mlsanityData to 7 Oct 2026

HYDRA: Competing convolutional kernels for fast and accurate time series classification

arXiv 2203.13652 ↗First posted 25 Mar 2022cs.LGcited by 53

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Abstract (arXiv)

We demonstrate a simple connection between dictionary methods for time series classification, which involve extracting and counting symbolic patterns in time series, and methods based on transforming input time series using convolutional kernels, namely ROCKET and its variants. We show that by adjusting a single hyperparameter it is possible to move by degrees between models resembling dictionary methods and models resembling ROCKET. We present HYDRA, a simple, fast, and accurate dictionary method for time series classification using competing convolutional kernels, combining key aspects of both ROCKET and conventional dictionary methods. HYDRA is faster and more accurate than the most accurate existing dictionary methods, and can be combined with ROCKET and its variants to further improve the accuracy of these methods.

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). Builds on 21 of its 34 references that are in the map. First posted on arXiv 25 Mar 2022.

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21 of 34 references.

References · 21

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2015Cyclical Learning Rates for Training Neural Networkscited by 627
  4. 2018Deep learning for time series classification: a reviewcited by 575
  5. 2018The UCR Time Series Archivecited by 421
  6. 2019InceptionTime: Finding AlexNet for Time Series Classificationcited by 386
  7. 2019ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernelscited by 336
  8. 2013Maxout Networkscited by 186
  9. 2020MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classificationcited by 186
  10. 2021HIVE-COTE 2.0: a new meta ensemble for time series classificationcited by 118
  11. 2015Should we really use post-hoc tests based on mean-ranks?cited by 116
  12. 2019catch22: CAnonical Time-series CHaracteristicscited by 103
9 more
  1. 2021MultiRocket: Multiple pooling operators and transformations for fast and effective time series classificationcited by 89
  2. 2019TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classificationcited by 67
  3. 2020The Canonical Interval Forest (CIF) Classifier for Time Series Classificationcited by 48
  4. 2017Fast and Accurate Time Series Classification with WEASELcited by 47
  5. 2018Proximity Forest: An effective and scalable distance-based classifier for time seriescited by 46
  6. 2020Interpretable Time Series Classification using Linear Models and Multi-resolution Multi-domain Symbolic Representationscited by 31
  7. 2021The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classificationcited by 26
  8. 2019Scalable Dictionary Classifiers for Time Series Classificationcited by 20
  9. 2018From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifierscited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 15; 2024: 8; 2025: 13; 2026: 17.

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  1. 2023Bake off redux: a review and experimental evaluation of recent time series classification algorithmscited by 99
  2. 2023Deep Learning for Time Series Classification and Extrinsic Regression: A Current Surveycited by 68
  3. 2023An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Setcited by 27
  4. 2023Inherently Interpretable Time Series Classification via Multiple Instance Learningcited by 23
  5. 2023WEASEL 2.0 -- A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series Classificationcited by 15
  6. 2023QUANT: A Minimalist Interval Method for Time Series Classificationcited by 15
  7. 2025Learning Soft Sparse Shapes for Efficient Time-Series Classificationcited by 10
  8. 2023Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fieldscited by 8
  9. 2024SeqNAS: Neural Architecture Search for Event Sequence Classificationcited by 8
  10. 2023Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelscited by 7
  11. 2025MONSTER: Monash Scalable Time Series Evaluation Repositorycited by 6
  12. 2023Proximity Forest 2.0: A new effective and scalable similarity-based classifier for time seriescited by 5
38 more
  1. 2025MASCOTS: Model-Agnostic Symbolic COunterfactual explanations for Time Seriescited by 5
  2. 2023POCKET: Pruning Random Convolution Kernels for Time Series Classification from a Feature Selection Perspectivecited by 4
  3. 2023Finding Foundation Models for Time Series Classification with a PreText Taskcited by 4
  4. 2025Random Feature Representation Boostingcited by 4
  5. 2025CLaP -- State Detection from Time Seriescited by 3
  6. 2026The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classificationcited by 3
  7. 2026MambaSL: Exploring Single-Layer Mamba for Time Series Classificationcited by 3
  8. 2023A hybrid feature learning approach based on convolutional kernels for ATM fault prediction using event-log datacited by 2
  9. 2024Nonlinear time-series embedding by monotone variational inequalitycited by 2
  10. 2024Classification of Raw MEG/EEG Data with Detach-Rocket Ensemble: An Improved ROCKET Algorithm for Multivariate Time Series Analysiscited by 2
  11. 2024Time series classification with random convolution kernels: pooling operators and input representations mattercited by 2
  12. 2025FIC-TSC: Learning Time Series Classification with Fisher Information Constraintcited by 2
  13. 2025Structural Classification of Locally Stationary Time Series Based on Second-order Characteristicscited by 2
  14. 2023Convolutional and Deep Learning based techniques for Time Series Ordinal Classificationcited by 1
  15. 2023Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximizationcited by 1
  16. 2023FRUITS: Feature Extraction Using Iterated Sums for Time Series Classificationcited by 1
  17. 2025Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detectioncited by 1
  18. 2026Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verificationcited by 1
  19. 2026Generating Financial Time Series by Matching Random Convolutional Featurescited by 1
  20. 2026In-Context Time Series Classification with Random Convolutional Featurescited by 1
  21. 2024MSTAR: Multi-Scale Backbone Architecture Search for Timeseries Classificationcited by 0
  22. 2024ECRTime: Ensemble Integration of Classification and Retrieval for Time Series Classificationcited by 0
  23. 2024Utilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasetscited by 0
  24. 2024A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Seriescited by 0
  25. 2025Adaptive Law-Based Transformation (ALT): A Lightweight Feature Representation for Time Series Classificationcited by 0
  26. 2025Random Projections and Natural Sparsity in Time-Series Classification: A Theoretical Analysiscited by 0
  27. 2025HIT-ROCKET: Hadamard-vector Inner-product Transformer for ROCKETcited by 0
  28. 2025When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregatecited by 0
  29. 2025A Regime-Aware Fusion Framework for Time Series Classificationcited by 0
  30. 2026Pruning Extensions and Efficiency Trade-Offs for Sustainable Time Series Classificationcited by 0
  31. 2026Random Neural Network Expressivity for Non-Linear Partial Differential Equationscited by 0
  32. 2026A Simple State Space Model Excels at Multivariate Time Series Classificationcited by 0
  33. 2026TimEE: End-to-end Time Series Classification via In-Context Learningcited by 0
  34. 2026Revisiting WEASEL 2.0: Reproduction, Sensitivity, and an Adaptive Ensemble-Size Rulecited by 0
  35. 2026Multi-Class Electrical and Mechanical Fault Classification Using Random Convolutional Kernelscited by 0
  36. 2026Contrastive Representation-Guided Genetic Minority Oversampling for Imbalanced Time-Series Classificationcited by 0
  37. 2026Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariancecited by 0
  38. 2026Local Reference Geometry Residual Augmentation for Imbalanced Time Series Classificationcited by 0

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