Nearest-neighbor radii converge almost surely and obey local-dimension moment bounds under polynomial and geometric mixing dependence.
IEEE/CAA Journal of Automatica Sinica , volume=
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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UNVERDICTED 3representative citing papers
TimeTok is a unified framework using hierarchical tokenization for granularity-controllable time-series generation that achieves state-of-the-art performance in standard tasks and shows transferability across heterogeneous datasets.
Di-COT is an unsupervised contrastive method that stochastically partitions time-series windows into overlapping sub-blocks to learn representations without augmentation, reporting SOTA results on classification and transfer tasks across multiple benchmarks while cutting training time.
citing papers explorer
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Nearest-Neighbor Radii under Dependent Sampling
Nearest-neighbor radii converge almost surely and obey local-dimension moment bounds under polynomial and geometric mixing dependence.
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TimeTok: Granularity-Controllable Time-Series Generation via Hierarchical Tokenization
TimeTok is a unified framework using hierarchical tokenization for granularity-controllable time-series generation that achieves state-of-the-art performance in standard tasks and shows transferability across heterogeneous datasets.
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Divide and Contrast: Learning Robust Temporal Features without Augmentation
Di-COT is an unsupervised contrastive method that stochastically partitions time-series windows into overlapping sub-blocks to learn representations without augmentation, reporting SOTA results on classification and transfer tasks across multiple benchmarks while cutting training time.