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Less is More: Efficient Time Series Dataset Condensation via Two-fold Modal Matching
Summary: TimeDC compresses large time-series datasets so models trained on condensed data achieve performance comparable to full datasets. It uses two-fold modal matching—decomposition-driven frequency matching to preserve temporal/frequency structure and curriculum training trajectory matching with an expert-buffer to cut memory/compute during condensation.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13877
- Venue
- VLDB
- Year
- 2025
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,609 | 26.27%
- DOI
-
10.14778/3705829.3705841
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No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
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Year |
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| 1,925 |
Apache IoTDB: Time-series Database for Internet of Things |
2020 |
VLDB |
0.00010073156 |
| 2,274 |
ModelarDB: Modular Model-Based Time Series Management with Spark and Cassandra |
2018 |
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9.1432785e-05 |
| 2,645 |
Camel: Managing Data for Efficient Stream Learning |
2022 |
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8.3768838e-05 |
| 3,322 |
Sketching Linear Classifiers over Data Streams |
2018 |
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7.217965e-05 |
| 4,082 |
Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series |
2023 |
VLDB |
6.4601453e-05 |
| 4,103 |
GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data |
2023 |
SIGMOD |
6.4460899e-05 |
| 4,110 |
RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection |
2021 |
SIGMOD |
6.4358092e-05 |
| 5,070 |
Time Series Data Encoding for Efficient Storage: A Comparative Analysis in Apache IoTDB |
2022 |
VLDB |
5.7133478e-05 |
| 5,449 |
Multiple Time Series Forecasting with Dynamic Graph Modeling |
2024 |
VLDB |
5.4980173e-05 |
| 6,329 |
Efficient Construction of Approximate Ad-Hoc ML models Through Materialization and Reuse |
2018 |
VLDB |
5.1030159e-05 |
| 6,589 |
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2023 |
SIGMOD |
4.9964862e-05 |
| 6,849 |
Time2Feat: Learning Interpretable Representations for Multivariate Time Series Clustering |
2023 |
VLDB |
4.903714e-05 |
| 8,386 |
PACE: Learning Effective Task Decomposition for Human-in-the-loop Healthcare Delivery |
2021 |
SIGMOD |
4.525798e-05 |
| 9,254 |
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2023 |
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4.3648789e-05 |
| 9,329 |
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2023 |
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4.351469e-05 |
| 10,637 |
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4.1905499e-05 |
| 11,044 |
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VLDB |
4.1905499e-05 |
| 11,147 |
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VLDB |
4.1905499e-05 |
| 13,127 |
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2025 |
VLDB |
- |
| 13,129 |
A Memory Guided Transformer for Time Series Forecasting |
2025 |
VLDB |
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