Online Multi-Task Learning Framework for Ensemble Forecasting

By Jianpeng Xu, Pang-Ning Tan, Jiayu Zhou, Lifeng Luo. 2017

29 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Environmental Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Dacheng Tao
2. Qiang Yang
3. Yu Zhang
4. Xinchao Wang
5. Mingli Song
6. Yiding Yang
7. Yongcheng Jing
8. Mingsheng Long

In Electrical and Electronic Engineering

1. Yu Zhang
2. Qiang Yang
3. Dacheng Tao
4. Mingli Song
5. Yiding Yang
6. Xinchao Wang
7. Dongrui Wu
8. Vladlen Koltun

In Environmental Engineering

1. Dacheng Tao
2. Qiang Yang
3. Yu Zhang

Citations in the corpus

• A Survey on Multi-Task Learning (2017, methodology): “In [215], an online MTL algorithm with a restart strategy is proposed for ensemble forecasting on the seasonal soil moisture.”
• Amalgamating Knowledge from Heterogeneous Graph Neural Networks (2021, background): “In the past few years, multi-task learning has been widely studied in various areas, such as bioinformatics [10, 20], ubiquitous computing [39, 40], natural language processing [4, 38] and computer vision [21, 54, 15, 14].”