Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering

Ruiyu Xu; Chao Wang; Yongxiang Li; Jianguo Wu

doi:10.1109/TPAMI.2025.3534202

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Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering

Journal article

Peer reviewed

Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering

Ruiyu Xu, Chao Wang, Yongxiang Li and Jianguo Wu

IEEE transactions on pattern analysis and machine intelligence, Vol.47(5), pp.3611-3624

05/2025

DOI: 10.1109/TPAMI.2025.3534202

PMID: 40031358

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Abstract

Dictionary learning is an effective tool for pattern recognition and classification of time series data. However, real-world time series data often exhibit temporal misalignment due to temporal delay, scaling or other temporal transformations, which poses significant challenges for effective dictionary learning. Dynamic time warping (DTW) is commonly used for dealing with such misalignment issues. Nevertheless, the DTW suffers overfitting or information loss due to its discrete nature in aligning time series data. To address this issue, we propose a generalized time warping invariant dictionary learning algorithm in this paper. Our approach features a generalized time warping operator, which consists of linear combinations of continuous basis functions for facilitating continuous temporal warping. The integration of the proposed operator and the dictionary learning is formulated as an optimization problem, where the block coordinate descent method is employed to jointly optimize warping paths, dictionaries, and sparse coefficients. The optimized results are then used as hyperspace distance measures to feed classification and clustering algorithms. The superiority of the proposed method in terms of dictionary learning, classification, and clustering is validated through ten sets of public datasets in comparison with various benchmark methods.

Time series analysis

Machine learning

Dictionaries

Clustering algorithms

Optimization

Atoms

Kernel

Accuracy

Feature extraction

Heuristic algorithms

Time warping

dictionary learning

time series classification

time series clustering

Details

Title: Subtitle: Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering
Creators: Ruiyu Xu - Peking University
Chao Wang - University of Iowa
Yongxiang Li - Shanghai Jiao Tong University
Jianguo Wu - Peking University
Resource Type: Journal article
Publication Details: IEEE transactions on pattern analysis and machine intelligence, Vol.47(5), pp.3611-3624
DOI: 10.1109/TPAMI.2025.3534202
PMID: 40031358
NLM abbreviation: IEEE Trans Pattern Anal Mach Intell
ISSN: 0162-8828
eISSN: 2160-9292
Publisher: IEEE COMPUTER SOC; LOS ALAMITOS
Number of pages: 15
Grant note: NSFC: NSFC-72171003, NSFC-71932006, NSFC-72101147
This work was supported by the NSFC under Grant NSFC-72171003, Grant NSFC-71932006, and Grant NSFC-72101147.
Language: English
Electronic publication date: 2025
Date published: 05/2025
Academic Unit: Industrial and Systems Engineering
Record Identifier: 9984781273702771

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