Classical and Contemporary Approaches to Big Time Series Forecasting
Summary: Tutorial surveying big time-series forecasting for data management: classical models, scalable tensor methods, and deep learning. Discusses learning from large, diverse corpora, leveraging similar series, and building scalable forecasting systems. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Christos Faloutsos (Amazon; Carnegie Mellon University)
- 2. Jan Gasthaus (Amazon)
- 3. Tim Januschowski (Amazon)
- 4. Yuyang Wang (Amazon)
BibTeX Citation
@inproceedings{faloutsos_sigmod19,
title = {{Classical and Contemporary Approaches to Big Time Series Forecasting}},
author = {Faloutsos, Christos and Gasthaus, Jan and Januschowski, Tim and Wang, Yuyang},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3314033},
url = {https://dl.acm.org/doi/10.1145/3299869.3314033},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,880 | RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection | 2021 | SIGMOD | 6.9478419e-05 |
| 4,027 | MagicScaler: Uncertainty-aware, Predictive Autoscaling | 2023 | VLDB | 6.8428173e-05 |
| 6,538 | AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting | 2023 | SIGMOD | 5.7511254e-05 |
| 9,662 | LightCTS: A Lightweight Framework for Correlated Time Series Forecasting | 2023 | SIGMOD | 5.142891e-05 |
| 13,618 | From Big Time Series Forecasting to Foundation Models for Structured Data | 2026 | VLDB | - |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 679 | StatStream: Statistical Monitoring of Thousands of Data Streams in Real Time | 2002 | VLDB | 0.00014831743 |
| 912 | Adaptive Stream Resource Management Using Kalman Filters | 2004 | SIGMOD | 0.0001310985 |
| 2,497 | Optimal Multi-scale Patterns in Time Series Streams | 2006 | SIGMOD | 8.382303e-05 |
| 3,463 | Prediction and Indexing of Moving Objects with Unknown Motion Patterns | 2004 | SIGMOD | 7.2799688e-05 |
| 5,270 | Forecasting Big Time Series: Old and New | 2018 | VLDB | 6.1993805e-05 |
| 5,308 | Probabilistic Demand Forecasting at Scale | 2017 | VLDB | 6.1844285e-05 |
| 5,397 | Adaptive, Hands-Off Stream Mining | 2003 | VLDB | 6.1479216e-05 |
| 12,768 | Parsimonious Linear Fingerprinting for Time Series | 2010 | VLDB | 4.9769913e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,789 | Database Workload Capacity Planning using Time Series Analysis and Machine Learning | 2020 | SIGMOD |
| 2 | 4,535 | SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting | 2023 | VLDB |
| 3 | 6,207 | Multiple Time Series Forecasting with Dynamic Graph Modeling | 2024 | VLDB |
| 4 | 7,096 | Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods | 2025 | VLDB |
| 5 | 3,433 | TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods | 2024 | VLDB |
| 6 | 4,185 | AutoAI-TS: AutoAI for Time Series Forecasting | 2021 | SIGMOD |
| 7 | 13,618 | From Big Time Series Forecasting to Foundation Models for Structured Data | 2026 | VLDB |
| 8 | 13,646 | Fully Automated Correlated Time Series Forecasting in Minutes | 2025 | VLDB |
| 9 | 10,283 | Mining and Forecasting of Big Time-series Data | 2015 | SIGMOD |
| 10 | 5,270 | Forecasting Big Time Series: Old and New | 2018 | VLDB |