2 citations · 4 across the 7 of their papers we have counts for
7 papers
Probabilistic Modeling of Multi-rater Medical Image Segmentation for Diversity and Personalization
Ke Liu, Shangde Gao, Yichao Fu +3
Lesion segmentation is inherently influenced by imaging uncertainty, arising from ill-defined lesion boundaries and inter-observer variability in diagnosis. To address this challen…
Matrix Factorization with Dynamic Multi-view Clustering for Recommender System
Shangde Gao, Ke Liu, Yichao Fu +2
Matrix factorization (MF), a cornerstone of recommender systems, decomposes user-item interaction matrices into latent representations. Traditional MF approaches, however, employ a…
KAER: Knowledge Adaptive Amalgamation of ExpeRts for Medical Images Segmentation
Shangde Gao, Yichao Fu, Ke Liu +2
Recently, many foundation models for medical image analysis such as MedSAM, SwinUNETR have been released and proven to be useful in multiple tasks. However, considering the inheren…
Unified Matrix Factorization with Dynamic Multi-view Clustering
Shangde Gao, Ke Liu, Yichao Fu
Matrix factorization (MF) is a classical collaborative filtering algorithm for recommender systems. It decomposes the user-item interaction matrix into a product of low-dimensional…
Contrastive Knowledge Amalgamation for Unsupervised Image Classification
Shangde Gao, Yichao Fu, Ke Liu +1
Knowledge amalgamation (KA) aims to learn a compact student model to handle the joint objective from multiple teacher models that are are specialized for their own tasks respective…
Feature Map Testing for Deep Neural Networks
Dong Huang, Qingwen Bu, Yahao Qing +2
Due to the widespread application of deep neural networks~(DNNs) in safety-critical tasks, deep learning testing has drawn increasing attention. During the testing process, test ca…
PACER: A Fully Push-forward-based Distributional Reinforcement Learning Algorithm
Wensong Bai, Chao Zhang, Yichao Fu +3
In this paper, we propose the first fully push-forward-based distributional reinforcement learning algorithm, named PACER, which consists of a distributional critic, a stochastic a…