192 citations · 259 across the 5 of their papers we have counts for
6 papers · 1 filter
Meta-learning with an Adaptive Task Scheduler
Huaxiu Yao, Yu Wang, Ying Wei +4
To benefit the learning of a new task, meta-learning has been proposed to transfer a well-generalized meta-model learned from various meta-training tasks. Existing meta-learning al…
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
Yifan Zhang, Ying Wei, Peilin Zhao +4
Deep learning based medical image diagnosis has shown great potential in clinical medicine. However, it often suffers two major difficulties in practice: 1) only limited labeled sa…
Graph Few-shot Learning via Knowledge Transfer
Huaxiu Yao, Chuxu Zhang, Ying Wei +5
Towards the challenging problem of semi-supervised node classification, there have been extensive studies. As a frontier, Graph Neural Networks (GNNs) have aroused great interest r…
Transferable Neural Processes for Hyperparameter Optimization
Ying Wei, Peilin Zhao, Huaxiu Yao +1
Automated machine learning aims to automate the whole process of machine learning, including model configuration. In this paper, we focus on automated hyperparameter optimization (…
Hierarchically Structured Meta-learning
Huaxiu Yao, Ying Wei, Junzhou Huang +1
In order to learn quickly with few samples, meta-learning utilizes prior knowledge learned from previous tasks. However, a critical challenge in meta-learning is task uncertainty a…
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction
Huaxiu Yao, Yiding Liu, Ying Wei +2
Spatial-temporal prediction is a fundamental problem for constructing smart city, which is useful for tasks such as traffic control, taxi dispatching, and environmental policy maki…