30 citations · 96 across the 12 of their papers we have counts for
6 papers · 1 filter
SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing
Sheng Li, Geng Yuan, Yue Dai +3
There has been a proliferation of artificial intelligence applications, where model training is key to promising high-quality services for these applications. However, the model tr…
Trustworthy Representation Learning Across Domains
Ronghang Zhu, Dongliang Guo, Daiqing Qi +3
As AI systems have obtained significant performance to be deployed widely in our daily live and human society, people both enjoy the benefits brought by these technologies and suff…
pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting
Yunyi Zhou, Zhixuan Chu, Yijia Ruan +3
Various probabilistic time series forecasting models have sprung up and shown remarkably good performance. However, the choice of model highly relies on the characteristics of the…
Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training
Geng Yuan, Yanyu Li, Sheng Li +5
Recently, sparse training has emerged as a promising paradigm for efficient deep learning on edge devices. The current research mainly devotes efforts to reducing training costs by…
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials
Zhixuan Chu, Stephen L. Rathbun, Sheng Li
Estimating treatment effects from observational data provides insights about causality guiding many real-world applications such as different clinical study designs, which are the…
Correlative Channel-Aware Fusion for Multi-View Time Series Classification
Yue Bai, Lichen Wang, Zhiqiang Tao +2
Multi-view time series classification (MVTSC) aims to improve the performance by fusing the distinctive temporal information from multiple views. Existing methods mainly focus on f…