3 citations · 3 across the 4 of their papers we have counts for
5 papers · 1 filter
Online Ensemble Transformer for Accurate Cloud Workload Forecasting in Predictive Auto-Scaling
Jiadong Chen, Xiao He, Hengyu Ye +4
In the swiftly evolving domain of cloud computing, the advent of serverless systems underscores the crucial need for predictive auto-scaling systems. This necessity arises to ensur…
Fremer: Lightweight and Effective Frequency Transformer for Workload Forecasting in Cloud Services
Jiadong Chen, Hengyu Ye, Fuxin Jiang +4
Workload forecasting is pivotal in cloud service applications, such as auto-scaling and scheduling, with profound implications for operational efficiency. Although Transformer-base…
Disentangled Parameter-Efficient Linear Model for Long-Term Time Series Forecasting
Yuang Zhao, Tianyu Li, Jiadong Chen +3
Long-term Time Series Forecasting (LTSF) is crucial across various domains, but complex deep models like Transformers are often prone to overfitting on extended sequences. Linear F…
MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection
Bokai Lin, Zihao Zeng, Zipeng Xiao +5
KV cache has become a de facto technique for the inference of large language models (LLMs), where tensors of shape (layer number, head number, sequence length, feature dimension) a…
ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecasting
Hengyu Ye, Jiadong Chen, Shijin Gong +4
The intricate nature of time series data analysis benefits greatly from the distinct advantages offered by time and frequency domain representations. While the time domain is super…