Forecasting Big Time Series: Old and New
Summary: Tutorial on forecasting at scale, spanning classical models, scalable tensor methods, and deep learning for leveraging similarities across massive, heterogeneous time-series collections. Distills practical lessons from building production forecasting systems. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Christos Faloutsos (Amazon; Carnegie Mellon University)
- 2. Jan Gasthaus (Amazon AI Labs)
- 3. Tim Januschowski (Amazon AI Labs)
- 4. Yuyang Wang (Amazon AI Labs)
BibTeX Citation
@article{faloutsos_vldb18,
title = {{Forecasting Big Time Series: Old and New}},
author = {Faloutsos, Christos and Gasthaus, Jan and Januschowski, Tim and Wang, Yuyang},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {12},
pages = {2102--2105},
doi = {10.14778/3229863.3229878},
url = {https://doi.org/10.14778/3229863.3229878},
year = {2018}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,520 | Classical and Contemporary Approaches to Big Time Series Forecasting | 2019 | SIGMOD | 6.5628257e-05 |
| 8,026 | TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications | 2023 | VLDB | 5.4045222e-05 |
| 9,077 | A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis | 2024 | VLDB | 5.2283159e-05 |
| 10,607 | WaveStitch: Flexible and Fast Conditional Time Series Generation With Diffusion Models | 2026 | SIGMOD | 4.9793485e-05 |
| 11,607 | A Flexible Forecasting Stack | 2024 | VLDB | 4.9793485e-05 |
| 11,668 | Weakly Guided Adaptation for Robust Time Series Forecasting | 2024 | VLDB | 4.9793485e-05 |
| 13,612 | From Big Time Series Forecasting to Foundation Models for Structured Data | 2026 | VLDB | - |
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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 |
|---|---|---|---|---|
| 78 | Automatic Database Management System Tuning Through Large-scale Machine Learning | 2017 | SIGMOD | 0.00036684414 |
| 460 | Query-based Workload Forecasting for Self-Driving Database Management Systems | 2018 | SIGMOD | 0.00017842695 |
| 678 | StatStream: Statistical Monitoring of Thousands of Data Streams in Real Time | 2002 | VLDB | 0.00014838454 |
| 2,497 | Optimal Multi-scale Patterns in Time Series Streams | 2006 | SIGMOD | 8.3861855e-05 |
| 3,462 | Prediction and Indexing of Moving Objects with Unknown Motion Patterns | 2004 | SIGMOD | 7.2834147e-05 |
| 5,304 | Probabilistic Demand Forecasting at Scale | 2017 | VLDB | 6.1873575e-05 |
| 5,390 | Adaptive, Hands-Off Stream Mining | 2003 | VLDB | 6.1508226e-05 |
| 12,762 | Parsimonious Linear Fingerprinting for Time Series | 2010 | VLDB | 4.9793485e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,534 | SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting | 2023 | VLDB |
| 2 | 6,783 | Database Workload Capacity Planning using Time Series Analysis and Machine Learning | 2020 | SIGMOD |
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| 5 | 7,094 | Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods | 2025 | VLDB |
| 6 | 4,185 | AutoAI-TS: AutoAI for Time Series Forecasting | 2021 | SIGMOD |
| 7 | 13,612 | From Big Time Series Forecasting to Foundation Models for Structured Data | 2026 | VLDB |
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| 9 | 10,277 | Mining and Forecasting of Big Time-series Data | 2015 | SIGMOD |
| 10 | 4,520 | Classical and Contemporary Approaches to Big Time Series Forecasting | 2019 | SIGMOD |