4 citations · 7 across the 5 of their papers we have counts for
5 papers
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…
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…
A General 3D Non-Stationary Wireless Channel Model for 5G and Beyond
Ji Bian, Cheng-Xiang Wang, Xiqi Gao +2
In this paper, a novel three-dimensional (3D) non-stationary geometry-based stochastic model (GBSM) for the fifth generation (5G) and beyond 5G (B5G) systems is proposed. The propo…