1 citations · 1 across the 5 of their papers we have counts for
7 papers
FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting
Qianyang Li, Xingjun Zhang, Shaoxun Wang +2
Large-scale retail and industrial forecasting systems contain many heterogeneous time series whose lifecycle, sparsity, volatility, seasonality, spectral patterns, and contextual s…
ASGMamba: Adaptive Spectral Gating Mamba for Multivariate Time Series Forecasting
Qianyang Li, Xingjun Zhang, Shaoxun Wang +2
Long-term multivariate time series forecasting (LTSF) plays a crucial role in various high-performance computing applications, including real-time energy grid management and large-…
DPWMixer: Dual-Path Wavelet Mixer for Long-Term Time Series Forecasting
Li Qianyang, Zhang Xingjun, Wang Shaoxun +1
Long-term time series forecasting (LTSF) is a critical task in computational intelligence. While Transformer-based models effectively capture long-range dependencies, they often su…
AWEMixer: Adaptive Wavelet-Enhanced Mixer Network for Long-Term Time Series Forecasting
Qianyang Li, Xingjun Zhang, Peng Tao +3
Forecasting long-term time series in IoT environments remains a significant challenge due to the non-stationary and multi-scale characteristics of sensor signals. Furthermore, erro…
DPANet: Dual Pyramid Attention Network for Multivariate Time Series Forecasting
Qianyang Li, Xingjun Zhang, Shaoxun Wang +1
Long-term time series forecasting (LTSF) is hampered by the challenge of modeling complex dependencies that span multiple temporal scales and frequency resolutions. Existing method…
Dual-pronged deep learning preprocessing on heterogeneous platforms with CPU, Accelerator and CSD
Jia Wei, Xingjun Zhang, Witold Pedrycz +2
For image-related deep learning tasks, the first step often involves reading data from external storage and performing preprocessing on the CPU. As accelerator speed increases and…
BEND: Bagging Deep Learning Training Based on Efficient Neural Network Diffusion
Jia Wei, Xingjun Zhang, Witold Pedrycz
Bagging has achieved great success in the field of machine learning by integrating multiple base classifiers to build a single strong classifier to reduce model variance. The perfo…