SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting

Summary: SimpleTS: a universal, efficient model-selection framework for time-series forecasting that classifies each input series into a type and selects a model, using model-clustering to prune candidates. Introduces soft-labeling and weighted representation learning to boost classification accuracy; empirically faster and more accurate than prior toolkits (AutoAITS/AutoForecast) on 52 public + 3 private datasets. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13203
Venue: VLDB
Year: 2023
Pagerank: 6.6175631e-05
Overall Rank: 3,934 | 72.64%
DOI: 10.14778/3611540.3611561

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,298	TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods	2024	VLDB	9.0742746e-05
9,915	Camel: Efficient Compression of Floating-Point Time Series	2024	SIGMOD	4.2561557e-05
10,750	Quantifying Point Contributions: A Lightweight Framework for Efficient and Effective Query-Driven Trajectory Simplification	2025	VLDB	4.1945683e-05
11,059	DARKER: Efficient Transformer with Data-driven Attention Mechanism for Time Series	2024	VLDB	4.1945683e-05
11,108	A Demonstration of TENDS: Time Series Management System based on Model Selection	2024	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
921	Democratizing Data Science through Interactive Curation of ML Pipelines	2019	SIGMOD	0.00015337438
1,045	Adaptive Stream Resource Management Using Kalman Filters	2004	SIGMOD	0.00014472777
3,184	AutoAI-TS: AutoAI for Time Series Forecasting	2021	SIGMOD	7.4198086e-05
4,113	RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection	2021	SIGMOD	6.4420064e-05
4,947	Efficient Temporal Pattern Mining in Big Time Series Using Mutual Information	2022	VLDB	5.8123636e-05
5,242	Towards Benchmarking Feature Type Inference for AutoML Platforms	2021	SIGMOD	5.6074743e-05
5,704	Imminence Monitoring of Critical Events: A Representation Learning Approach	2021	SIGMOD	5.3636151e-05
6,004	Compression of Uncertain Trajectories in Road Networks	2020	VLDB	5.2415551e-05
8,286	OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting	2023	VLDB	4.5435639e-05
9,446	TRACE: Real-time Compression of Streaming Trajectories in Road Networks	2021	VLDB	4.3404859e-05

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
4,079	Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series	2023	VLDB	6.4663636e-05
11,200	LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation	2023	SIGMOD	4.1945683e-05
9,324	LightCTS: A Lightweight Framework for Correlated Time Series Forecasting	2023	SIGMOD	4.3556432e-05
2,298	TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods	2024	VLDB	9.0742746e-05
5,026	AutoCTS: Automated Correlated Time Series Forecasting	2022	VLDB	5.7528419e-05
4,888	Forecasting Big Time Series: Old and New	2018	VLDB	5.8531064e-05
4,476	Classical and Contemporary Approaches to Big Time Series Forecasting	2019	SIGMOD	6.1517903e-05
10,738	TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection	2025	VLDB	4.1945683e-05
13,113	Fully Automated Correlated Time Series Forecasting in Minutes	2025	VLDB	-
3,184	AutoAI-TS: AutoAI for Time Series Forecasting	2021	SIGMOD	7.4198086e-05