523 citations · 524 across the 3 of their papers we have counts for
6 papers
Hierarchical Transformer for Survival Prediction Using Multimodality Whole Slide Images and Genomics
Chunyuan Li, Xinliang Zhu, Jiawen Yao +1
Learning good representation of giga-pixel level whole slide pathology images (WSI) for downstream tasks is critical. Previous studies employ multiple instance learning (MIL) to re…
Hierarchical Proxy-based Loss for Deep Metric Learning
Zhibo Yang, Muhammet Bastan, Xinliang Zhu +2
Proxy-based metric learning losses are superior to pair-based losses due to their fast convergence and low training complexity. However, existing proxy-based losses focus on learni…
Whole Slide Images based Cancer Survival Prediction using Attention Guided Deep Multiple Instance Learning Networks
Jiawen Yao, Xinliang Zhu, Jitendra Jonnagaddala +2
Traditional image-based survival prediction models rely on discriminative patch labeling which make those methods not scalable to extend to large datasets. Recent studies have show…
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation
Jinyu Yang, Weizhi An, Sheng Wang +3
Unsupervised domain adaptation enables to alleviate the need for pixel-wise annotation in the semantic segmentation. One of the most common strategies is to translate images from t…
Robust Contextual Bandit via the Capped- norm
Feiyun Zhu, Xinliang Zhu, Sheng Wang +2
This paper considers the actor-critic contextual bandit for the mobile health (mHealth) intervention. The state-of-the-art decision-making methods in mHealth generally assume that…
Cohesion-based Online Actor-Critic Reinforcement Learning for mHealth Intervention
Feiyun Zhu, Peng Liao, Xinliang Zhu +2
In the wake of the vast population of smart device users worldwide, mobile health (mHealth) technologies are hopeful to generate positive and wide influence on people's health. The…