arXiv AI August 13, 2026 By Ziqiang Li, Yun Liu, Gouhei Tanaka

Robust and Efficient Noisy-Label Time-Series Classification via Dynamic Time Warping Based Granular Ball Computing

arXiv:2608. 11704v1 Announce Type: cross Abstract: Dynamic Time Warping (DTW)-based Nearest-Neighbor (NN) classifiers are effective for time-series classification but are vulnerable to mislabeled training samples and require numerous DTW computations during inference.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

benchmarks

arXiv Machine Learning

5d ago

Adaptive $k$ Nearest Neighbors Classifier via Granular Ball Computing

arXiv:2608. 12903v1 Announce Type: new Abstract: The $k$-Nearest Neighbor~(KNN) algorithm is widely used across various tasks.

By Xiaoyu Lian, Shuyin Xia, Hongxuan He, Lifeng Shen, Guoyin Wang, Xinbo Gao

arXiv Machine Learning

Jun 11

Efficient Time Series Clustering from Multiscale Reservoir Dynamics with Granular-Ball Anchoring Graph Optimization

arXiv:2606. 12077v1 Announce Type: new Abstract: Time-series clustering remains challenging due to the inherent trade-off between clustering effectiveness and computational efficiency.

By Yifan Wang, Lifeng Shen, Shuyin Xia, Yi Wang

benchmarks

arXiv AI

Jul 9

TimEE: End-to-end Time Series Classification via In-Context Learning

arXiv:2607. 07500v1 Announce Type: cross Abstract: Time series classification (TSC) is dominated by a two-stage paradigm: train a feature encoder -- either from scratch on the target dataset or via pretraining on large corpora -- and then fit a task-specific classifier on top.

By Jaris K\"uken, Shi Bin Hoo, Martin Mr\'az, Frank Hutter, Lennart Purucker

llms benchmarks

arXiv AI

Jul 14

Rethinking Zero-Shot Time Series Classification: From Task-specific Classifiers to In-Context Inference

arXiv:2602. 00620v2 Announce Type: replace-cross Abstract: The zero-shot evaluation of time series foundation models (TSFMs) for classification typically uses a frozen encoder followed by a task-specific classifier.

By Juntao Fang, Shifeng Xie, Shengbin Nie, Yuhui Ling, Yuming Liu, Zijian Li, Keli Zhang, Lujia Pan, Themis Palpanas, Ruichu Cai

llms safety

arXiv Machine Learning

Jul 22

In-Context Time Series Classification with Random Convolutional Features

arXiv:2607. 19234v1 Announce Type: new Abstract: Time series classification is central to domains like medical signal analysis, industrial monitoring, and sensor-based activity recognition, where class information manifests as localized shapes, specific frequencies, temporal shifts, or complex cross-channel interactions.

By Joscha C\"uppers, Jilles Vreeken

benchmarks

arXiv AI

Aug 11

FreSH: Frequency-Segmented Hierarchical Multi-Expert Framework for Multivariate Time Series Classification

arXiv:2608. 08207v1 Announce Type: cross Abstract: Multivariate Time Series Classification (MTSC) demands models that can effectively capture complex temporal patterns across multiple scales while remaining computationally efficient.

By Pingping Liu, Muyao Wang, Zijian Zhang, Tongshun Zhang, Hao Miao, Guorui Xie, Qingliang Li, Qiuzhan Zhou

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Adaptive $k$ Nearest Neighbors Classifier via Granular Ball Computing

Efficient Time Series Clustering from Multiscale Reservoir Dynamics with Granular-Ball Anchoring Graph Optimization

TimEE: End-to-end Time Series Classification via In-Context Learning

Rethinking Zero-Shot Time Series Classification: From Task-specific Classifiers to In-Context Inference

In-Context Time Series Classification with Random Convolutional Features

FreSH: Frequency-Segmented Hierarchical Multi-Expert Framework for Multivariate Time Series Classification