Pruning hybrid time series classifiers including the new Hydrant combination can reduce energy consumption by up to 80% while keeping accuracy loss below 5%.
Multirocket: multiple pooling operators and transformations for fast and effective time series classification
3 Pith papers cite this work. Polarity classification is still indexing.
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cs.LG 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
CRAFTIIF uses 500 random analytic wavelet features across four families and five structured isolation forests to target four anomaly types, achieving first place on mTSBench VUS-PR at 0.463.
A review synthesizes evidence from EEG, EMG, ECG, PPG and ocular signals to argue that waveform morphology, rather than modality or model class, primarily determines TSC performance and interpretability.
citing papers explorer
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Pruning Extensions and Efficiency Trade-Offs for Sustainable Time Series Classification
Pruning hybrid time series classifiers including the new Hydrant combination can reduce energy consumption by up to 80% while keeping accuracy loss below 5%.
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CRAFTIIF: Cross-Resolution Analytic Four-Type Interpretable Isolation Forest for Multivariate Time Series Anomaly Detection
CRAFTIIF uses 500 random analytic wavelet features across four families and five structured isolation forests to target four anomaly types, achieving first place on mTSBench VUS-PR at 0.463.
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Modality vs. Morphology: A Framework for Time Series Classification for Biological Signals
A review synthesizes evidence from EEG, EMG, ECG, PPG and ocular signals to argue that waveform morphology, rather than modality or model class, primarily determines TSC performance and interpretability.