Minimalist Interval Method for Time Series Classificationcited by 15
  6. 2025Learning Soft Sparse Shapes for Efficient Time-Series Classificationcited by 10
  7. 2023Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fieldscited by 8
  8. 2025MONSTER: Monash Scalable Time Series Evaluation Repositorycited by 6
  9. 2026The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classificationcited by 4
  10. 2025CLaP -- State Detection from Time Seriescited by 3
  11. 2026A Unified Shape-Aware Foundation Model for Time Series Classificationcited by 3
  12. 2023Convolutional and Deep Learning based techniques for Time Series Ordinal Classificationcited by 1
10 more
  1. 2023Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturingcited by 1
  2. 2026Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verificationcited by 1
  3. 2026In-Context Time Series Classification with Random Convolutional Featurescited by 1
  4. 2024Prevalidated ridge regression is a highly-efficient drop-in replacement for logistic regression for high-dimensional datacited by 0
  5. 2024Castor: Competing shapelets for fast and accurate time series classificationcited by 0
  6. 2024ECRTime: Ensemble Integration of Classification and Retrieval for Time Series Classificationcited by 0
  7. 2024Utilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasetscited by 0
  8. 2025Learning Interpretable Differentiable Logic Networks for Time-Series Classificationcited by 0
  9. 2026Time Series as Language: A Universal Tokenizer for General-Purpose Time Series Foundation Modelscited by 0
  10. 2026Revisiting WEASEL 2.0: Reproduction, Sensitivity, and an Adaptive Ensemble-Size Rulecited by 0