4 citations · 7 across the 6 of their papers we have counts for
6 papers
Progressive Supervision via Label Decomposition: An Long-Term and Large-Scale Wireless Traffic Forecasting Method
Daojun Liang, Haixia Zhang, Dongfeng Yuan
Long-term and Large-scale Wireless Traffic Forecasting (LL-WTF) is pivotal for strategic network management and comprehensive planning on a macro scale. However, LL-WTF poses great…
Multi-Head Encoding for Extreme Label Classification
Daojun Liang, Haixia Zhang, Dongfeng Yuan +1
The number of categories of instances in the real world is normally huge, and each instance may contain multiple labels. To distinguish these massive labels utilizing machine learn…
Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data
Daojun Liang, Haixia Zhang, Jing Wang +2
In this paper, we find that existing online forecasting methods have the following issues: 1) They do not consider the update frequency of streaming data and directly use labels (f…
DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting
Daojun Liang, Haixia Zhang, Dongfeng Yuan
Traditional regression and prediction tasks often only provide deterministic point estimates. To estimate the distribution or uncertainty of the response variable, traditional meth…
Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals
Daojun Liang, Haixia Zhang, Dongfeng Yuan +2
In this paper, we find that ubiquitous time series (TS) forecasting models are prone to severe overfitting. To cope with this problem, we embrace a de-redundancy approach to progre…
Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?
Daojun Liang, Haixia Zhang, Dongfeng Yuan +3
As Transformer-based models have achieved impressive performance on various time series tasks, Long-Term Series Forecasting (LTSF) tasks have also received extensive attention in r…